the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Feb 2021
Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier
Abstract. Accurately assessing landform evolution and quantifying rapid environmental changes are gaining importance in the context of monitoring techniques in alpine environments. In the European Alps, glaciers and rock glaciers are among the most characteristic cryospheric components bearing the most prolonged monitoring periods. This study introduces a rigorous procedure to quantify rock glacier kinematics and their associated uncertainty derived from sequential unmanned aerial vehicle (UAV) surveys. High-resolution digital elevation models (DEMs) and orthomosaics are derived from UAV image series combined with structure from motion (SfM) photogrammetry techniques. Multitemporal datasets are employed for measuring spatially continuous rock glacier kinematics using image matching algorithms. This procedure is tested on seven consecutive (from 2016 to 2019) UAV surveys of Tsarmine rock glacier, Valais Alps, Switzerland. The evaluation of superficial displacements was performed with simultaneous in-situ differential global navigation satellite system (GNSS) measurements. During the study period, the rock glacier doubled its overall frontal velocity, from around 5 m yr−1 between October 2016 and June 2017 to more than 10 m yr−1 between June and September 2019. Using the adequate UAV survey acquisition, processing, and validation steps, we almost achieved the same accuracy as the GNSS-derived velocities. Nevertheless, the proposed monitoring method provides accurate surface velocity fields values, which allow an enhanced description of the current rock glacier dynamics and its surface expression.
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Interactive discussion
Status: closed
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RC1: 'Comment on esurf-2021-8', Gernot Seier, 02 Apr 2021
Dear authors,
Your manuscript entitled ‘Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier’ intends to show the added value of using UAVs and Structure-from-Motion-based photogrammetry for the quantification of rock glacier dynamics. The study is based on the comparison and analyses of photogrammetrically processed images acquired in the period 2016 to 2019. The manuscript aims at proposing technology-immanent benefits of using UAVs for rock glacier monitoring. As the main outcome, kinematic and volumetric changes and its variations and characteristics are presented.
Due to the general arguments and some detailed comments, I think that the manuscript needs amendment, please see my remarks as follows. In addition, even though I am not a native English speaker, I think the text is basically well-prepared and requires minor proof-reading only.
According to the manuscript’s title and presentation, the main aim of your contribution is to introduce UAVs in rock glacier monitoring and to propose SfM-photogrammetric UAV surveys as favorable approach compared to established techniques. This assumption is a central issue because even though UAVs are not as long in use as other methods and devices, today, UAVs are already established in geosciences. Therefore, research based on UAVs should either focus on methodological questions, which is not case in your study, or otherwise should in detail discuss and explain geomorphological changes, which rather should be the aim of your manuscript. Therefore, I think it is necessary to revise the title and presentation of the manuscript. In addition, as there are other previous studies, please expand the relating literature discussing UAV-based surveys on rock glaciers. Also, the discussion on relating studies as in the present form needs revisions, please see my detailed comments concerning P12L362-376.
In terms of validation of the UAV-based results, geodetic measurements are shown in order to independently assess the quality. However, the way of how the UAV survey-related design and the relating provided information are presented does not allow to completely comprehend the methodological benefits. Several details concerning the survey design, such as the planned and actual flight paths and coverages, the estimated theoretical precision compared to actual achieved precision, the details of processing including, e.g., the quality of tie points on the image plain, as well as a dimensionless theoretical assessment of the achieved quality are just some but relevant information that would help to promote UAV-based surveys, which is not the case in the current form of the manuscript. I think that such a methodological discussion and information is the prerequisite for a technology-featuring presentation of the manuscript. In contrast, the manuscript appears as a well designed and presented case study of a rock glacier’s kinematics but does not introduce new methodological approaches and therefore, should focus on the characteristics and specifics of the landform investigated. In this sense, it appears rather inappropriate to contend that UAVs are a new method for rock glacier monitoring as this is not the case.
Concerning the survey design it would be necessary to first define what is required in terms of survey quality and the landform investigated in order to then conclude whether it was appropriate or not. Instead, the manuscript is characterized by a rather vague survey concept in order to subsequently conclude that the results are quite appropriate. In other words, at first it should be declared what survey quality is strived and estimated, which would then allow for assessing whether or whether not the results are appropriate.
The description of the processing needs revision. Without presenting and discussing photogrammetrically relevant parameters, such as exterior and interior orientation parameters, the quality of tie points and residuals of GCPs, photogrammetric studies are not comprehensible and meaningful. Therefore, the robust and detailed workflow that is stressed by the authors lacks these important components, which I think needs to be amended and the formulation revised. In addition, today, numerous articles are based on SfM-MVS photogrammetry. I suggest to expand and discuss the relevant literature in more detail, as there is no ample discussion and interrelationship with existing subject-specific literature yet.
Other methodological questions could deal with potential issues using the RTK-based survey configuration, e.g., are UAV-based surveys solely using direct georeferencing really capable of achieving the required quality? This could be worth discussing.
The presentation of the rock glacier’s velocities based on an area-based matching algorithm needs revisions. The validation of the velocity values should be expanded and the description revised, as the matching settings (grid size, correlation window size) are necessarily adjusted to the specific case and pair of images, e.g., the approx. 13 m large windows should be able to track 13 m long displacements (cf. P8L227). As a consequence, this results in high correlation values (R2 values presented in Section 4.1) and therefore, such a comparison of geodetically and NCC-derived velocities inherently cannot be completely independent. And this at least should be mentioned. Similarly, the presentation of the movement’s directional quality (Section 4.2) could be more comprehensible by explicitly mentioning that the directions were smoothed, as a directional filter was applied (Section 3.3).
The surface velocity fields should be revised, as thus far, categories of different velocities are presented and instead, vectors that show the exact displacement value should be presented, which also would allow for including and presenting the displacement vector-specific LoD value. As mentioned in Section 3.3 (P9L251), it would be a real benefit for the reader if these vector-specific LoDs would be shown in maps.
Detailed comments:
P1L10-11: As the survey configuration details are not completely outlined, it is not tenable to contend that a rigorous procedure is introduced.
P1L20-21: As the comparison with GNSS-based measurements is mentioned here and the description of the rock glacier dynamics, the main research contribution is the investigation of the specific rock glacier’s dynamics and behavior rather than methodological questions.
P2L36-48: What about rock glacier kinematic surveys beyond the European Alps?
P2L52-53: Style – “[…], evidence of […] identified as evident signs […]”.
P2L61: Style – “The quantification […] has been measured […]”.
P3L72: “[…] Unmanned Aerial Vehicles (UAV) systems […]”. Plural ending not correct, please check throughout the manuscript.
P3L79-80: Expand the list of published studies dealing with UAV-based rock glacier surveys. As there are already studies demonstrating the benefits and challenges of UAV-based rock glacier surveys and as generally, the landform rock glacier does not entail a specific methodological treatment compared to other landforms and as SfM photogrammetric UAV-based surveys are today already established, this cannot be the research question.
P3L81: Yes, but both a protocol and relevant details of the UAV-related configuration and processing are not discussed in this manuscript and therefore, this should not be mentioned and understood as the research question.
P3L82: It is meant “[…] high altitude […]“, please clarify.
P3L84-85: General statement that I do not support. One could also argue, as the surface velocities are in a hardly observable cm-range, a thorough validation is necessary. Therefore, no, different rock glacier velocities are not an argument.
P3L86: So far it was not mentioned in the manuscript that the quality of kinematic data is an issue, so, maybe it should be clarified at first that kinematic measurements are of diverse quality, which is why a thorough validation is necessary.
P3L92-93: This is the formulation of the study’s aims, which are a better understanding of the rock glacier behavior and dynamics. Therefore, your study contributes to rock glacier monitoring rather than the technique or methodological questions and therefore, the presentation should not focus on UAVs for the simple reason that these are maybe not that commonly used on rock glaciers yet, which is, if indeed, possibly coherent with the number of rock glacier studies.
P4L111: “[…] 2016. the []”.
P4L114: Please clarify, that this specific landform “Tsarmine” was meant.
P5L427: As it is a specific number of points (58), it cannot be “around”.
P5L132: I would say that 2 cm are also in the cm range, please clarify.
P5L141: Table 2 is mentioned before Table 1, modify.
P5L152: Add the focal length’s unit.
P5L154: Do you really mean “accuracy” of the RTK-based camera positions, as I cannot see the relationship to other, independent measurements, please clarify.
P5L155: Explicitly mention that the low accuracy is too low in terms of the study-relating aims, because low accuracy per se could still suffice.
P5L155-156: Please expand with a few words the tests mentioned in order to make the statement more comprehensible. In addition, with “mainly” you mean “mostly”?
P6L160-161: As you describe the planned image overlap of your survey, a citation does not make sense; delete the reference or clarify.
P7L198: It should be “[…] GCPs next to the […]” or similar.
P7L203: In order to discuss the quality of the bundle adjustment it is necessary to present and discuss the data of exterior and interior orientation parameters and the quality of the tie points.
P7L210: Check plural ending and indefinite article. Also, mention for clarity that the orthomosaics were resampled to 0.01 m, as the GSDs differed (cf. Table 1).
P7L213: Mention the subsections number instead of “previous step”, as this would be clearer.
P7L21-216: As you describe the principle, it does not make sense to relate to rock glaciers; the principle is valid for every surface surveyed.
P7L217: With “extensive” it is meant “larger”, which is more applicable, I think.
P8L237: Please check with the journal requirements whether or not the citation (“their Fig 2”) is appropriate.
P8L240: As it is a specific number of points (69), it cannot be “around”. Also, show the 69 subareas in the map.
P9L255: As it is a specific number of points (35), it cannot be “ca.”. Moreover, I cannot find the relating results of the mentioned comparison. In addition, show the spatial distribution of these 35 points in a map, as this is not the case yet.
P9L272: For understanding: these are the same 35 points mentioned in Section 3.4 (here used as independent z check points)?
P9L274: Is the term ‘significant’ in the sense of statistically significant appropriate here?
P11L335-337: Agree, but why are then the relating details of acquisition, processing and analysis not presented yet?
P11L337-339: Disagree, the inability of potentially new UAV-users cannot be anticipated, which is also attenuated by the high degree of automatization and usability of modern UAVs. Also, the depreciation of commercial UAV flight providers is not comprehensible as the necessary information needs to be negotiated and should be part of the contract, which is why commercial UAV survey providers of course could deliver the required data and metadata.
P11L342: This discussion could be more controversial as 30 minutes could be the net flight time, but usually the setup and pre-flight checks also need time as well as accompanying geodetic measurements and moreover, UAV flights are more weather-dependent (so probably it is necessary to wait for optimum conditions), which is why usually a UAV survey takes remarkably more time than 30 minutes.
P12L344: The different LoD values resulting from NCC and GNSS are not completely shown yet, only partially in Table 3.
P12L352: Elaborate, what are the “[…] suitable environmental conditions […]”? In addition, what is the point of “ […] that means about four months a year […]”? Usually, also geodetic surveys (except permanent measurements of a single point) are conducted in the snow-free season, so this is not specific for UAV surveys.
P12L350-356: This is a rather general discussion and the relating pros and cons were not investigated in the study.
P12L360-361: As it is obviously necessary to make SfM photogrammetric studies more comprehensible using protocols and standards, consequently, why don’t you present and discuss the complete survey details including planning, theoretical and actual quality estimates, processing settings etc.?
P12L362-376: This is a repetition of how (only) some others (i.e. not all relating studies) performed UAV-based studies on rock glaciers and as the text passage stresses you performed something what others did not, the character of this text passage is rather contemptuous. Therefore, I suggest to revise or exclude this text passage.
P12L373: Disagree, it cannot be concluded that companies are not willing to deliver what is necessary, it is rather necessary to adequately negotiate a contract by those interested in processing the data.
P12L374: The term “intrinsic” is distracting, as interior orientation parameters could be meant with this but which are not presented in Table 2 or elsewhere in the manuscript.
P12L375: To perform all working steps by oneself is not a guarantee for high-quality results. I fail to see any argument and therefore suggest to revise or exclude this paragraph.
P13L395: Add “[…] Tsarmine rock glacier […]” for clarity.
P14L411-412: Not the kinematic points but their velocities are shown.
P14L432: Which proposed uncertainty analysis you are relating to here? I cannot find relating data.
P14L434: Disagree, there are no details presented concerning the customized data acquisition and robustness of processing.
P14L434-440: As UAV-based SfM-photogrammetric studies are already established and as the landform of rock glaciers does not entail any specific methodological adaptations, I fail to understand what is concluded in this text passage and therefore suggest revision.
P15L449: Disagree, the current form of the manuscript does not show all details relevant in SfM-photogrammetric studies.
P18L564: The list of references needs revision, e.g., the publication in P18L564, which is not mentioned in the text yet.
Figure 4: In the legend: shouldn’t the category be “1-LoD” instead of “LoD-1”? As already mentioned, I think it would be favorable to show real vectors instead of categories, which would then also allow to show the displacement-specific LoD values.
Figure 6: The hillshade could be more low-contrast or so, which would then probably better allow to perceive the lines.
Figure 7: The categories of elevation differences are partially overlapping and therefore, seem to be wrong, e.g., categories “-4.50 to -3.70” m and “-3.80 to -3.00” m etc.
Table 1: This table could be expanded with values of theoretically achievable precision estimates, which are survey configuration-specific.
Table 2: Expand the table by showing both, the RMSEs of GCPs and CPs on the modelled surface as well as the image plane.
Table 3: Mention the relating confidence interval.
I hope you will find my comments appropriate,
Gernot Seier
Citation: https://doi.org/10.5194/esurf-2021-8-RC1 -
AC1: 'Reply on RC1', Sebastián Vivero, 12 May 2021
We want to thank Gernot Seier for his technical review that will help to improve some essential aspects of the manuscript.
We agree with most of the general and detailed comments made (as explained below) and modified the manuscript accordingly.
The referee comments are in italic (red) font, and our responses and revisions are in normal (black) font.
General comments:
Your manuscript entitled ‘Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier’ intends to show the added value of using UAVs and Structure-from-Motion-based photogrammetry for the quantification of rock glacier dynamics. The study is based on the comparison and analyses of photogrammetrically processed images acquired in the period 2016 to 2019. The manuscript aims at proposing technology-immanent benefits of using UAVs for rock glacier monitoring. As the main outcome, kinematic and volumetric changes and its variations and characteristics are presented.
We learnt from your comments and agree with your central assessment that our aims and arguments concerning the benefits of using UAV monitoring techniques in rock glaciers were not well understood. Our objectives are to propose and explore a monitoring method for rock glaciers using UAV-derived data validated on a destabilized rock glacier. Our study's findings can potentially contribute to established permafrost monitoring networks (like PERMOS). As explained during the first introductory paragraph, rock glacier dynamics cannot be directly measured by remote sensing techniques alone (i.e. UAV-SfM). Therefore, we claim that our paper deals with quantifying rock glacier kinematics (i.e. change in geometry with time), which is a piece of complementary information to understand the dynamical processes associated with the creep of mountain permafrost (see Haeberli et al., 2006).
Due to the general arguments and some detailed comments, I think that the manuscript needs amendment, please see my remarks as follows. In addition, even though I am not a native English speaker, I think the text is basically well-prepared and requires minor proofreading only.
Thanks for these comments. We are also not native English speakers, and we speak different languages, but we enjoy disseminating our work in English and as well as in other languages.
According to the manuscript’s title and presentation, the main aim of your contribution is to introduce UAVs in rock glacier monitoring and to propose SfM-photogrammetric UAV surveys as favorable approach compared to established techniques. This assumption is a central issue because even though UAVs are not as long in use as other methods and devices, today, UAVs are already established in geosciences. Therefore, research based on UAVs should either focus on methodological questions, which is not case in your study, or otherwise should in detail discuss and explain geomorphological changes, which rather should be the aim of your manuscript. Therefore, I think it is necessary to revise the title and presentation of the manuscript. In addition, as there are other previous studies, please expand the relating literature discussing UAV-based surveys on rock glaciers. Also, the discussion on relating studies as in the present form needs revisions, please see my detailed comments concerning P12L362-376.
We partially agree with this statement. As indicated in the manuscript introduction, we propose UAV surveys as a complementary method to monitor rock glacier kinematics. For achieving this, we exploited the capabilities of the image correlation software CIAS to derived landform-wide kinematic fields from sequential UAV-SfM-derived orthomosaics. A fundamental step before explaining the geomorphological changes was to validate the results via independent ground information during five consecutive periods. The good agreement with data collected by repeated dGNSS demonstrated the robustness and reliability of the monitoring protocol (Figure 3), which similar studies have not demonstrated. Nevertheless, we decided to change the title of the revised manuscript to “Application of sequential unmanned aerial vehicle surveys to monitor the kinematics and geomorphological changes of a rapid rock glacier”. We also included more literature discussing UAV-based surveys on rock glaciers (Halla et al., 2021; Kaufmann et al., 2018), but it has to be noted that published studies having quantified rock glacier kinematics using UAVs remain very few to our knowledge.
In terms of validation of the UAV-based results, geodetic measurements are shown in order to independently assess the quality. However, the way of how the UAV survey-related design and the relating provided information are presented does not allow to completely comprehend the methodological benefits. Several details concerning the survey design, such as the planned and actual flight paths and coverages, the estimated theoretical precision compared to actual achieved precision, the details of processing including, e.g., the quality of tie points on the image plain, as well as a dimensionless theoretical assessment of the achieved quality are just some but relevant information that would help to promote UAV-based surveys, which is not the case in the current form of the manuscript. I think that such a methodological discussion and information is the prerequisite for a technology-featuring presentation of the manuscript. In contrast, the manuscript appears as a well designed and presented case study of a rock glacier’s kinematics but does not introduce new methodological approaches and therefore, should focus on the characteristics and specifics of the landform investigated. In this sense, it appears rather inappropriate to contend that UAVs are a new method for rock glacier monitoring as this is not the case.
The quality of 3-D point clouds and orthomosaics derived from UAV-SfM workflows depend on several physical, geometric and processing parameters (Benassi et al., 2017): surface texture and contrast, air refraction index, lighting conditions, sensor quality, global or rolling shutter, image sharpness, flight height and speed, grid pattern, camera angle, forward and side overlaps, the distribution and accuracy of GCPs, camera self-calibration, BBA, image matching algorithms, point cloud densification and outlier removal algorithms among other parameters. In this context, determining the quality of several SfM parameters is a complex mission, as the number of related variables is quite large (even though some parameters can be kept unchanged like grid patterns or image overlaps). Furthermore, a degree of spatial uncertainty accompanies the orthomosaics generation as well as the performance of the automatic image matching via correlation (Leprince et al., 2007; Redpath et al., 2016). Nevertheless, when deriving surface movement from sequential orthomosaics, we exploited the relative accuracy of the coregistration on stable sectors as the overall source of uncertainty. We expanded the section dealing with the coregistration assessment and added a new table. In doing this, we assume to account for the variability of these different parameters represented on either the orthomosaics or the point clouds (Cook and Dietze, 2019). We made this concept more evident through the manuscript. We also include more technical details about the UAV surveys on the new supplementary material.
Focusing the manuscript on the investigated landform would require adding many more data acquired on-site for near 20 years to completely reorganize it and shift the purpose to the landform dynamics. It was not our primary goal but to explore the benefits/complementarity of UAV-based survey to the ongoing kinematic monitoring. We prefer to keep the paper in its original objective but improve it accordingly (see our various responses below).
Concerning the survey design it would be necessary to first define what is required in terms of survey quality and the landform investigated in order to then conclude whether it was appropriate or not. Instead, the manuscript is characterized by a rather vague survey concept in order to subsequently conclude that the results are quite appropriate. In other words, at first it should be declared what survey quality is strived and estimated, which would then allow for assessing whether or whether not the results are appropriate.
We acknowledge that the UAV survey concept was also not well explained. The strived survey quality was not explicitly mentioned. As most of the landform is moving up to several meters between each survey and according to that, the relative stability of the surface material, which is exploited with any ground-based or remote technique is not fully insured (some tilting or sliding of the surface boulders can be expected in many places), a minimal accuracy of about 10 cm yr-1 or better in the resulting displacement rate would be adequate. Nevertheless, we maintained that the GNSS survey design follows the protocol design by Lambiel and Delaloye (2004), which has been established as a standard for rock glacier kinematics, at least for some national monitoring initiatives (see PERMOS reports). We depart from this framework with the addition of UAV surveys during the same TGS campaigns. The choice of the spatial and temporal characteristics of the UAV surveys was not trivial. The spatial resolution allowed to track rock glacier surface texture at 10 cm finely, and the biannual surveys are adapted to the high rock glacier speeds. We also indicated and discussed some factors that can degrade the quality of the UAV-derived velocities. The experimental design in this challenging terrain can provide a better assessment for destabilized rock glaciers, as this is the case for Tsarmine. We have made some amendments to the original manuscript to make this clearer.
The description of the processing needs revision. Without presenting and discussing photogrammetrically relevant parameters, such as exterior and interior orientation parameters, the quality of tie points and residuals of GCPs, photogrammetric studies are not comprehensible and meaningful. Therefore, the robust and detailed workflow that is stressed by the authors lacks these important components, which I think needs to be amended and the formulation revised. In addition, today, numerous articles are based on SfM-MVS photogrammetry. I suggest to expand and discuss the relevant literature in more detail, as there is no ample discussion and interrelationship with existing subject-specific-literature yet.
We agree that the data processing sections need revisions. We changed the emphasis to the evaluation of the UAV-SfM-derived products rather than the SfM processing. In doing so, we included a new section (3.4 Comparison with the TGS) where we better explained the validation protocol. We also expanded the section dealing with the coregistration assessment and added a new table. Regarding your last sentence, we are aware of most of those studies dealing with SfM-MVS photogrammetry, particularly in ESurf, but tried to keep the focus on the rock glacier applications.
Other methodological questions could deal with potential issues using the RTK-based survey configuration, e.g., are UAV-based surveys solely using direct georeferencing really capable of achieving the required quality? This could be worth discussing.
We thank the reviewer for this comment, but this methodological issue has been already discussed (see Benassi et al., 2017). The EBee RTK cannot achieve the so-called "direct georeferencing" since the camera attitude angles are not constrained by the IMU (only default values are available). That is why we performed a GNSS-support Aerial triangulation (GNSS-AT) with at least four GCPs. We included this explanation in the revised manuscript.
The presentation of the rock glacier’s velocities based on an area-based matching algorithm needs revisions. The validation of the velocity values should be expanded and the description revised, as the matching settings (grid size, correlation window size) are necessarily adjusted to the specific case and pair of images, e.g., the approx. 13 m large windows should be able to track 13 m long displacements (cf. P8L227). As a consequence, this results in high correlation values (R2 values presented in Section 4.1) and therefore, such a comparison of geodetically and NCC-derived velocities inherently cannot be completely independent. And this at least should be mentioned. Similarly, the presentation of the movement’s directional quality (Section 4.2) could be more comprehensible by explicitly mentioning that the directions were smoothed, as a directional filter was applied (Section 3.3).
We thank the reviewer for pointing on this valid concern, which we have been aware of during our CIAS analysis. The decision to use a particular combination of reference and search window sizes was pragmatic because the expected maximum displacement can be estimated beforehand from the visual inspection of sequential orthomosaics. In this regard, keeping the exact configuration of the search and window sizes provided only a theoretical maximum displacement limit of about 13 m (more than twice the maximum value observed) for each pair of consecutive orthomosaics. Repeating the CIAS processing using larger windows sizes increases both computing time and the number of bundlers (for a detailed explanation, see Kääb and Vollmer, 2000). As such, we do not agree with the argument of high r2 values (Figure 3) are related to the limit of 13 m, as we were able to quantify different maximum displacement values during different periods.
We removed the application of the directional filter, as we found it to be irrelevant for the few serious mismatches, which can be manually removed. The overall change caused by this filter was relatively small, and therefore, there is no smoothing effect in the results presented in Section 4.2.
The surface velocity fields should be revised, as thus far, categories of different velocities are presented and instead, vectors that show the exact displacement value should be presented, which also would allow for including and presenting the displacement vector-specific LoD value. As mentioned in Section 3.3 (P9L251), it would be a real benefit for the reader if these vector-specific LoDs would be shown in maps.
We thank the reviewer for this suggestion. However, we performed several tests and reached the conclusion that standardized velocities categories are better suited to highlight the rock glacier velocities changes during the study period, as this is also the case for displaying elevation changes. For instance, previous publications in ESurf also prefer to show such quantities in categories rather than individual vectors (see Clapuyt et al., 2017; Monnier and Kinnard, 2017; Piermattei et al., 2016) as well as other rock glacier kinematic studies (Micheletti et al., 2015; Scotti et al., 2017; Seppi et al., 2019). We also performed some tests to integrate the LoD values in Figure 4, but we did not reach satisfactory results. The mean LoD for each period is now indicated in Figure 4, and LoD statistics for each period are shown in Table 3.
Detailed comments:
P1L10-11: As the survey configuration details are not completely outlined, it is not tenable to contend that a rigorous procedure is introduced.
Agreed, we removed "rigorous" from the abstract.
P1L20-21: As the comparison with GNSS-based measurements is mentioned here and the description of the rock glacier dynamics, the main research contribution is the investigation of the specific rock glacier’s dynamics and behavior rather than methodological questions.
We included more arguments about the need for the improvement and validation of the monitoring protocol.
P2L36-48: What about rock glacier kinematic surveys beyond the European Alps?
Without being Eurocentric, we must acknowledge that the majority and best quality rock glacier kinematic data are found on the European Alps (Kellerer-Pirklbauer et al., 2018). There are intermittent examples of early rock glacier kinematics surveys outside the European alps, such as the Pedregoso rock glacier in the South American Andes (Marangunic, 1976) or the Galena Creek rock glacier in North America (Potter, 1972). Promisingly, recent remote sensing research has become critical to reducing this gap between Europe and other rock glacier regions (Blöthe et al., 2020; Kääb et al., 2021; Strozzi et al., 2020). We added some information for extra-European rock glaciers.
P2L52-53: Style – “[…], evidence of […] identified as evident signs […]”.
Agreed, we removed “evident” from the sentence.
P2L61: Style – “The quantification […] has been measured […]”.
Changed: “Rock glacier kinematics have been traditionally….”
P3L72: “[…] Unmanned Aerial Vehicles (UAV) systems […]”. Plural ending not correct, please check throughout the manuscript.
Thanks. We have corrected this issue.
P3L79-80: Expand the list of published studies dealing with UAV-based rock glacier surveys. As there are already studies demonstrating the benefits and challenges of UAV-based rock glacier surveys and as generally, the landform rock glacier does not entail a specific methodological treatment compared to other landforms and as SfM photogrammetric UAV-based surveys are today already established, this cannot be the research question.
As mentioned before, we have included the work by Kaufmann et al. (2018). However, we did not find other studies dealing exclusively with UAV-based rock glacier kinematics. Furthermore, we argued that some rock glaciers are currently destabilized (like Tsarmine), and they can behave in a unique fashion that does not follow other types of landforms (they have a different dynamical response than glaciers, solifluction lobes, debris-cover glaciers or landslides). Therefore, we emphasised the challenges raised by the unique response of destabilized rock glaciers and the potential benefits and limitations of a monitoring strategy based solely on sequential and systematic UAV surveys.
P3L81: Yes, but both a protocol and relevant details of the UAV-related configuration and processing are not discussed in this manuscript and therefore, this should not be mentioned and understood as the research question.
We cannot totally agree with this statement. The study area is characterized by the availability of high-quality ground truth information like permanent GNSS stations and biannual GNSS surveys, together with complementary close-range remote sensing techniques such as terrestrial laser scanner (TLS) surveys and webcam devices. Our results are discussed against similar research (Dall’Asta et al., 2017; Fey and Krainer, 2020), focusing on quantifying rock glacier displacements and their related uncertainty, together with the validation strategies. Additionally, the discussion also provides some perspectives when our results are compared with concurrent InSAR investigations on the same rock glacier (Strozzi et al., 2020). With the details added to the manuscript (see other responses above) and the improved discussion, we are convinced that the stated research question is justified. To make those arguments more evident, we have changed the sentence: “However, as UAV systems are continuously changing and improving, there is still scope for the assessment of monitoring protocols using different UAV configurations in high altitude and challenging terrain.”
P3L82: It is meant “[…] high altitude please clarify.
Done.
P3L84-85: General statement that I do not support. One could also argue, as the surface velocities are in a hardly observable cm-range, a thorough validation is necessary. Therefore, no, different rock glacier velocities are not an argument.
We modified this sentence. “In the context of rapid rock glacier acceleration and destabilization, new and customizable monitoring techniques are necessary.”
P3L86: So far it was not mentioned in the manuscript that the quality of kinematic data is an issue, so, maybe it should be clarified at first that kinematic measurements are of diverse quality, which is why a thorough validation is necessary.
Thanks, we clarified this: “Likewise, as the quality of kinematic data obtained from different remote sensing techniques can be variable, a systematic ground validation through consecutive periods is required to improve the monitoring techniques and shed light on rock glaciers' kinematic behaviour in great spatial detail.”
P3L92-93: This is the formulation of the study’s aims, which are a better understanding of the rock glacier behavior and dynamics. Therefore, your study contributes to rock glacier monitoring rather than the technique or methodological questions and therefore, the presentation should not focus on UAVs for the simple reason that these are maybe not that commonly used on rock glaciers yet, which is, if indeed, possibly coherent with the number of rock glacier studies.
Thank you for these comments. We have improved our arguments, and we indicated that a particular monitoring technique and its validation are still needed for rock glaciers, especially during acceleration and destabilization phases.
P4L111: “[…] 2016. the []”.
We do not see this error in the original manuscript.
P4L114: Please clarify, that this specific landform “Tsarmine” was meant.
Done.
P5L427: As it is a specific number of points (58), it cannot be “around”.
Corrected.
P5L132: I would say that 2 cm are also in the cm range, please clarify.
We changed to “1–2 cm range”.
P5L141: Table 2 is mentioned before Table 1, modify.
Revised.
P5L152: Add the focal length’s unit.
Added.
P5L154: Do you really mean “accuracy” of the RTK-based camera positions, as I cannot see the relationship to other, independent measurements, please clarify.
We changed to “precision”.
P5L155: Explicitly mention that the low accuracy is too low in terms of the study-relating aims, because low accuracy per se could still suffice.
Clarified: “The UAV camera orientation values (Roll, Pitch, and Yaw angles) recorded by the Inertial Measurement Unit (IMU) device have low accuracy, hampering a reliable block orientation by the direct sensor orientation (DSO) method.”
P5L155-156: Please expand with a few words the tests mentioned in order to make the statement more comprehensible. In addition, with “mainly” you mean “mostly”?
We changed to: “However, independent tests using different combinations of GCPs have found that position accuracies are mostly too optimistic, suggesting that some sort of ground or check control should be included during the UAV block orientation (Benassi et al., 2017).”
P6L160-161: As you describe the planned image overlap of your survey, a citation does not make sense; delete the reference or clarify.
Agreed.
P7L198: It should be “[…] GCPs next to the […]” or similar.
Corrected.
P7L203: In order to discuss the quality of the bundle adjustment it is necessary to present and discuss the data of exterior and interior orientation parameters and the quality of the tie points.
Thanks for pointing out this. As we mentioned before, we are not thoroughly discussing the quality of the SfM procedure but rather the quality of the sequential datasets derived from it. We included other results in Table 2 (Mean Reprojection Error). We argued that the checkpoints are the most suitable way to independently gauge the quality of the bundle adjustment (see James and Robson, 2014) rather than the interior or exterior orientation parameters.
P7L210: Check plural ending and indefinite article. Also, mention for clarity that the orthomosaics were resampled to 0.01 m, as the GSDs differed (cf. Table 1).
We corrected this and changed the manuscript accordingly.
P7L213: Mention the subsections number instead of “previous step”, as this would be
clearer.
Changed.
P7L21-216: As you describe the principle, it does not make sense to relate to rock glaciers; the principle is valid for every surface surveyed.
We changed to “moving surface”.
P7L217: With “extensive” it is meant “larger”, which is more applicable, I think.
We changed to “larger”.
P8L237: Please check with the journal requirements whether or not the citation (“their Fig 2”) is appropriate.
We are not aware of such specific requirements. Nonetheless, we will leave it to the potential typesetting and copy-editing services provided by Copernicus Publications.
P8L240: As it is a specific number of points (69), it cannot be “around”. Also, show the 69 subareas in the map.
We changed to “between 60 and 69 stable rock surfaces” and included a new table with the results of the coregistration assessment. Also, there are not 69 subareas, but there are 69 points circumscribed to the stable sectors in Fig1C.
P9L255: As it is a specific number of points (35), it cannot be “ca.”. Moreover, I cannot find the relating results of the mentioned comparison. In addition, show the spatial distribution of these 35 points in a map, as this is not the case yet.
We changed to “35 TGS points”. The results of this comparison and the spatial distribution of these points are included in a new supplementary material (table and figure) related to this manuscript.
P9L272: For understanding: these are the same 35 points mentioned in Section 3.4 (here used as independent z check points)?
Yes, they are the same. We made this more evident.
P9L274: Is the term ‘significant’ in the sense of statistically significant appropriate here?
We removed the term “significant.”
P11L335-337: Agree, but why are then the relating details of acquisition, processing and
analysis not presented yet?
The requested details of acquisition and processing are presented in sections 2.3 and 3.2, and the corresponding analysis is delivered through the “Results" section.
P11L337-339: Disagree, the inability of potentially new UAV-users cannot be anticipated, which is also attenuated by the high degree of automatization and usability of modern UAVs. Also, the depreciation of commercial UAV flight providers is not comprehensible as the necessary information needs to be negotiated and should be part of the contract, which is why commercial UAV survey providers of course could deliver the required data and metadata.
In the framework of remote sensing approaches, our sentence makes a discussion about platform operation between classical aerial surveys or satellite programs (notably companies) and new UAV surveys (primarily researchers). In this regard, we stated the benefit of low-cost surveying tools, which allows the scientists to be in charge of the data acquisition (Anderson et al., 2019; Eltner et al., 2016), potentially closing the gap between commercial aerial photography and small research initiatives.
P11L342: This discussion could be more controversial as 30 minutes could be the net flight time, but usually the setup and pre-flight checks also need time as well as accompanying geodetic measurements and moreover, UAV flights are more weather-dependent (so probably it is necessary to wait for optimum conditions), which is why usually a UAV survey takes remarkably more time than 30 minutes.
To our experience, the typical UAV setup and pre-flight checks take less than 5 minutes. Since the permanent GCPs are fixed and already provided, this step is not needed for subsequent UAV surveys. In any case, we now indicated that the actual data capture from the first to the last images usually takes no more than 30 minutes (roughly the time between takeoff and landing) for the size of the Tsarmine rock glacier, which is considerably less time than the regular GNSS data capture (which is 2 hours from the first to the last measurement). Please, check Table 1, where the individual UAV survey times are indicated. The flight plan mission is now included in the supplementary material.
P12L344: The different LoD values resulting from NCC and GNSS are not completely shown yet, only partially in Table 3.
The LoD values from GNSS are now included in Table 3.
P12L352: Elaborate, what are the “[…] suitable environmental conditions […]”? In addition, what is the point of “ […] that means about four months a year […]”? Usually, also geodetic surveys (except permanent measurements of a single point) are conducted in the snow-free season, so this is not specific for UAV surveys.
We changed to “suitable weather conditions”. We changed to “For our study area, the snow-free period usually spans for four months a year”.
We have to disagree with the second sentence, as geodetic surveys can be conducted during the snow season, particularly exploiting prominent boulders at the rock glacier surface (see Perruchoud and Delaloye, 2007).
P12L350-356: This is a rather general discussion and the relating pros and cons were not investigated in the study
Thanks for point out this. We included more precise details about the pros and cons. We made clear that the investigated area size, weather conditions and specific UAV regulations are all potential limiting factors for our study area.
P12L360-361: As it is obviously necessary to make SfM photogrammetric studies more comprehensible using protocols and standards, consequently, why don’t you present and discuss the complete survey details including planning, theoretical and actual quality estimates, processing settings etc.?
From previous studies, we highlighted two main protocols issues that we have accounted for in the present contribution. The assessment of the stable areas (uncertainty estimation) and surface velocity validation by independent GNSS data were explained for five consecutive periods. We have indicated the most relevant survey and processing details, particularly in sections 2 and 3. Additional details are included on the new supplementary material (UAV surveys settings, DEM assessment and Helmert results).
P12L362-376: This is a repetition of how (only) some others (i.e. not all relating studies) performed UAV-based studies on rock glaciers and as the text passage stresses you performed something what others did not, the character of this text passage is rather contemptuous. Therefore, I suggest to revise or exclude this text passage.
We acknowledge the early work of Dall’Asta et al. (2017) to establish a UAV monitoring protocol on rock glaciers. Their work inspired us to test such approaches on a rapid rock glacier with systematic kinematic measurements since 2004. However, we also have to highlight the main differences with previous researches to show the advances in data interpretation and validation, which are part of the current contribution. However, we recognize that the tone is a bit contemptuous, and we made the changes accordingly.
P12L373: Disagree, it cannot be concluded that companies are not willing to deliver what is necessary, it is rather necessary to adequately negotiate a contract by those interested in processing the data.
We have not concluded such a statement as the original article reads: “Since the UAV flight and the data processing were performed by an external company more detailed information are not available”(Fey and Krainer, 2020, p.4). From this evidence, we stated that Fey and Krainer (2020) did not provide relevant error metrics such as RMSE, mean error or standard deviation error, which could have helped to evaluate the overall quality of the UAV-SfM derived products presented in their article.
P12L374: The term “intrinsic” is distracting, as interior orientation parameters could be meant with this but which are not presented in Table 2 or elsewhere in the manuscript.
We changed to “relevant quality data”. Table 2 expanded with more relevant results.
P12L375: To perform all working steps by oneself is not a guarantee for high-quality results. I fail to see any argument and therefore suggest to revise or exclude this paragraph.
Agreed, we removed this sentence.
P13L395: Add “[…] Tsarmine rock glacier […]” for clarity.
Added.
P14L411-412: Not the kinematic points but their velocities are shown.
Changed “kinematic points” to “velocities values derived from…”
P14L432: Which proposed uncertainty analysis you are relating to here? I cannot find relating data.
We removed “based on the proposed uncertainty analysis.”
P14L434: Disagree, there are no details presented concerning the customized data
acquisition and robustness of processing.
We included more relevant details about UAV data acquisition and processing results. We changed to “The customised UAV data acquisition, and the subsequent data processing workflow delivered spatially distributed kinematics for this destabilized rock glacier during the 2016–2019 period.”
P14L434-440: As UAV-based SfM-photogrammetric studies are already established and as the landform of rock glaciers does not entail any specific methodological adaptations, I fail to understand what is concluded in this text passage and therefore suggest revision.
We changed our argument, and we explained why a destabilized rock glacier (i.e. Tsarmine) entails a specific UAV monitoring strategy.
P15L449: Disagree, the current form of the manuscript does not show all details relevant in SfM-photogrammetric studies.
We removed “SfM techniques”.
P18L564: The list of references needs revision, e.g., the publication in P18L564, which is not mentioned in the text yet.
Thanks for spotting! We added this reference to the manuscript.
Figure 4: In the legend: shouldn’t the category be “1-LoD” instead of “LoD-1”? As already mentioned, I think it would be favorable to show real vectors instead of categories, which would then also allow to show the displacement-specific LoD values.
Please, see our previous response to the same commentary.
Figure 6: The hillshade could be more low-contrast or so, which would then probably better allow to perceive the lines.
Thanks for this constructive suggestion. We modified the hillshade accordingly.
Figure 7: The categories of elevation differences are partially overlapping and therefore, seem to be wrong, e.g., categories “-4.50 to -3.70” m and “-3.80 to -3.00” m etc.
Thanks for spotting! We modified the categories accordingly.
Table 1: This table could be expanded with values of theoretically achievable precision estimates, which are survey configuration-specific.
We have not found such a type of table together with the "theoretically achievable precision estimates" as an example on relevant publications. Therefore, as previous UAV related publications on ESurf (Clapuyt et al., 2017; Cook and Dietze, 2019; Van Woerkom et al., 2019; Zhang et al., 2019), we only indicated the most relevant UAV surveys parameters.
Table 2: Expand the table by showing both, the RMSEs of GCPs and CPs on the modelled surface as well as the image plane.
We expanded the table with the GCPs and CPs mean and standard deviation errors.
Table 3: Mention the relating confidence interval.
Agreed, we included the confidence limit.
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Citation: https://doi.org/10.5194/esurf-2021-8-AC1
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AC1: 'Reply on RC1', Sebastián Vivero, 12 May 2021
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RC2: 'Comment on esurf-2021-8', Anonymous Referee #2, 06 Apr 2021
Review of the manuscript “Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier” from Vivero et al. Submitted to The Cryosphere earth surface Dynamics.
This paper attempt to show the importance of using sequential UAV-surveys and Structure for Motion photogrammetry workflows for monitoring and quantifying changes in rock glaciers. This study is based on the analysis and comparison of very high-resolution photogrammetric products (i.e. DEMs and orthomosaics) acquired between 2016-2019.
The manuscript has as the main goal to propose the benefits of using UAV surveys through a “rigorous” methodological approach to estimate surface velocities and volume changes over the Tsarmine rock glacier.
Finally, the authors analyze the UAV monitoring strategies as well as the kinematical behavior and surface changes of this rock glacier.
Due to the general arguments and some detailed comments unfortunately I think that there are some major drawbacks in this manuscript that from my point of view could question the acceptance of the manuscript. In addition, even though I am not native English speaker, I think the text requires some corrections. I strongly recommend having the manuscript reviewed by a English native speaker.
General and specific comments are described as follows:
General comments:
SfM methodology
- First, the main contribution of the study is focused on the establishment of a “rigorous methodology” for monitoring rock glaciers using UAV. However, this aspect is crucial because in this study I could not find significant differences (in the methodology) concerning other studies.
- No discussion is presented about the “implementation of this rigorous protocol” methodology. At this point, I wonder, what is the main difference between the traditional UAV surveys and the new one you propose? More details are needed about specific steps on the protocol, e.g. orientation parameters, the quality of the point cloud, and the differences between GCPs and external data.
- Second, you mentioned in the text the implementation of the “co-registration” stage as the main difference between other studies. However, I think there is a misinterpretation of the term “co-registration”. Initially, you speak of multi-temporal co-registration (Figure 2) to the fact of always using the same 4 control points for the aerotriangulation stage. However, co-registration is more related to comparing one product with another, (i.e. master DEM to another, co-registration on SAR images that follows the same principle). The fact that you are always using the 4 points for the aerotriangulation stage is part of the "rigorous protocol", nevertheless, this is not necessarily a co-registration stage. In your case, the co-registration step should be implemented after ortho-images and DEMs generation and with independent references (points, DEMs, etc) that were not included in photogrammetric analysis.
- Then you talk about that the co-registration based on the Helmert methodology you do not find rotations or changes of scale. This issue is obvious since you always used the same 4 points for aerotriangulation. Then, you mention shifts between orthomosaics (computed again using Helmert methodology) but these values are not reported anywhere. Is this important? Or not?
- Later, only the ortho-images were "co-registered" and not the DEMs. In the case of x-y shifts in the ortho-images were important, this also implies strong variations in the elevation changes calculated using the non-coregistered DEMs.
- Finally, you mention that you use small areas to perform this co-registration, however, these areas represent a very small portion of the overall DEMs (which is not presented indeed). The fact of selecting small areas can lead to misinterpretations in the uncertainties.
Surface velocities
- Another methodological question arises on the presentation of rock glacier surface velocities. More details are needed to discuss the validation of the feature tracking products. Also, the current manuscript does not allow the correct interpretation about technical details like grid size, correlation windows size which is fundamental. For example, given the current displacements of Tsarmine rock glacier in the frontal part, adaptable window correlation size are maybe needed. Independent comparisons between products (correlation results) should be mentioned and results should be provided as supplementary material.
- Given the recent importance of these in geosciences, I consider that it is necessary to expand a little more literature on the methodology used in other studies and to be able to propose a new one.
- As showed in Table 1, your latest survey was made early in the morning. This aspect is not even mentioned, we don’t have any idea if the presence of shadows in the morning or light conditions could harm the feature tracking process.
- The fact that you are using very high-resolution data leads to fine changes in image texture and quality. There is no discussion about the influence of using a very high-resolution image to compute surface velocities fields.
Thickness changes
- This study leads with very high-resolution data, therefore the validation of these must be rigorous and independent. Although the manuscript presents a validation step (independent using GPS data), robust statistical analysis is necessary to support these results.
- Additionally, as you are computing differences between many DEMs, uncertainties between those should be presented at least as supplementary material.
Specific comments:
P1L10-11: as details about UAV surveys were not detailed, the “rigorous procedure” is ambiguous and it is no possible to understand why it is rigorous.
P1L19: On the phrase “we almost archived the same accuracy as the GNSS-derived velocities”, numerical comparations should be provided for this comparison.
P1L26-27; The phrase “Rock glacier analogues […] (Cliford et al.,2013)” does not contribute to the discussion of the document and is out of context.
P2L33: the word “top” is too ambiguous. I suggest changing this by “surface”.
P2L37-39: The phrase “The most extending […] Schneider, 2001)” should be revised because it is no clear.
P2L44: Annual surveys derived from what?
P2L62-63: on the sentence “[…] more recently using differential GPS (Berthling et al., 1998”) the reference is too old.
P3L64-68: In this paragraph, you mentioned remote sensing techniques to measure rock glacier displacements and all the references are at the end. However, we do not know which corresponds to which one. I suggest changing this paragraph putting the correct references after each technique.
P3L70: There is no only Kaab that has been working on photogrammetry and rock glacier. For example, you forgot Kaufman publications and one of your Swiss colleagues Michelleti et al 2015, Australian and French colleagues.
P3L80-81: Ok, we are gree that UAVs are changing and improving, but it will affect the way to make photogrammetry? I think this sentence is too ambiguous.
P3L85: What is necessary?
P3L87: the benefits of UAV have been already proved for rock glaciers? Why are you interested in proving these again?
P4L119: Mounty peak instead that “peak monthly”.
P5L127: 58 points is a specific number, it cannot be “around”.
P5128: […] six fixed points […]. In this sentence, you write six? However, on the L127 you mentioned “58 points…” with a number. Please harmonize.
P5L141: Table 2 is mentioned before Table 1.
P5L151: Add focal length units.
P5L152: Add focal length units.
P5L155- L152: The sentence “However […]” is too ambiguous. Poor information is provided about the independent test.
P6L164-165: The sentence “Moreover […] ground […] is repetitive. You already mentioned this on L146. Please check the redundancy.
P7L208: are you sure that the way to present “average density of points” is the correct way? Please verify this.
P8L223: I am confused. On the L210 you said that you generate ortho-mosaics at 0.1 m resolution. But here on the L223, you calculate surface displacements using orthomosaics at “one-tenth of the original pixel size (i.e. 0.01m)” which is not coherent. Please verify.
P8L229: Dis you check the influence of shadows on very high-resolution ortho-mosaics? This aspect is not even mentioned.
P8l234-237: Disagree. Please see my general comment. No detailed information is presented about this issue (i.e. differences in stable areas, x-y shifts, etc.).
P8L240: Again, 69 is a specific number, it cannot be “around”. Also, these 69 “rock surfaces” are not displayed anywhere.
P8L241: x-y-shift translation vectors are not mentioned anywhere. Please provide a detailed description of the specific values obtained from the Helmert similarity.
P9L255: What means ca? Please check this. Moreover, no information on this comparison was presented. Please provide Z differences of these 35 points.
P9L261-262: Uncertainties of DEMs, as well as uncertainties propagated, thought DoD calculation should be shown.
P9L265: how much is this area examination? Please presents values on square meters.
P9L272: Did you measure the displacement of these 35 points? Additionally, these are the same used in section 3.4 (DEM assessment)?
P11L335-339: Disagree. I think this paragraph is too ambiguous because it depends on your goals. Recent developments of satellite photogrammetry (i.e. world-view 2 and 3, Pleiades, etc) showed the high quality of their products even on rock glaciers.
P11L242: Disagree. Again, too ambiguous. The UAV survey can early take more than 30 minutes because it is weather-dependent. In this case. In case the conditions are not optimal, the acquisition time can easily exceed 30 minutes. I suggest changing this part.
P12L344: Disagree. The limits of detection depend on the size of the window used for correlation and it should be tested on fixed areas. Some information about these values is partially reported in Table 3, however, more detailed information needs to be provided.
P12L350-356: This paragraph does not contribute anything to the study. It is maybe a general discussion about “optimal conditions” but this topic is already known.
P12L258-269: Disagree. This paragraph is redundant and a repetition of what the others already do. However, no technical comparisons are given about your protocol against the others (i.e. planning, processing, etc). I suggest revising or excluding this paragraph.
P12L367-369: Ok, you are using stable terrain to validate your products but detailed information about these areas is not presented anywhere. Also, these areas are very small compared to the total extension of your DEMs. Please see my remark on P8l234-237.
P12L375. The fact that you perform all working steps does not guarantee high-quality results. It should be proved by comparing independent methods. Additionally, a detailed report is needed to support this argument. I suggest revising or exclude this paragraph.
P13L404: "[…] net frontal retreats (Fig. 6)" reference is missing.
P14L411: Surface velocities are showed instead of kinematic points. Please change this and also on Figure 9.
P14L428-430. Agree, but what is the contribution of this paragraph to your work? This paragraph takes place at the introduction instead than in the discussion section. Please revise this or exclude this paragraph.
P14L430-432: I could not find an uncertainty analysis. You are relating this to GNSS comparison? The fact that you are using very high-resolution products needs a robust statistical analysis concerning the uncertainties between photogrammetric products notable on stable areas (for DEMs) and surface velocities.
P14L434: What are the differences between your UAV protocol against others? More details are needed to be related to “customizable data acquisition”.
P14L436-437: Agree. With your data, you could explain more extensively this process regarding even into sub-periods.
P15L449-450: Even this works shows a detailed description of UAV surveys on rock glaciers, I difficult to me what’s is the main difference against a normal UAV survey. The current status of the manuscript does not show in detail the relevant differences of SfM photogrammetric studies.
P18L564: the list of references needs revision. The reference Fugazza […] is not cited in the text.
Figures and tables
Figure 1. Panel b: add a north arrow to make clear the image.
Figure 2 Panel b. Disagree with multitemporal co-registration. Please see my remark in general comments.
Figure 4: I think that the community has much more interest to know which are the values of these limits of detection (LoD) instead than only the text. Please show specific values of LoD.
Figure 5. This figure is nice. However, there is not always clear to relate a 3D view to a plane view as shown in Figure 4. I suggest changing the 3D image by a more explicit figure that shows the localization of the longitudinal profile.
Figure 6. It is difficult to see front evolutions because the lines overlay. You said the mean “front line displacements” did you calculate this displacement over the entire line? If yes, precise which method did you use?
Figure 7. These results could be showed better. Is too difficult to interpret this figure because even if the intervals are regular, there is not obvious to see ±0.8. The intervals should be divided by entire numbers (-1.0 - -2.0 as an example) instead of 0.8. Also, on the color scale, you say that you found values greater (less) than +6.8m (-6.8m), I suggest that you present the min and max values as well as the north arrow. Finally, please use a color scale adapted for colorblind people.
Figure 8. On panel a), please indicate the photo was acquired.
Table 1. Please provide the “GSD” acronym.
Table 1. if it is a rigorous protocol, all flights were made between 11h-13h. Why was your last flight in the morning? I found no justification in the text. Please specify this. Did this early flight have any consequences on the velocity calculation? (important presence of shadows).
Table 2. Change “errors” by uncertainties.
Table 2. Why are you expressing uncertainties in pixels? It should be better expressed in meters.
Table 3. Additional statistical analysis is required.
I hope you will find my comments appropriate,
Best regards
Citation: https://doi.org/10.5194/esurf-2021-8-RC2 -
AC2: 'Reply on RC2', Sebastián Vivero, 12 May 2021
We want to thank the anonymous referee for this technical review and comments that will help to improve some aspects of the manuscript. We agree with most of the comments and suggestions made by the anonymous referee. Nevertheless, very similar observations were also raised by the first reviewer, and therefore, already explained in the first author’s response (AR1). Where this is the case, we indicated that similar responses are also in the first author’s response (AR1).
The referee comments are in italic font, and our responses and revisions are in normal font.
Review of the manuscript “Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier” from Vivero et al. Submitted to The Cryosphere earth surface Dynamics.
This paper attempt to show the importance of using sequential UAV-surveys and Structure for Motion photogrammetry workflows for monitoring and quantifying changes in rock glaciers. This study is based on the analysis and comparison of very high-resolution photogrammetric products (i.e. DEMs and orthomosaics) acquired between 2016-2019.
The manuscript has as the main goal to propose the benefits of using UAV surveys through a “rigorous” methodological approach to estimate surface velocities and volume changes over the Tsarmine rock glacier.
Finally, the authors analyse the UAV monitoring strategies as well as the kinematical behavior and surface changes of this rock glacier.
Due to the general arguments and some detailed comments unfortunately I think that there are some major drawbacks in this manuscript that from my point of view could question the acceptance of the manuscript. In addition, even though I am not native English speaker, I think the text requires some corrections. I strongly recommend having the manuscript reviewed by a English native speaker.
Thank you for the overall summary of our work. We will review the English of this manuscript accordingly.
General and specific comments are described as follows:
General comments:
SfM methodology
First, the main contribution of the study is focused on the establishment of a “rigorous methodology” for monitoring rock glaciers using UAV. However, this aspect is crucial because in this study I could not find significant differences (in the methodology) concerning other studies.
We propose UAV surveys as a complementary method to monitor rock glacier kinematics. For achieving this, we exploited the capabilities of the image correlation software CIAS to derived landform-wide kinematic fields from sequential UAV-SfM-derived orthomosaics. A fundamental step before explaining the geomorphological changes was to validate the results via independent ground information during five consecutive periods. The good agreement with data collected by repeated dGNSS demonstrated the robustness and reliability of the monitoring protocol (Figure 3), which similar studies have not demonstrated. Please, see also our similar response to reviewer 1 (AR1).
No discussion is presented about the “implementation of this rigorous protocol” methodology. At this point, I wonder, what is the main difference between the traditional UAV surveys and the new one you propose? More details are needed about specific steps on the protocol, e.g. orientation parameters, the quality of the point cloud, and the differences between GCPs and external data.
We acknowledge that the UAV monitoring concept and validation was not well presented. We changed the emphasis to the evaluation of the UAV-SfM-derived products rather than the SfM processing. In doing so, we included a new section (3.4 Comparison with the TGS) where we better explained the validation protocol. We also expanded the section dealing with the coregistration assessment and added a new table. Please, see also our similar response to reviewer 1 (AR1).
Second, you mentioned in the text the implementation of the “co-registration” stage as the main difference between other studies. However, I think there is a misinterpretation of the term “co-registration”. Initially, you speak of multi-temporal co- registration (Figure 2) to the fact of always using the same 4 control points for the aerotriangulation stage. However, co-registration is more related to comparing one product with another, (i.e. master DEM to another, co-registration on SAR images that follows the same principle). The fact that you are always using the 4 points for the aerotriangulation stage is part of the "rigorous protocol", nevertheless, this is not necessarily a co-registration stage. In your case, the co-registration step should be implemented after ortho-images and DEMs generation and with independent references (points, DEMs, etc) that were not included in photogrammetric analysis.
We agreed that the term co-registration was incorrectly assigned to the four multitemporal GCP. We have changed accordingly and corrected the caption in Figure 2.
The GCPs and CPs are used to determine the absolute accuracy of the UAV-SfM-derived products. However, the relative accuracy was evaluated for each orthomosaic pair using a Helmert similarity transform based on 69 points sampled on stable terrain features without significant vegetation. In doing this, we assessed both the coregistration and image matching accuracies. See our similar response to review 1 (AR1).
Then you talk about that the co-registration based on the Helmert methodology you do not find rotations or changes of scale. This issue is obvious since you always used the same 4 points for aerotriangulation. Then, you mention shifts between orthomosaics (computed again using Helmert methodology) but these values are not reported anywhere. Is this important? Or not?
The mention of the lack of rotation or scale differences among the sequential orthomosaics may sound trivial, but we include it as initial quality control. Additional details are included on the new Table and supplementary material.
Later, only the ortho-images were "co-registered" and not the DEMs. In the case of x-y shifts in the ortho-images were important, this also implies strong variations in the elevation changes calculated using the non-coregistered DEMs.
We thank the reviewer for this comment, but we did not observe such “strong variations in the elevation changes” caused by the subpixel x-y-shifts. Therefore, we evaluated the uncertainty of each DEM according to their absolute accuracy (35 points), and we propagated the errors during the DoD analysis following Wheaton et al. (2010). We included these results in the supplementary material.
Finally, you mention that you use small areas to perform this co-registration, however, these areas represent a very small portion of the overall DEMs (which is not presented indeed). The fact of selecting small areas can lead to misinterpretations in the uncertainties.
The co-registration was performed on 69 points distributed on well-evaluated areas (see Kummert and Delaloye, 2018) and without significant vegetation (as the NCC misses the coherence on this kind of surfaces). This selection was not trivial, as we have detected some landslide activity in the vicinity (see Barboux et al., 2014). Still, the “small areas” represent about 1/4 of the study area (Tsarmine rock glacier) and are distributed on five disconnected regions. We are not aware of this level of assessment of the stable regions at this high resolution by similar studies.
Surface velocities
Another methodological question arises on the presentation of rock glacier surface velocities. More details are needed to discuss the validation of the feature tracking products. Also, the current manuscript does not allow the correct interpretation about technical details like grid size, correlation windows size which is fundamental. For example, given the current displacements of Tsarmine rock glacier in the frontal part, adaptable window correlation size are maybe needed. Independent comparisons between products (correlation results) should be mentioned and results should be provided as supplementary material.
The decision to use a particular combination of reference and search window sizes was pragmatic because the expected maximum displacement can be estimated beforehand from the visual inspection of sequential orthomosaics. In this regard, keeping the exact configuration of the search and window sizes provided only a theoretical maximum displacement limit of about 13 m (more than twice the maximum value observed) for each pair of consecutive orthomosaics.
We included a new section (3.4 Comparison with the TGS) to explain the validation protocol better. We also expanded the section dealing with the coregistration assessment and added a new table. Please, see our similar response to reviewer 1 (AR1).
Given the recent importance of these in geosciences, I consider that it is necessary to expand a little more literature on the methodology used in other studies and to be able to propose a new one.
We expanded the references.
As showed in Table 1, your latest survey was made early in the morning. This aspect is not even mentioned, we don’t have any idea if the presence of shadows in the morning or light conditions could harm the feature tracking process.
We thank the reviewer for pointing on this valid concern; however, It is well known that the normalised cross-correlation (NCC) can account for the differences in contrast and brightness (see Heid and Kääb, 2012). We included this explanation.
The fact that you are using very high-resolution data leads to fine changes in image texture and quality. There is no discussion about the influence of using a very high- resolution image to compute surface velocities fields.
Agreed, we have put more emphasis on the very high-resolution datasets.
Thickness changes
This study leads with very high-resolution data, therefore the validation of these must be rigorous and independent. Although the manuscript presents a validation step (independent using GPS data), robust statistical analysis is necessary to support these results.
Additional details are included in the new supplementary material (DEM assessment).
Additionally, as you are computing differences between many DEMs, uncertainties between those should be presented at least as supplementary material.
Agreed, we included additional details in the new supplementary material (DEM assessment).
Specific comments:
P1L10-11: as details about UAV surveys were not detailed, the “rigorous procedure” is ambiguous and it is no possible to understand why it is rigorous.
Agreed, we removed “rigorous” from the abstract.
P1L19: On the phrase “we almost archived the same accuracy as the GNSS-derived velocities”, numerical comparations should be provided for this comparison.
Changed to: “We achieved uncertainties down to 0.08 m using the adequate UAV survey acquisition, processing and validation steps.”
P1L26-27; The phrase “Rock glacier analogues […] (Cliford et al.,2013)” does not contribute to the discussion of the document and is out of context.
Agreed, we remove this sentence from our manuscript.
P2L33: the word “top” is too ambiguous. I suggest changing this by “surface”.
Changed to “surface”.
P2L37-39: The phrase “The most extending […] Schneider, 2001)” should be revised
because it is no clear.
Changed to “One of the first monitoring efforts goes back to the summer of 1938 at the outer Hochebenkar in the Ötztal Alps of Western Austria”.
P2L44: Annual surveys derived from what?
Annual surveys derived “from in-situ measurements”.
P2L62-63: on the sentence “[…] more recently using differential GPS (Berthling et al., 1998”) the reference is too old.
We removed “and more recently using”.
P3L64-68: In this paragraph, you mentioned remote sensing techniques to measure rock glacier displacements and all the references are at the end. However, we do not know which corresponds to which one. I suggest changing this paragraph putting the correct references after each technique.
Changed.
P3L70: There is no only Kaab that has been working on photogrammetry and rock glacier. For example, you forgot Kaufman publications and one of your Swiss colleagues Michelleti et al 2015, Australian and French colleagues.
Andreas Kääb did a lot of work in this field, and in our view, he produced some of the most inspiring articles dealing with photogrammetry applications on rock glaciers. Furthermore, we are employing the CIAS software which he developed. We expanded, however, the list of authors. Also, we are not aware of the“Australian colleagues” working on photogrammetry and rock glacier.
P3L80-81: Ok, we are gree that UAVs are changing and improving, but it will affect the way to make photogrammetry? I think this sentence is too ambiguous.
We have changed the sentence: “how rock glacier kinematics and geomorphic changes are evaluated still presents a challenge, and there is still scope for the assessment of monitoring protocols using different UAV configurations high altitude and challenging terrain”.
P3L85: What is necessary?
We modified this sentence to: “In the context of rapid rock glacier acceleration, a robust validation of the increasing velocities from particular remote sensing techniques is necessary”.
P3L87: the benefits of UAV have been already proved for rock glaciers? Why are you
interested in proving these again?
Previous research has partly described these benefits, but as we had argued, a destabilised rock glacier entails a specific UAV monitoring strategy and particular analyses. Topics such as substantial velocity variations, scarp development and frontal erosion processes have been described and discussed in the present manuscript. See our similar responses to reviewer 1 (AR1).
P4L119: Mounty peak instead that “peak monthly”.
Changed.
P5L127: 58 points is a specific number, it cannot be “around”.
Corrected.
P5128: […] six fixed points […]. In this sentence, you write six? However, on the L127 you mentioned “58 points…” with a number. Please harmonise.
According to the “house standards” in ESurf: “For items other than units of time or measure, use words for cardinal numbers less than 10; use numerals for 10 and above (e.g. three flasks, seven trees, 6 m, 9 d, 10 desks). Therefore, we have to follow the “house standards”.
P5L141: Table 2 is mentioned before Table 1.
Revised.
P5L151: Add focal length units.
Added.
P5L152: Add focal length units.
Added.
P5L155- L152: The sentence “However […]” is too ambiguous. Poor information is provided about the independent test.
Clarified.
P6L164-165: The sentence “Moreover […] ground […] is repetitive. You already mentioned this on L146. Please check the redundancy.
Thanks for point this redundancy issue. We modified this sentence.
P7L208: are you sure that the way to present “average density of points” is the correct way? Please verify this.
Density is usually quantified as a quantity per unit of volume (pts m-3). We will verify this with the Copernicus typesetting and language copy-editing services.
P8L223: I am confused. On the L210 you said that you generate ortho-mosaics at 0.1 m resolution. But here on the L223, you calculate surface displacements using orthomosaics at “one-tenth of the original pixel size (i.e. 0.01m)” which is not coherent. Please verify.
We added the following sentence: “To achieve displacements at sub-pixel precisions (Debella-Gilo and Kääb, 2011) the original orthomosaics were resampled to one-tenth of the original pixel size (i.e. 0.01 m).”
P8L229: Dis you check the influence of shadows on very high-resolution ortho-mosaics? This aspect is not even mentioned.
The investigated area inside the orthomosaics is normally free from deep shadows caused by high mountain relief. Therefore, we did not observe such influence in the CIAS results. We included this explanation.
P8l234-237: Disagree. Please see my general comment. No detailed information is presented about this issue (i.e. differences in stable areas, x-y shifts, etc.).
Please, see our previous response to this comment.
P8L240: Again, 69 is a specific number, it cannot be “around”. Also, these 69 “rock surfaces” are not displayed anywhere.
We removed “around”. Please, see our response to reviewer 1 (AR1).
P8L241: x-y-shift translation vectors are not mentioned anywhere. Please provide a detailed description of the specific values obtained from the Helmert similarity.
The x-y-shift translation vectors are included in a new supplementary material (Table) related to this manuscript.
P9L255: What means ca? Please check this. Moreover, no information on this comparison was presented. Please provide Z differences of these 35 points.
We removed “ca”. Also, the Z differences of these 35 points are included in a new supplementary material (Table) related to this manuscript.
P9L261-262: Uncertainties of DEMs, as well as uncertainties propagated, thought DoD calculation should be shown.
We included the DEM evaluation in a new supplementary material (Table) related to this manuscript. As the DoD calculation is not the main facet in our contribution, we refer to the original work of Wheaton et al. (2010) for further details.
P9L265: how much is this area examination? Please presents values on square meters.
Added. 50 064 m2.
P9L272: Did you measure the displacement of these 35 points? Additionally, these are the same used in section 3.4 (DEM assessment)?
Yes, they are the same. We made this more evident.
P11L335-339: Disagree. I think this paragraph is too ambiguous because it depends on your goals. Recent developments of satellite photogrammetry (i.e. world-view 2 and 3, Pleiades, etc) showed the high quality of their products even on rock glaciers.
In the framework of remote sensing approaches, our sentence makes a discussion about platform operation between classical aerial surveys or satellite programs (notably companies) and new UAV surveys (primarily researchers). We argued that UAV devices could help to close the gap between expensive commercial providers and small research initiatives (Eltner et al., 2016). We improved the paragraph accordingly.
P11L242: Disagree. Again, too ambiguous. The UAV survey can early take more than 30 minutes because it is weather-dependent. In this case. In case the conditions are not optimal, the acquisition time can easily exceed 30 minutes. I suggest changing this part.
To our experience, the typical UAV setup and pre-flight checks take less than 5 minutes. Since the geodetic measurements are fixed and already provided, this step is not needed for subsequent UAV surveys. In any case, we now indicated that the actual data capture from the first to the last images usually takes no more than 30 minutes (for the size of Tsarmine rock glacier), which is considerably less time than the regular GNSS data capture. Please, check Table 1, where the individual UAV survey times are indicated.
P12L344: Disagree. The limits of detection depend on the size of the window used for correlation and it should be tested on fixed areas. Some information about these values is partially reported in Table 3, however, more detailed information needs to be provided.
We improved the evaluation of sequential orthomosaics in stable areas and included the results in a new table. We also indicated that the estimated LoD takes into account the orthorectification and NCC uncertainties.
P12L350-356: This paragraph does not contribute anything to the study. It is maybe a general discussion about “optimal conditions” but this topic is already known.
Thanks for point out this. We included more precise details about the pros and cons. We made clear that the investigated area size, weather conditions and specific UAV regulations are all potential limiting factors for our study area.
P12L258-269: Disagree. This paragraph is redundant and a repetition of what the others already do. However, no technical comparisons are given about your protocol against the others (i.e. planning, processing, etc). I suggest revising or excluding this paragraph.
We agree that this section needs revision. However, from previous studies, we highlighted two main protocols issues that we have accounted for in the present contribution. The assessment of the stable areas (uncertainty estimation) and surface velocity validation by independent GNSS data were explained for five consecutive periods. We have indicated the most relevant survey and processing details, particularly in sections 2 and 3. Additional details are included on the new supplementary material (UAV surveys settings, DEM assessment and Helmert results).
P12L367-369: Ok, you are using stable terrain to validate your products but detailed information about these areas is not presented anywhere. Also, these areas are very small compared to the total extension of your DEMs. Please see my remark on P8l234-237.
Please see our previous comments about the stable terrain.
P12L375. The fact that you perform all working steps does not guarantee high-quality results. It should be proved by comparing independent methods. Additionally, a detailed report is needed to support this argument. I suggest revising or exclude this paragraph.
Agreed, we removed this sentence.
P13L404: "[…] net frontal retreats (Fig. 6)" reference is missing.
We added new references (Kääb and Reichmuth, 2005; Kummert et al., 2018).
P14L411: Surface velocities are showed instead of kinematic points. Please change this and also on Figure 9.
Changed “kinematic points” to “velocities values derived from…”
P14L428-430. Agree, but what is the contribution of this paragraph to your work? This paragraph takes place at the introduction instead than in the discussion section. Please revise this or exclude this paragraph.
We excluded this sentence.
P14L430-432: I could not find an uncertainty analysis. You are relating this to GNSS comparison? The fact that you are using very high-resolution products needs a robust statistical analysis concerning the uncertainties between photogrammetric products notable on stable areas (for DEMs) and surface velocities.
Changed to “The quality of the high-resolution UAV-derived datasets leads us to stress that regular and spatially distributed surface velocity measurements would permit landform-wide kinematics to be better monitored.”
P14L434: What are the differences between your UAV protocol against others? More details are needed to be related to “customisable data acquisition”.
Our protocol is tested and validated on a rock glacier during a destabilised period. See our similar responses to reviewer 1 (AR1).
P14L436-437: Agree. With your data, you could explain more extensively this process regarding even into sub-periods.
Thanks for acknowledging this. We included this in the new supplementary material.
P15L449-450: Even this works shows a detailed description of UAV surveys on rock glaciers, I difficult to me what’s is the main difference against a normal UAV survey. The current status of the manuscript does not show in detail the relevant differences of SfM photogrammetric studies.
We showed a detailed description of a destabilised rock glacier with a suitable UAV monitoring strategy. We changed the sentence: “This work detailed the use of UAV surveys to monitor rapid kinematic and geomorphological changes on destabilised rock glacier with enhanced temporal and spatial details.” Please, see our similar responses to reviewer 1 (AR1).
P18L564: the list of references needs revision. The reference Fugazza […] is not cited in the text.
Thanks for spotting! We added this reference to the manuscript.
Figures and tables
Figure 1. Panel b: add a north arrow to make clear the image.
Added
Figure 2 Panel b. Disagree with multitemporal co-registration. Please see my remark in general comments.
Changed to “Sequential SfM processing using four permanent GCP outside the rock glacier.”
Figure 4: I think that the community has much more interest to know which are the values of these limits of detection (LoD) instead than only the text. Please show specific values of LoD.
Agreed. Information about the mean LoD is indicated on each panel. Information about the LoD for each period is shown in Table 3.
Figure 5. This figure is nice. However, there is not always clear to relate a 3D view to a plane view as shown in Figure 4. I suggest changing the 3D image by a more explicit figure that shows the localisation of the longitudinal profile.
Thank you for the feedback. We included the localisation of the profile in Figure 1.
Figure 6. It is difficult to see front evolutions because the lines overlay. You said the mean “front line displacements” did you calculate this displacement over the entire line? If yes, precise which method did you use?
As suggested by the first reviewer, we modified the hillshade of this figure. We indicated the method on the figure caption.
Figure 7. These results could be showed better. Is too difficult to interpret this figure because even if the intervals are regular, there is not obvious to see ±0.8. The intervals should be divided by entire numbers (-1.0 - -2.0 as an example) instead of 0.8. Also, on the color scale, you say that you found values greater (less) than +6.8m (-6.8m), I suggest that you present the min and max values as well as the north arrow. Finally, please use a color scale adapted for colorblind people.
Thanks for the suggestions to improve our figure. As suggested by the first reviewer, we modified the categories accordingly and added the north arrow. Regarding the colour scale and the min/max values, we have followed the journal style for the representation of similar results. Please, see the relevant figures published recently on ESurf (Ulrich et al., 2021; Van Woerkom et al., 2019).
Figure 8. On panel a), please indicate the photo was acquired.
Agreed. Photograph acquired during the same day of the UAV survey (24 September 2019).
Table 1. Please provide the “GSD” acronym.
Thanks. We included “ground sample distance (GSD)” directly in the text.
Table 1. if it is a rigorous protocol, all flights were made between 11h-13h. Why was your last flight in the morning? I found no justification in the text. Please specify this. Did this early flight have any consequences on the velocity calculation? (important presence of shadows).
The UAV flight is typically performed simultaneously as the TGS or vice versa, but we must adjust the survey accordingly due to weather and personnel constraints. Please, see our previous response about the influence of “shadows”.
Table 2. Change “errors” by uncertainties.
We retain “errors” as this is the case for this type of statistics.
Table 2. Why are you expressing uncertainties in pixels? It should be better expressed in meters.
Changed to “meters.”
Table 3. Additional statistical analysis is required.
Thanks for this suggestion. However, we are not aware of such “additional statistical analysis” for this kind of data. We included the LoD values for the GNSS technique.
REFERENCES
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Van Woerkom, T., Steiner, J. F., Kraaijenbrink, P. D. A., Miles, E. S. and Immerzeel, W. W.: Sediment supply from lateral moraines to a debris-covered glacier in the Himalaya, Earth Surf. Dyn., 7(2), 411–427, doi:10.5194/esurf-7-411-2019, 2019.
Citation: https://doi.org/10.5194/esurf-2021-8-AC2
Interactive discussion
Status: closed
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RC1: 'Comment on esurf-2021-8', Gernot Seier, 02 Apr 2021
Dear authors,
Your manuscript entitled ‘Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier’ intends to show the added value of using UAVs and Structure-from-Motion-based photogrammetry for the quantification of rock glacier dynamics. The study is based on the comparison and analyses of photogrammetrically processed images acquired in the period 2016 to 2019. The manuscript aims at proposing technology-immanent benefits of using UAVs for rock glacier monitoring. As the main outcome, kinematic and volumetric changes and its variations and characteristics are presented.
Due to the general arguments and some detailed comments, I think that the manuscript needs amendment, please see my remarks as follows. In addition, even though I am not a native English speaker, I think the text is basically well-prepared and requires minor proof-reading only.
According to the manuscript’s title and presentation, the main aim of your contribution is to introduce UAVs in rock glacier monitoring and to propose SfM-photogrammetric UAV surveys as favorable approach compared to established techniques. This assumption is a central issue because even though UAVs are not as long in use as other methods and devices, today, UAVs are already established in geosciences. Therefore, research based on UAVs should either focus on methodological questions, which is not case in your study, or otherwise should in detail discuss and explain geomorphological changes, which rather should be the aim of your manuscript. Therefore, I think it is necessary to revise the title and presentation of the manuscript. In addition, as there are other previous studies, please expand the relating literature discussing UAV-based surveys on rock glaciers. Also, the discussion on relating studies as in the present form needs revisions, please see my detailed comments concerning P12L362-376.
In terms of validation of the UAV-based results, geodetic measurements are shown in order to independently assess the quality. However, the way of how the UAV survey-related design and the relating provided information are presented does not allow to completely comprehend the methodological benefits. Several details concerning the survey design, such as the planned and actual flight paths and coverages, the estimated theoretical precision compared to actual achieved precision, the details of processing including, e.g., the quality of tie points on the image plain, as well as a dimensionless theoretical assessment of the achieved quality are just some but relevant information that would help to promote UAV-based surveys, which is not the case in the current form of the manuscript. I think that such a methodological discussion and information is the prerequisite for a technology-featuring presentation of the manuscript. In contrast, the manuscript appears as a well designed and presented case study of a rock glacier’s kinematics but does not introduce new methodological approaches and therefore, should focus on the characteristics and specifics of the landform investigated. In this sense, it appears rather inappropriate to contend that UAVs are a new method for rock glacier monitoring as this is not the case.
Concerning the survey design it would be necessary to first define what is required in terms of survey quality and the landform investigated in order to then conclude whether it was appropriate or not. Instead, the manuscript is characterized by a rather vague survey concept in order to subsequently conclude that the results are quite appropriate. In other words, at first it should be declared what survey quality is strived and estimated, which would then allow for assessing whether or whether not the results are appropriate.
The description of the processing needs revision. Without presenting and discussing photogrammetrically relevant parameters, such as exterior and interior orientation parameters, the quality of tie points and residuals of GCPs, photogrammetric studies are not comprehensible and meaningful. Therefore, the robust and detailed workflow that is stressed by the authors lacks these important components, which I think needs to be amended and the formulation revised. In addition, today, numerous articles are based on SfM-MVS photogrammetry. I suggest to expand and discuss the relevant literature in more detail, as there is no ample discussion and interrelationship with existing subject-specific literature yet.
Other methodological questions could deal with potential issues using the RTK-based survey configuration, e.g., are UAV-based surveys solely using direct georeferencing really capable of achieving the required quality? This could be worth discussing.
The presentation of the rock glacier’s velocities based on an area-based matching algorithm needs revisions. The validation of the velocity values should be expanded and the description revised, as the matching settings (grid size, correlation window size) are necessarily adjusted to the specific case and pair of images, e.g., the approx. 13 m large windows should be able to track 13 m long displacements (cf. P8L227). As a consequence, this results in high correlation values (R2 values presented in Section 4.1) and therefore, such a comparison of geodetically and NCC-derived velocities inherently cannot be completely independent. And this at least should be mentioned. Similarly, the presentation of the movement’s directional quality (Section 4.2) could be more comprehensible by explicitly mentioning that the directions were smoothed, as a directional filter was applied (Section 3.3).
The surface velocity fields should be revised, as thus far, categories of different velocities are presented and instead, vectors that show the exact displacement value should be presented, which also would allow for including and presenting the displacement vector-specific LoD value. As mentioned in Section 3.3 (P9L251), it would be a real benefit for the reader if these vector-specific LoDs would be shown in maps.
Detailed comments:
P1L10-11: As the survey configuration details are not completely outlined, it is not tenable to contend that a rigorous procedure is introduced.
P1L20-21: As the comparison with GNSS-based measurements is mentioned here and the description of the rock glacier dynamics, the main research contribution is the investigation of the specific rock glacier’s dynamics and behavior rather than methodological questions.
P2L36-48: What about rock glacier kinematic surveys beyond the European Alps?
P2L52-53: Style – “[…], evidence of […] identified as evident signs […]”.
P2L61: Style – “The quantification […] has been measured […]”.
P3L72: “[…] Unmanned Aerial Vehicles (UAV) systems […]”. Plural ending not correct, please check throughout the manuscript.
P3L79-80: Expand the list of published studies dealing with UAV-based rock glacier surveys. As there are already studies demonstrating the benefits and challenges of UAV-based rock glacier surveys and as generally, the landform rock glacier does not entail a specific methodological treatment compared to other landforms and as SfM photogrammetric UAV-based surveys are today already established, this cannot be the research question.
P3L81: Yes, but both a protocol and relevant details of the UAV-related configuration and processing are not discussed in this manuscript and therefore, this should not be mentioned and understood as the research question.
P3L82: It is meant “[…] high altitude […]“, please clarify.
P3L84-85: General statement that I do not support. One could also argue, as the surface velocities are in a hardly observable cm-range, a thorough validation is necessary. Therefore, no, different rock glacier velocities are not an argument.
P3L86: So far it was not mentioned in the manuscript that the quality of kinematic data is an issue, so, maybe it should be clarified at first that kinematic measurements are of diverse quality, which is why a thorough validation is necessary.
P3L92-93: This is the formulation of the study’s aims, which are a better understanding of the rock glacier behavior and dynamics. Therefore, your study contributes to rock glacier monitoring rather than the technique or methodological questions and therefore, the presentation should not focus on UAVs for the simple reason that these are maybe not that commonly used on rock glaciers yet, which is, if indeed, possibly coherent with the number of rock glacier studies.
P4L111: “[…] 2016. the []”.
P4L114: Please clarify, that this specific landform “Tsarmine” was meant.
P5L427: As it is a specific number of points (58), it cannot be “around”.
P5L132: I would say that 2 cm are also in the cm range, please clarify.
P5L141: Table 2 is mentioned before Table 1, modify.
P5L152: Add the focal length’s unit.
P5L154: Do you really mean “accuracy” of the RTK-based camera positions, as I cannot see the relationship to other, independent measurements, please clarify.
P5L155: Explicitly mention that the low accuracy is too low in terms of the study-relating aims, because low accuracy per se could still suffice.
P5L155-156: Please expand with a few words the tests mentioned in order to make the statement more comprehensible. In addition, with “mainly” you mean “mostly”?
P6L160-161: As you describe the planned image overlap of your survey, a citation does not make sense; delete the reference or clarify.
P7L198: It should be “[…] GCPs next to the […]” or similar.
P7L203: In order to discuss the quality of the bundle adjustment it is necessary to present and discuss the data of exterior and interior orientation parameters and the quality of the tie points.
P7L210: Check plural ending and indefinite article. Also, mention for clarity that the orthomosaics were resampled to 0.01 m, as the GSDs differed (cf. Table 1).
P7L213: Mention the subsections number instead of “previous step”, as this would be clearer.
P7L21-216: As you describe the principle, it does not make sense to relate to rock glaciers; the principle is valid for every surface surveyed.
P7L217: With “extensive” it is meant “larger”, which is more applicable, I think.
P8L237: Please check with the journal requirements whether or not the citation (“their Fig 2”) is appropriate.
P8L240: As it is a specific number of points (69), it cannot be “around”. Also, show the 69 subareas in the map.
P9L255: As it is a specific number of points (35), it cannot be “ca.”. Moreover, I cannot find the relating results of the mentioned comparison. In addition, show the spatial distribution of these 35 points in a map, as this is not the case yet.
P9L272: For understanding: these are the same 35 points mentioned in Section 3.4 (here used as independent z check points)?
P9L274: Is the term ‘significant’ in the sense of statistically significant appropriate here?
P11L335-337: Agree, but why are then the relating details of acquisition, processing and analysis not presented yet?
P11L337-339: Disagree, the inability of potentially new UAV-users cannot be anticipated, which is also attenuated by the high degree of automatization and usability of modern UAVs. Also, the depreciation of commercial UAV flight providers is not comprehensible as the necessary information needs to be negotiated and should be part of the contract, which is why commercial UAV survey providers of course could deliver the required data and metadata.
P11L342: This discussion could be more controversial as 30 minutes could be the net flight time, but usually the setup and pre-flight checks also need time as well as accompanying geodetic measurements and moreover, UAV flights are more weather-dependent (so probably it is necessary to wait for optimum conditions), which is why usually a UAV survey takes remarkably more time than 30 minutes.
P12L344: The different LoD values resulting from NCC and GNSS are not completely shown yet, only partially in Table 3.
P12L352: Elaborate, what are the “[…] suitable environmental conditions […]”? In addition, what is the point of “ […] that means about four months a year […]”? Usually, also geodetic surveys (except permanent measurements of a single point) are conducted in the snow-free season, so this is not specific for UAV surveys.
P12L350-356: This is a rather general discussion and the relating pros and cons were not investigated in the study.
P12L360-361: As it is obviously necessary to make SfM photogrammetric studies more comprehensible using protocols and standards, consequently, why don’t you present and discuss the complete survey details including planning, theoretical and actual quality estimates, processing settings etc.?
P12L362-376: This is a repetition of how (only) some others (i.e. not all relating studies) performed UAV-based studies on rock glaciers and as the text passage stresses you performed something what others did not, the character of this text passage is rather contemptuous. Therefore, I suggest to revise or exclude this text passage.
P12L373: Disagree, it cannot be concluded that companies are not willing to deliver what is necessary, it is rather necessary to adequately negotiate a contract by those interested in processing the data.
P12L374: The term “intrinsic” is distracting, as interior orientation parameters could be meant with this but which are not presented in Table 2 or elsewhere in the manuscript.
P12L375: To perform all working steps by oneself is not a guarantee for high-quality results. I fail to see any argument and therefore suggest to revise or exclude this paragraph.
P13L395: Add “[…] Tsarmine rock glacier […]” for clarity.
P14L411-412: Not the kinematic points but their velocities are shown.
P14L432: Which proposed uncertainty analysis you are relating to here? I cannot find relating data.
P14L434: Disagree, there are no details presented concerning the customized data acquisition and robustness of processing.
P14L434-440: As UAV-based SfM-photogrammetric studies are already established and as the landform of rock glaciers does not entail any specific methodological adaptations, I fail to understand what is concluded in this text passage and therefore suggest revision.
P15L449: Disagree, the current form of the manuscript does not show all details relevant in SfM-photogrammetric studies.
P18L564: The list of references needs revision, e.g., the publication in P18L564, which is not mentioned in the text yet.
Figure 4: In the legend: shouldn’t the category be “1-LoD” instead of “LoD-1”? As already mentioned, I think it would be favorable to show real vectors instead of categories, which would then also allow to show the displacement-specific LoD values.
Figure 6: The hillshade could be more low-contrast or so, which would then probably better allow to perceive the lines.
Figure 7: The categories of elevation differences are partially overlapping and therefore, seem to be wrong, e.g., categories “-4.50 to -3.70” m and “-3.80 to -3.00” m etc.
Table 1: This table could be expanded with values of theoretically achievable precision estimates, which are survey configuration-specific.
Table 2: Expand the table by showing both, the RMSEs of GCPs and CPs on the modelled surface as well as the image plane.
Table 3: Mention the relating confidence interval.
I hope you will find my comments appropriate,
Gernot Seier
Citation: https://doi.org/10.5194/esurf-2021-8-RC1 -
AC1: 'Reply on RC1', Sebastián Vivero, 12 May 2021
We want to thank Gernot Seier for his technical review that will help to improve some essential aspects of the manuscript.
We agree with most of the general and detailed comments made (as explained below) and modified the manuscript accordingly.
The referee comments are in italic (red) font, and our responses and revisions are in normal (black) font.
General comments:
Your manuscript entitled ‘Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier’ intends to show the added value of using UAVs and Structure-from-Motion-based photogrammetry for the quantification of rock glacier dynamics. The study is based on the comparison and analyses of photogrammetrically processed images acquired in the period 2016 to 2019. The manuscript aims at proposing technology-immanent benefits of using UAVs for rock glacier monitoring. As the main outcome, kinematic and volumetric changes and its variations and characteristics are presented.
We learnt from your comments and agree with your central assessment that our aims and arguments concerning the benefits of using UAV monitoring techniques in rock glaciers were not well understood. Our objectives are to propose and explore a monitoring method for rock glaciers using UAV-derived data validated on a destabilized rock glacier. Our study's findings can potentially contribute to established permafrost monitoring networks (like PERMOS). As explained during the first introductory paragraph, rock glacier dynamics cannot be directly measured by remote sensing techniques alone (i.e. UAV-SfM). Therefore, we claim that our paper deals with quantifying rock glacier kinematics (i.e. change in geometry with time), which is a piece of complementary information to understand the dynamical processes associated with the creep of mountain permafrost (see Haeberli et al., 2006).
Due to the general arguments and some detailed comments, I think that the manuscript needs amendment, please see my remarks as follows. In addition, even though I am not a native English speaker, I think the text is basically well-prepared and requires minor proofreading only.
Thanks for these comments. We are also not native English speakers, and we speak different languages, but we enjoy disseminating our work in English and as well as in other languages.
According to the manuscript’s title and presentation, the main aim of your contribution is to introduce UAVs in rock glacier monitoring and to propose SfM-photogrammetric UAV surveys as favorable approach compared to established techniques. This assumption is a central issue because even though UAVs are not as long in use as other methods and devices, today, UAVs are already established in geosciences. Therefore, research based on UAVs should either focus on methodological questions, which is not case in your study, or otherwise should in detail discuss and explain geomorphological changes, which rather should be the aim of your manuscript. Therefore, I think it is necessary to revise the title and presentation of the manuscript. In addition, as there are other previous studies, please expand the relating literature discussing UAV-based surveys on rock glaciers. Also, the discussion on relating studies as in the present form needs revisions, please see my detailed comments concerning P12L362-376.
We partially agree with this statement. As indicated in the manuscript introduction, we propose UAV surveys as a complementary method to monitor rock glacier kinematics. For achieving this, we exploited the capabilities of the image correlation software CIAS to derived landform-wide kinematic fields from sequential UAV-SfM-derived orthomosaics. A fundamental step before explaining the geomorphological changes was to validate the results via independent ground information during five consecutive periods. The good agreement with data collected by repeated dGNSS demonstrated the robustness and reliability of the monitoring protocol (Figure 3), which similar studies have not demonstrated. Nevertheless, we decided to change the title of the revised manuscript to “Application of sequential unmanned aerial vehicle surveys to monitor the kinematics and geomorphological changes of a rapid rock glacier”. We also included more literature discussing UAV-based surveys on rock glaciers (Halla et al., 2021; Kaufmann et al., 2018), but it has to be noted that published studies having quantified rock glacier kinematics using UAVs remain very few to our knowledge.
In terms of validation of the UAV-based results, geodetic measurements are shown in order to independently assess the quality. However, the way of how the UAV survey-related design and the relating provided information are presented does not allow to completely comprehend the methodological benefits. Several details concerning the survey design, such as the planned and actual flight paths and coverages, the estimated theoretical precision compared to actual achieved precision, the details of processing including, e.g., the quality of tie points on the image plain, as well as a dimensionless theoretical assessment of the achieved quality are just some but relevant information that would help to promote UAV-based surveys, which is not the case in the current form of the manuscript. I think that such a methodological discussion and information is the prerequisite for a technology-featuring presentation of the manuscript. In contrast, the manuscript appears as a well designed and presented case study of a rock glacier’s kinematics but does not introduce new methodological approaches and therefore, should focus on the characteristics and specifics of the landform investigated. In this sense, it appears rather inappropriate to contend that UAVs are a new method for rock glacier monitoring as this is not the case.
The quality of 3-D point clouds and orthomosaics derived from UAV-SfM workflows depend on several physical, geometric and processing parameters (Benassi et al., 2017): surface texture and contrast, air refraction index, lighting conditions, sensor quality, global or rolling shutter, image sharpness, flight height and speed, grid pattern, camera angle, forward and side overlaps, the distribution and accuracy of GCPs, camera self-calibration, BBA, image matching algorithms, point cloud densification and outlier removal algorithms among other parameters. In this context, determining the quality of several SfM parameters is a complex mission, as the number of related variables is quite large (even though some parameters can be kept unchanged like grid patterns or image overlaps). Furthermore, a degree of spatial uncertainty accompanies the orthomosaics generation as well as the performance of the automatic image matching via correlation (Leprince et al., 2007; Redpath et al., 2016). Nevertheless, when deriving surface movement from sequential orthomosaics, we exploited the relative accuracy of the coregistration on stable sectors as the overall source of uncertainty. We expanded the section dealing with the coregistration assessment and added a new table. In doing this, we assume to account for the variability of these different parameters represented on either the orthomosaics or the point clouds (Cook and Dietze, 2019). We made this concept more evident through the manuscript. We also include more technical details about the UAV surveys on the new supplementary material.
Focusing the manuscript on the investigated landform would require adding many more data acquired on-site for near 20 years to completely reorganize it and shift the purpose to the landform dynamics. It was not our primary goal but to explore the benefits/complementarity of UAV-based survey to the ongoing kinematic monitoring. We prefer to keep the paper in its original objective but improve it accordingly (see our various responses below).
Concerning the survey design it would be necessary to first define what is required in terms of survey quality and the landform investigated in order to then conclude whether it was appropriate or not. Instead, the manuscript is characterized by a rather vague survey concept in order to subsequently conclude that the results are quite appropriate. In other words, at first it should be declared what survey quality is strived and estimated, which would then allow for assessing whether or whether not the results are appropriate.
We acknowledge that the UAV survey concept was also not well explained. The strived survey quality was not explicitly mentioned. As most of the landform is moving up to several meters between each survey and according to that, the relative stability of the surface material, which is exploited with any ground-based or remote technique is not fully insured (some tilting or sliding of the surface boulders can be expected in many places), a minimal accuracy of about 10 cm yr-1 or better in the resulting displacement rate would be adequate. Nevertheless, we maintained that the GNSS survey design follows the protocol design by Lambiel and Delaloye (2004), which has been established as a standard for rock glacier kinematics, at least for some national monitoring initiatives (see PERMOS reports). We depart from this framework with the addition of UAV surveys during the same TGS campaigns. The choice of the spatial and temporal characteristics of the UAV surveys was not trivial. The spatial resolution allowed to track rock glacier surface texture at 10 cm finely, and the biannual surveys are adapted to the high rock glacier speeds. We also indicated and discussed some factors that can degrade the quality of the UAV-derived velocities. The experimental design in this challenging terrain can provide a better assessment for destabilized rock glaciers, as this is the case for Tsarmine. We have made some amendments to the original manuscript to make this clearer.
The description of the processing needs revision. Without presenting and discussing photogrammetrically relevant parameters, such as exterior and interior orientation parameters, the quality of tie points and residuals of GCPs, photogrammetric studies are not comprehensible and meaningful. Therefore, the robust and detailed workflow that is stressed by the authors lacks these important components, which I think needs to be amended and the formulation revised. In addition, today, numerous articles are based on SfM-MVS photogrammetry. I suggest to expand and discuss the relevant literature in more detail, as there is no ample discussion and interrelationship with existing subject-specific-literature yet.
We agree that the data processing sections need revisions. We changed the emphasis to the evaluation of the UAV-SfM-derived products rather than the SfM processing. In doing so, we included a new section (3.4 Comparison with the TGS) where we better explained the validation protocol. We also expanded the section dealing with the coregistration assessment and added a new table. Regarding your last sentence, we are aware of most of those studies dealing with SfM-MVS photogrammetry, particularly in ESurf, but tried to keep the focus on the rock glacier applications.
Other methodological questions could deal with potential issues using the RTK-based survey configuration, e.g., are UAV-based surveys solely using direct georeferencing really capable of achieving the required quality? This could be worth discussing.
We thank the reviewer for this comment, but this methodological issue has been already discussed (see Benassi et al., 2017). The EBee RTK cannot achieve the so-called "direct georeferencing" since the camera attitude angles are not constrained by the IMU (only default values are available). That is why we performed a GNSS-support Aerial triangulation (GNSS-AT) with at least four GCPs. We included this explanation in the revised manuscript.
The presentation of the rock glacier’s velocities based on an area-based matching algorithm needs revisions. The validation of the velocity values should be expanded and the description revised, as the matching settings (grid size, correlation window size) are necessarily adjusted to the specific case and pair of images, e.g., the approx. 13 m large windows should be able to track 13 m long displacements (cf. P8L227). As a consequence, this results in high correlation values (R2 values presented in Section 4.1) and therefore, such a comparison of geodetically and NCC-derived velocities inherently cannot be completely independent. And this at least should be mentioned. Similarly, the presentation of the movement’s directional quality (Section 4.2) could be more comprehensible by explicitly mentioning that the directions were smoothed, as a directional filter was applied (Section 3.3).
We thank the reviewer for pointing on this valid concern, which we have been aware of during our CIAS analysis. The decision to use a particular combination of reference and search window sizes was pragmatic because the expected maximum displacement can be estimated beforehand from the visual inspection of sequential orthomosaics. In this regard, keeping the exact configuration of the search and window sizes provided only a theoretical maximum displacement limit of about 13 m (more than twice the maximum value observed) for each pair of consecutive orthomosaics. Repeating the CIAS processing using larger windows sizes increases both computing time and the number of bundlers (for a detailed explanation, see Kääb and Vollmer, 2000). As such, we do not agree with the argument of high r2 values (Figure 3) are related to the limit of 13 m, as we were able to quantify different maximum displacement values during different periods.
We removed the application of the directional filter, as we found it to be irrelevant for the few serious mismatches, which can be manually removed. The overall change caused by this filter was relatively small, and therefore, there is no smoothing effect in the results presented in Section 4.2.
The surface velocity fields should be revised, as thus far, categories of different velocities are presented and instead, vectors that show the exact displacement value should be presented, which also would allow for including and presenting the displacement vector-specific LoD value. As mentioned in Section 3.3 (P9L251), it would be a real benefit for the reader if these vector-specific LoDs would be shown in maps.
We thank the reviewer for this suggestion. However, we performed several tests and reached the conclusion that standardized velocities categories are better suited to highlight the rock glacier velocities changes during the study period, as this is also the case for displaying elevation changes. For instance, previous publications in ESurf also prefer to show such quantities in categories rather than individual vectors (see Clapuyt et al., 2017; Monnier and Kinnard, 2017; Piermattei et al., 2016) as well as other rock glacier kinematic studies (Micheletti et al., 2015; Scotti et al., 2017; Seppi et al., 2019). We also performed some tests to integrate the LoD values in Figure 4, but we did not reach satisfactory results. The mean LoD for each period is now indicated in Figure 4, and LoD statistics for each period are shown in Table 3.
Detailed comments:
P1L10-11: As the survey configuration details are not completely outlined, it is not tenable to contend that a rigorous procedure is introduced.
Agreed, we removed "rigorous" from the abstract.
P1L20-21: As the comparison with GNSS-based measurements is mentioned here and the description of the rock glacier dynamics, the main research contribution is the investigation of the specific rock glacier’s dynamics and behavior rather than methodological questions.
We included more arguments about the need for the improvement and validation of the monitoring protocol.
P2L36-48: What about rock glacier kinematic surveys beyond the European Alps?
Without being Eurocentric, we must acknowledge that the majority and best quality rock glacier kinematic data are found on the European Alps (Kellerer-Pirklbauer et al., 2018). There are intermittent examples of early rock glacier kinematics surveys outside the European alps, such as the Pedregoso rock glacier in the South American Andes (Marangunic, 1976) or the Galena Creek rock glacier in North America (Potter, 1972). Promisingly, recent remote sensing research has become critical to reducing this gap between Europe and other rock glacier regions (Blöthe et al., 2020; Kääb et al., 2021; Strozzi et al., 2020). We added some information for extra-European rock glaciers.
P2L52-53: Style – “[…], evidence of […] identified as evident signs […]”.
Agreed, we removed “evident” from the sentence.
P2L61: Style – “The quantification […] has been measured […]”.
Changed: “Rock glacier kinematics have been traditionally….”
P3L72: “[…] Unmanned Aerial Vehicles (UAV) systems […]”. Plural ending not correct, please check throughout the manuscript.
Thanks. We have corrected this issue.
P3L79-80: Expand the list of published studies dealing with UAV-based rock glacier surveys. As there are already studies demonstrating the benefits and challenges of UAV-based rock glacier surveys and as generally, the landform rock glacier does not entail a specific methodological treatment compared to other landforms and as SfM photogrammetric UAV-based surveys are today already established, this cannot be the research question.
As mentioned before, we have included the work by Kaufmann et al. (2018). However, we did not find other studies dealing exclusively with UAV-based rock glacier kinematics. Furthermore, we argued that some rock glaciers are currently destabilized (like Tsarmine), and they can behave in a unique fashion that does not follow other types of landforms (they have a different dynamical response than glaciers, solifluction lobes, debris-cover glaciers or landslides). Therefore, we emphasised the challenges raised by the unique response of destabilized rock glaciers and the potential benefits and limitations of a monitoring strategy based solely on sequential and systematic UAV surveys.
P3L81: Yes, but both a protocol and relevant details of the UAV-related configuration and processing are not discussed in this manuscript and therefore, this should not be mentioned and understood as the research question.
We cannot totally agree with this statement. The study area is characterized by the availability of high-quality ground truth information like permanent GNSS stations and biannual GNSS surveys, together with complementary close-range remote sensing techniques such as terrestrial laser scanner (TLS) surveys and webcam devices. Our results are discussed against similar research (Dall’Asta et al., 2017; Fey and Krainer, 2020), focusing on quantifying rock glacier displacements and their related uncertainty, together with the validation strategies. Additionally, the discussion also provides some perspectives when our results are compared with concurrent InSAR investigations on the same rock glacier (Strozzi et al., 2020). With the details added to the manuscript (see other responses above) and the improved discussion, we are convinced that the stated research question is justified. To make those arguments more evident, we have changed the sentence: “However, as UAV systems are continuously changing and improving, there is still scope for the assessment of monitoring protocols using different UAV configurations in high altitude and challenging terrain.”
P3L82: It is meant “[…] high altitude please clarify.
Done.
P3L84-85: General statement that I do not support. One could also argue, as the surface velocities are in a hardly observable cm-range, a thorough validation is necessary. Therefore, no, different rock glacier velocities are not an argument.
We modified this sentence. “In the context of rapid rock glacier acceleration and destabilization, new and customizable monitoring techniques are necessary.”
P3L86: So far it was not mentioned in the manuscript that the quality of kinematic data is an issue, so, maybe it should be clarified at first that kinematic measurements are of diverse quality, which is why a thorough validation is necessary.
Thanks, we clarified this: “Likewise, as the quality of kinematic data obtained from different remote sensing techniques can be variable, a systematic ground validation through consecutive periods is required to improve the monitoring techniques and shed light on rock glaciers' kinematic behaviour in great spatial detail.”
P3L92-93: This is the formulation of the study’s aims, which are a better understanding of the rock glacier behavior and dynamics. Therefore, your study contributes to rock glacier monitoring rather than the technique or methodological questions and therefore, the presentation should not focus on UAVs for the simple reason that these are maybe not that commonly used on rock glaciers yet, which is, if indeed, possibly coherent with the number of rock glacier studies.
Thank you for these comments. We have improved our arguments, and we indicated that a particular monitoring technique and its validation are still needed for rock glaciers, especially during acceleration and destabilization phases.
P4L111: “[…] 2016. the []”.
We do not see this error in the original manuscript.
P4L114: Please clarify, that this specific landform “Tsarmine” was meant.
Done.
P5L427: As it is a specific number of points (58), it cannot be “around”.
Corrected.
P5L132: I would say that 2 cm are also in the cm range, please clarify.
We changed to “1–2 cm range”.
P5L141: Table 2 is mentioned before Table 1, modify.
Revised.
P5L152: Add the focal length’s unit.
Added.
P5L154: Do you really mean “accuracy” of the RTK-based camera positions, as I cannot see the relationship to other, independent measurements, please clarify.
We changed to “precision”.
P5L155: Explicitly mention that the low accuracy is too low in terms of the study-relating aims, because low accuracy per se could still suffice.
Clarified: “The UAV camera orientation values (Roll, Pitch, and Yaw angles) recorded by the Inertial Measurement Unit (IMU) device have low accuracy, hampering a reliable block orientation by the direct sensor orientation (DSO) method.”
P5L155-156: Please expand with a few words the tests mentioned in order to make the statement more comprehensible. In addition, with “mainly” you mean “mostly”?
We changed to: “However, independent tests using different combinations of GCPs have found that position accuracies are mostly too optimistic, suggesting that some sort of ground or check control should be included during the UAV block orientation (Benassi et al., 2017).”
P6L160-161: As you describe the planned image overlap of your survey, a citation does not make sense; delete the reference or clarify.
Agreed.
P7L198: It should be “[…] GCPs next to the […]” or similar.
Corrected.
P7L203: In order to discuss the quality of the bundle adjustment it is necessary to present and discuss the data of exterior and interior orientation parameters and the quality of the tie points.
Thanks for pointing out this. As we mentioned before, we are not thoroughly discussing the quality of the SfM procedure but rather the quality of the sequential datasets derived from it. We included other results in Table 2 (Mean Reprojection Error). We argued that the checkpoints are the most suitable way to independently gauge the quality of the bundle adjustment (see James and Robson, 2014) rather than the interior or exterior orientation parameters.
P7L210: Check plural ending and indefinite article. Also, mention for clarity that the orthomosaics were resampled to 0.01 m, as the GSDs differed (cf. Table 1).
We corrected this and changed the manuscript accordingly.
P7L213: Mention the subsections number instead of “previous step”, as this would be
clearer.
Changed.
P7L21-216: As you describe the principle, it does not make sense to relate to rock glaciers; the principle is valid for every surface surveyed.
We changed to “moving surface”.
P7L217: With “extensive” it is meant “larger”, which is more applicable, I think.
We changed to “larger”.
P8L237: Please check with the journal requirements whether or not the citation (“their Fig 2”) is appropriate.
We are not aware of such specific requirements. Nonetheless, we will leave it to the potential typesetting and copy-editing services provided by Copernicus Publications.
P8L240: As it is a specific number of points (69), it cannot be “around”. Also, show the 69 subareas in the map.
We changed to “between 60 and 69 stable rock surfaces” and included a new table with the results of the coregistration assessment. Also, there are not 69 subareas, but there are 69 points circumscribed to the stable sectors in Fig1C.
P9L255: As it is a specific number of points (35), it cannot be “ca.”. Moreover, I cannot find the relating results of the mentioned comparison. In addition, show the spatial distribution of these 35 points in a map, as this is not the case yet.
We changed to “35 TGS points”. The results of this comparison and the spatial distribution of these points are included in a new supplementary material (table and figure) related to this manuscript.
P9L272: For understanding: these are the same 35 points mentioned in Section 3.4 (here used as independent z check points)?
Yes, they are the same. We made this more evident.
P9L274: Is the term ‘significant’ in the sense of statistically significant appropriate here?
We removed the term “significant.”
P11L335-337: Agree, but why are then the relating details of acquisition, processing and
analysis not presented yet?
The requested details of acquisition and processing are presented in sections 2.3 and 3.2, and the corresponding analysis is delivered through the “Results" section.
P11L337-339: Disagree, the inability of potentially new UAV-users cannot be anticipated, which is also attenuated by the high degree of automatization and usability of modern UAVs. Also, the depreciation of commercial UAV flight providers is not comprehensible as the necessary information needs to be negotiated and should be part of the contract, which is why commercial UAV survey providers of course could deliver the required data and metadata.
In the framework of remote sensing approaches, our sentence makes a discussion about platform operation between classical aerial surveys or satellite programs (notably companies) and new UAV surveys (primarily researchers). In this regard, we stated the benefit of low-cost surveying tools, which allows the scientists to be in charge of the data acquisition (Anderson et al., 2019; Eltner et al., 2016), potentially closing the gap between commercial aerial photography and small research initiatives.
P11L342: This discussion could be more controversial as 30 minutes could be the net flight time, but usually the setup and pre-flight checks also need time as well as accompanying geodetic measurements and moreover, UAV flights are more weather-dependent (so probably it is necessary to wait for optimum conditions), which is why usually a UAV survey takes remarkably more time than 30 minutes.
To our experience, the typical UAV setup and pre-flight checks take less than 5 minutes. Since the permanent GCPs are fixed and already provided, this step is not needed for subsequent UAV surveys. In any case, we now indicated that the actual data capture from the first to the last images usually takes no more than 30 minutes (roughly the time between takeoff and landing) for the size of the Tsarmine rock glacier, which is considerably less time than the regular GNSS data capture (which is 2 hours from the first to the last measurement). Please, check Table 1, where the individual UAV survey times are indicated. The flight plan mission is now included in the supplementary material.
P12L344: The different LoD values resulting from NCC and GNSS are not completely shown yet, only partially in Table 3.
The LoD values from GNSS are now included in Table 3.
P12L352: Elaborate, what are the “[…] suitable environmental conditions […]”? In addition, what is the point of “ […] that means about four months a year […]”? Usually, also geodetic surveys (except permanent measurements of a single point) are conducted in the snow-free season, so this is not specific for UAV surveys.
We changed to “suitable weather conditions”. We changed to “For our study area, the snow-free period usually spans for four months a year”.
We have to disagree with the second sentence, as geodetic surveys can be conducted during the snow season, particularly exploiting prominent boulders at the rock glacier surface (see Perruchoud and Delaloye, 2007).
P12L350-356: This is a rather general discussion and the relating pros and cons were not investigated in the study
Thanks for point out this. We included more precise details about the pros and cons. We made clear that the investigated area size, weather conditions and specific UAV regulations are all potential limiting factors for our study area.
P12L360-361: As it is obviously necessary to make SfM photogrammetric studies more comprehensible using protocols and standards, consequently, why don’t you present and discuss the complete survey details including planning, theoretical and actual quality estimates, processing settings etc.?
From previous studies, we highlighted two main protocols issues that we have accounted for in the present contribution. The assessment of the stable areas (uncertainty estimation) and surface velocity validation by independent GNSS data were explained for five consecutive periods. We have indicated the most relevant survey and processing details, particularly in sections 2 and 3. Additional details are included on the new supplementary material (UAV surveys settings, DEM assessment and Helmert results).
P12L362-376: This is a repetition of how (only) some others (i.e. not all relating studies) performed UAV-based studies on rock glaciers and as the text passage stresses you performed something what others did not, the character of this text passage is rather contemptuous. Therefore, I suggest to revise or exclude this text passage.
We acknowledge the early work of Dall’Asta et al. (2017) to establish a UAV monitoring protocol on rock glaciers. Their work inspired us to test such approaches on a rapid rock glacier with systematic kinematic measurements since 2004. However, we also have to highlight the main differences with previous researches to show the advances in data interpretation and validation, which are part of the current contribution. However, we recognize that the tone is a bit contemptuous, and we made the changes accordingly.
P12L373: Disagree, it cannot be concluded that companies are not willing to deliver what is necessary, it is rather necessary to adequately negotiate a contract by those interested in processing the data.
We have not concluded such a statement as the original article reads: “Since the UAV flight and the data processing were performed by an external company more detailed information are not available”(Fey and Krainer, 2020, p.4). From this evidence, we stated that Fey and Krainer (2020) did not provide relevant error metrics such as RMSE, mean error or standard deviation error, which could have helped to evaluate the overall quality of the UAV-SfM derived products presented in their article.
P12L374: The term “intrinsic” is distracting, as interior orientation parameters could be meant with this but which are not presented in Table 2 or elsewhere in the manuscript.
We changed to “relevant quality data”. Table 2 expanded with more relevant results.
P12L375: To perform all working steps by oneself is not a guarantee for high-quality results. I fail to see any argument and therefore suggest to revise or exclude this paragraph.
Agreed, we removed this sentence.
P13L395: Add “[…] Tsarmine rock glacier […]” for clarity.
Added.
P14L411-412: Not the kinematic points but their velocities are shown.
Changed “kinematic points” to “velocities values derived from…”
P14L432: Which proposed uncertainty analysis you are relating to here? I cannot find relating data.
We removed “based on the proposed uncertainty analysis.”
P14L434: Disagree, there are no details presented concerning the customized data
acquisition and robustness of processing.
We included more relevant details about UAV data acquisition and processing results. We changed to “The customised UAV data acquisition, and the subsequent data processing workflow delivered spatially distributed kinematics for this destabilized rock glacier during the 2016–2019 period.”
P14L434-440: As UAV-based SfM-photogrammetric studies are already established and as the landform of rock glaciers does not entail any specific methodological adaptations, I fail to understand what is concluded in this text passage and therefore suggest revision.
We changed our argument, and we explained why a destabilized rock glacier (i.e. Tsarmine) entails a specific UAV monitoring strategy.
P15L449: Disagree, the current form of the manuscript does not show all details relevant in SfM-photogrammetric studies.
We removed “SfM techniques”.
P18L564: The list of references needs revision, e.g., the publication in P18L564, which is not mentioned in the text yet.
Thanks for spotting! We added this reference to the manuscript.
Figure 4: In the legend: shouldn’t the category be “1-LoD” instead of “LoD-1”? As already mentioned, I think it would be favorable to show real vectors instead of categories, which would then also allow to show the displacement-specific LoD values.
Please, see our previous response to the same commentary.
Figure 6: The hillshade could be more low-contrast or so, which would then probably better allow to perceive the lines.
Thanks for this constructive suggestion. We modified the hillshade accordingly.
Figure 7: The categories of elevation differences are partially overlapping and therefore, seem to be wrong, e.g., categories “-4.50 to -3.70” m and “-3.80 to -3.00” m etc.
Thanks for spotting! We modified the categories accordingly.
Table 1: This table could be expanded with values of theoretically achievable precision estimates, which are survey configuration-specific.
We have not found such a type of table together with the "theoretically achievable precision estimates" as an example on relevant publications. Therefore, as previous UAV related publications on ESurf (Clapuyt et al., 2017; Cook and Dietze, 2019; Van Woerkom et al., 2019; Zhang et al., 2019), we only indicated the most relevant UAV surveys parameters.
Table 2: Expand the table by showing both, the RMSEs of GCPs and CPs on the modelled surface as well as the image plane.
We expanded the table with the GCPs and CPs mean and standard deviation errors.
Table 3: Mention the relating confidence interval.
Agreed, we included the confidence limit.
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Citation: https://doi.org/10.5194/esurf-2021-8-AC1
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AC1: 'Reply on RC1', Sebastián Vivero, 12 May 2021
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RC2: 'Comment on esurf-2021-8', Anonymous Referee #2, 06 Apr 2021
Review of the manuscript “Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier” from Vivero et al. Submitted to The Cryosphere earth surface Dynamics.
This paper attempt to show the importance of using sequential UAV-surveys and Structure for Motion photogrammetry workflows for monitoring and quantifying changes in rock glaciers. This study is based on the analysis and comparison of very high-resolution photogrammetric products (i.e. DEMs and orthomosaics) acquired between 2016-2019.
The manuscript has as the main goal to propose the benefits of using UAV surveys through a “rigorous” methodological approach to estimate surface velocities and volume changes over the Tsarmine rock glacier.
Finally, the authors analyze the UAV monitoring strategies as well as the kinematical behavior and surface changes of this rock glacier.
Due to the general arguments and some detailed comments unfortunately I think that there are some major drawbacks in this manuscript that from my point of view could question the acceptance of the manuscript. In addition, even though I am not native English speaker, I think the text requires some corrections. I strongly recommend having the manuscript reviewed by a English native speaker.
General and specific comments are described as follows:
General comments:
SfM methodology
- First, the main contribution of the study is focused on the establishment of a “rigorous methodology” for monitoring rock glaciers using UAV. However, this aspect is crucial because in this study I could not find significant differences (in the methodology) concerning other studies.
- No discussion is presented about the “implementation of this rigorous protocol” methodology. At this point, I wonder, what is the main difference between the traditional UAV surveys and the new one you propose? More details are needed about specific steps on the protocol, e.g. orientation parameters, the quality of the point cloud, and the differences between GCPs and external data.
- Second, you mentioned in the text the implementation of the “co-registration” stage as the main difference between other studies. However, I think there is a misinterpretation of the term “co-registration”. Initially, you speak of multi-temporal co-registration (Figure 2) to the fact of always using the same 4 control points for the aerotriangulation stage. However, co-registration is more related to comparing one product with another, (i.e. master DEM to another, co-registration on SAR images that follows the same principle). The fact that you are always using the 4 points for the aerotriangulation stage is part of the "rigorous protocol", nevertheless, this is not necessarily a co-registration stage. In your case, the co-registration step should be implemented after ortho-images and DEMs generation and with independent references (points, DEMs, etc) that were not included in photogrammetric analysis.
- Then you talk about that the co-registration based on the Helmert methodology you do not find rotations or changes of scale. This issue is obvious since you always used the same 4 points for aerotriangulation. Then, you mention shifts between orthomosaics (computed again using Helmert methodology) but these values are not reported anywhere. Is this important? Or not?
- Later, only the ortho-images were "co-registered" and not the DEMs. In the case of x-y shifts in the ortho-images were important, this also implies strong variations in the elevation changes calculated using the non-coregistered DEMs.
- Finally, you mention that you use small areas to perform this co-registration, however, these areas represent a very small portion of the overall DEMs (which is not presented indeed). The fact of selecting small areas can lead to misinterpretations in the uncertainties.
Surface velocities
- Another methodological question arises on the presentation of rock glacier surface velocities. More details are needed to discuss the validation of the feature tracking products. Also, the current manuscript does not allow the correct interpretation about technical details like grid size, correlation windows size which is fundamental. For example, given the current displacements of Tsarmine rock glacier in the frontal part, adaptable window correlation size are maybe needed. Independent comparisons between products (correlation results) should be mentioned and results should be provided as supplementary material.
- Given the recent importance of these in geosciences, I consider that it is necessary to expand a little more literature on the methodology used in other studies and to be able to propose a new one.
- As showed in Table 1, your latest survey was made early in the morning. This aspect is not even mentioned, we don’t have any idea if the presence of shadows in the morning or light conditions could harm the feature tracking process.
- The fact that you are using very high-resolution data leads to fine changes in image texture and quality. There is no discussion about the influence of using a very high-resolution image to compute surface velocities fields.
Thickness changes
- This study leads with very high-resolution data, therefore the validation of these must be rigorous and independent. Although the manuscript presents a validation step (independent using GPS data), robust statistical analysis is necessary to support these results.
- Additionally, as you are computing differences between many DEMs, uncertainties between those should be presented at least as supplementary material.
Specific comments:
P1L10-11: as details about UAV surveys were not detailed, the “rigorous procedure” is ambiguous and it is no possible to understand why it is rigorous.
P1L19: On the phrase “we almost archived the same accuracy as the GNSS-derived velocities”, numerical comparations should be provided for this comparison.
P1L26-27; The phrase “Rock glacier analogues […] (Cliford et al.,2013)” does not contribute to the discussion of the document and is out of context.
P2L33: the word “top” is too ambiguous. I suggest changing this by “surface”.
P2L37-39: The phrase “The most extending […] Schneider, 2001)” should be revised because it is no clear.
P2L44: Annual surveys derived from what?
P2L62-63: on the sentence “[…] more recently using differential GPS (Berthling et al., 1998”) the reference is too old.
P3L64-68: In this paragraph, you mentioned remote sensing techniques to measure rock glacier displacements and all the references are at the end. However, we do not know which corresponds to which one. I suggest changing this paragraph putting the correct references after each technique.
P3L70: There is no only Kaab that has been working on photogrammetry and rock glacier. For example, you forgot Kaufman publications and one of your Swiss colleagues Michelleti et al 2015, Australian and French colleagues.
P3L80-81: Ok, we are gree that UAVs are changing and improving, but it will affect the way to make photogrammetry? I think this sentence is too ambiguous.
P3L85: What is necessary?
P3L87: the benefits of UAV have been already proved for rock glaciers? Why are you interested in proving these again?
P4L119: Mounty peak instead that “peak monthly”.
P5L127: 58 points is a specific number, it cannot be “around”.
P5128: […] six fixed points […]. In this sentence, you write six? However, on the L127 you mentioned “58 points…” with a number. Please harmonize.
P5L141: Table 2 is mentioned before Table 1.
P5L151: Add focal length units.
P5L152: Add focal length units.
P5L155- L152: The sentence “However […]” is too ambiguous. Poor information is provided about the independent test.
P6L164-165: The sentence “Moreover […] ground […] is repetitive. You already mentioned this on L146. Please check the redundancy.
P7L208: are you sure that the way to present “average density of points” is the correct way? Please verify this.
P8L223: I am confused. On the L210 you said that you generate ortho-mosaics at 0.1 m resolution. But here on the L223, you calculate surface displacements using orthomosaics at “one-tenth of the original pixel size (i.e. 0.01m)” which is not coherent. Please verify.
P8L229: Dis you check the influence of shadows on very high-resolution ortho-mosaics? This aspect is not even mentioned.
P8l234-237: Disagree. Please see my general comment. No detailed information is presented about this issue (i.e. differences in stable areas, x-y shifts, etc.).
P8L240: Again, 69 is a specific number, it cannot be “around”. Also, these 69 “rock surfaces” are not displayed anywhere.
P8L241: x-y-shift translation vectors are not mentioned anywhere. Please provide a detailed description of the specific values obtained from the Helmert similarity.
P9L255: What means ca? Please check this. Moreover, no information on this comparison was presented. Please provide Z differences of these 35 points.
P9L261-262: Uncertainties of DEMs, as well as uncertainties propagated, thought DoD calculation should be shown.
P9L265: how much is this area examination? Please presents values on square meters.
P9L272: Did you measure the displacement of these 35 points? Additionally, these are the same used in section 3.4 (DEM assessment)?
P11L335-339: Disagree. I think this paragraph is too ambiguous because it depends on your goals. Recent developments of satellite photogrammetry (i.e. world-view 2 and 3, Pleiades, etc) showed the high quality of their products even on rock glaciers.
P11L242: Disagree. Again, too ambiguous. The UAV survey can early take more than 30 minutes because it is weather-dependent. In this case. In case the conditions are not optimal, the acquisition time can easily exceed 30 minutes. I suggest changing this part.
P12L344: Disagree. The limits of detection depend on the size of the window used for correlation and it should be tested on fixed areas. Some information about these values is partially reported in Table 3, however, more detailed information needs to be provided.
P12L350-356: This paragraph does not contribute anything to the study. It is maybe a general discussion about “optimal conditions” but this topic is already known.
P12L258-269: Disagree. This paragraph is redundant and a repetition of what the others already do. However, no technical comparisons are given about your protocol against the others (i.e. planning, processing, etc). I suggest revising or excluding this paragraph.
P12L367-369: Ok, you are using stable terrain to validate your products but detailed information about these areas is not presented anywhere. Also, these areas are very small compared to the total extension of your DEMs. Please see my remark on P8l234-237.
P12L375. The fact that you perform all working steps does not guarantee high-quality results. It should be proved by comparing independent methods. Additionally, a detailed report is needed to support this argument. I suggest revising or exclude this paragraph.
P13L404: "[…] net frontal retreats (Fig. 6)" reference is missing.
P14L411: Surface velocities are showed instead of kinematic points. Please change this and also on Figure 9.
P14L428-430. Agree, but what is the contribution of this paragraph to your work? This paragraph takes place at the introduction instead than in the discussion section. Please revise this or exclude this paragraph.
P14L430-432: I could not find an uncertainty analysis. You are relating this to GNSS comparison? The fact that you are using very high-resolution products needs a robust statistical analysis concerning the uncertainties between photogrammetric products notable on stable areas (for DEMs) and surface velocities.
P14L434: What are the differences between your UAV protocol against others? More details are needed to be related to “customizable data acquisition”.
P14L436-437: Agree. With your data, you could explain more extensively this process regarding even into sub-periods.
P15L449-450: Even this works shows a detailed description of UAV surveys on rock glaciers, I difficult to me what’s is the main difference against a normal UAV survey. The current status of the manuscript does not show in detail the relevant differences of SfM photogrammetric studies.
P18L564: the list of references needs revision. The reference Fugazza […] is not cited in the text.
Figures and tables
Figure 1. Panel b: add a north arrow to make clear the image.
Figure 2 Panel b. Disagree with multitemporal co-registration. Please see my remark in general comments.
Figure 4: I think that the community has much more interest to know which are the values of these limits of detection (LoD) instead than only the text. Please show specific values of LoD.
Figure 5. This figure is nice. However, there is not always clear to relate a 3D view to a plane view as shown in Figure 4. I suggest changing the 3D image by a more explicit figure that shows the localization of the longitudinal profile.
Figure 6. It is difficult to see front evolutions because the lines overlay. You said the mean “front line displacements” did you calculate this displacement over the entire line? If yes, precise which method did you use?
Figure 7. These results could be showed better. Is too difficult to interpret this figure because even if the intervals are regular, there is not obvious to see ±0.8. The intervals should be divided by entire numbers (-1.0 - -2.0 as an example) instead of 0.8. Also, on the color scale, you say that you found values greater (less) than +6.8m (-6.8m), I suggest that you present the min and max values as well as the north arrow. Finally, please use a color scale adapted for colorblind people.
Figure 8. On panel a), please indicate the photo was acquired.
Table 1. Please provide the “GSD” acronym.
Table 1. if it is a rigorous protocol, all flights were made between 11h-13h. Why was your last flight in the morning? I found no justification in the text. Please specify this. Did this early flight have any consequences on the velocity calculation? (important presence of shadows).
Table 2. Change “errors” by uncertainties.
Table 2. Why are you expressing uncertainties in pixels? It should be better expressed in meters.
Table 3. Additional statistical analysis is required.
I hope you will find my comments appropriate,
Best regards
Citation: https://doi.org/10.5194/esurf-2021-8-RC2 -
AC2: 'Reply on RC2', Sebastián Vivero, 12 May 2021
We want to thank the anonymous referee for this technical review and comments that will help to improve some aspects of the manuscript. We agree with most of the comments and suggestions made by the anonymous referee. Nevertheless, very similar observations were also raised by the first reviewer, and therefore, already explained in the first author’s response (AR1). Where this is the case, we indicated that similar responses are also in the first author’s response (AR1).
The referee comments are in italic font, and our responses and revisions are in normal font.
Review of the manuscript “Validation and application of sequential unmanned aerial vehicle surveys to monitor the kinematics of a rapid rock glacier” from Vivero et al. Submitted to The Cryosphere earth surface Dynamics.
This paper attempt to show the importance of using sequential UAV-surveys and Structure for Motion photogrammetry workflows for monitoring and quantifying changes in rock glaciers. This study is based on the analysis and comparison of very high-resolution photogrammetric products (i.e. DEMs and orthomosaics) acquired between 2016-2019.
The manuscript has as the main goal to propose the benefits of using UAV surveys through a “rigorous” methodological approach to estimate surface velocities and volume changes over the Tsarmine rock glacier.
Finally, the authors analyse the UAV monitoring strategies as well as the kinematical behavior and surface changes of this rock glacier.
Due to the general arguments and some detailed comments unfortunately I think that there are some major drawbacks in this manuscript that from my point of view could question the acceptance of the manuscript. In addition, even though I am not native English speaker, I think the text requires some corrections. I strongly recommend having the manuscript reviewed by a English native speaker.
Thank you for the overall summary of our work. We will review the English of this manuscript accordingly.
General and specific comments are described as follows:
General comments:
SfM methodology
First, the main contribution of the study is focused on the establishment of a “rigorous methodology” for monitoring rock glaciers using UAV. However, this aspect is crucial because in this study I could not find significant differences (in the methodology) concerning other studies.
We propose UAV surveys as a complementary method to monitor rock glacier kinematics. For achieving this, we exploited the capabilities of the image correlation software CIAS to derived landform-wide kinematic fields from sequential UAV-SfM-derived orthomosaics. A fundamental step before explaining the geomorphological changes was to validate the results via independent ground information during five consecutive periods. The good agreement with data collected by repeated dGNSS demonstrated the robustness and reliability of the monitoring protocol (Figure 3), which similar studies have not demonstrated. Please, see also our similar response to reviewer 1 (AR1).
No discussion is presented about the “implementation of this rigorous protocol” methodology. At this point, I wonder, what is the main difference between the traditional UAV surveys and the new one you propose? More details are needed about specific steps on the protocol, e.g. orientation parameters, the quality of the point cloud, and the differences between GCPs and external data.
We acknowledge that the UAV monitoring concept and validation was not well presented. We changed the emphasis to the evaluation of the UAV-SfM-derived products rather than the SfM processing. In doing so, we included a new section (3.4 Comparison with the TGS) where we better explained the validation protocol. We also expanded the section dealing with the coregistration assessment and added a new table. Please, see also our similar response to reviewer 1 (AR1).
Second, you mentioned in the text the implementation of the “co-registration” stage as the main difference between other studies. However, I think there is a misinterpretation of the term “co-registration”. Initially, you speak of multi-temporal co- registration (Figure 2) to the fact of always using the same 4 control points for the aerotriangulation stage. However, co-registration is more related to comparing one product with another, (i.e. master DEM to another, co-registration on SAR images that follows the same principle). The fact that you are always using the 4 points for the aerotriangulation stage is part of the "rigorous protocol", nevertheless, this is not necessarily a co-registration stage. In your case, the co-registration step should be implemented after ortho-images and DEMs generation and with independent references (points, DEMs, etc) that were not included in photogrammetric analysis.
We agreed that the term co-registration was incorrectly assigned to the four multitemporal GCP. We have changed accordingly and corrected the caption in Figure 2.
The GCPs and CPs are used to determine the absolute accuracy of the UAV-SfM-derived products. However, the relative accuracy was evaluated for each orthomosaic pair using a Helmert similarity transform based on 69 points sampled on stable terrain features without significant vegetation. In doing this, we assessed both the coregistration and image matching accuracies. See our similar response to review 1 (AR1).
Then you talk about that the co-registration based on the Helmert methodology you do not find rotations or changes of scale. This issue is obvious since you always used the same 4 points for aerotriangulation. Then, you mention shifts between orthomosaics (computed again using Helmert methodology) but these values are not reported anywhere. Is this important? Or not?
The mention of the lack of rotation or scale differences among the sequential orthomosaics may sound trivial, but we include it as initial quality control. Additional details are included on the new Table and supplementary material.
Later, only the ortho-images were "co-registered" and not the DEMs. In the case of x-y shifts in the ortho-images were important, this also implies strong variations in the elevation changes calculated using the non-coregistered DEMs.
We thank the reviewer for this comment, but we did not observe such “strong variations in the elevation changes” caused by the subpixel x-y-shifts. Therefore, we evaluated the uncertainty of each DEM according to their absolute accuracy (35 points), and we propagated the errors during the DoD analysis following Wheaton et al. (2010). We included these results in the supplementary material.
Finally, you mention that you use small areas to perform this co-registration, however, these areas represent a very small portion of the overall DEMs (which is not presented indeed). The fact of selecting small areas can lead to misinterpretations in the uncertainties.
The co-registration was performed on 69 points distributed on well-evaluated areas (see Kummert and Delaloye, 2018) and without significant vegetation (as the NCC misses the coherence on this kind of surfaces). This selection was not trivial, as we have detected some landslide activity in the vicinity (see Barboux et al., 2014). Still, the “small areas” represent about 1/4 of the study area (Tsarmine rock glacier) and are distributed on five disconnected regions. We are not aware of this level of assessment of the stable regions at this high resolution by similar studies.
Surface velocities
Another methodological question arises on the presentation of rock glacier surface velocities. More details are needed to discuss the validation of the feature tracking products. Also, the current manuscript does not allow the correct interpretation about technical details like grid size, correlation windows size which is fundamental. For example, given the current displacements of Tsarmine rock glacier in the frontal part, adaptable window correlation size are maybe needed. Independent comparisons between products (correlation results) should be mentioned and results should be provided as supplementary material.
The decision to use a particular combination of reference and search window sizes was pragmatic because the expected maximum displacement can be estimated beforehand from the visual inspection of sequential orthomosaics. In this regard, keeping the exact configuration of the search and window sizes provided only a theoretical maximum displacement limit of about 13 m (more than twice the maximum value observed) for each pair of consecutive orthomosaics.
We included a new section (3.4 Comparison with the TGS) to explain the validation protocol better. We also expanded the section dealing with the coregistration assessment and added a new table. Please, see our similar response to reviewer 1 (AR1).
Given the recent importance of these in geosciences, I consider that it is necessary to expand a little more literature on the methodology used in other studies and to be able to propose a new one.
We expanded the references.
As showed in Table 1, your latest survey was made early in the morning. This aspect is not even mentioned, we don’t have any idea if the presence of shadows in the morning or light conditions could harm the feature tracking process.
We thank the reviewer for pointing on this valid concern; however, It is well known that the normalised cross-correlation (NCC) can account for the differences in contrast and brightness (see Heid and Kääb, 2012). We included this explanation.
The fact that you are using very high-resolution data leads to fine changes in image texture and quality. There is no discussion about the influence of using a very high- resolution image to compute surface velocities fields.
Agreed, we have put more emphasis on the very high-resolution datasets.
Thickness changes
This study leads with very high-resolution data, therefore the validation of these must be rigorous and independent. Although the manuscript presents a validation step (independent using GPS data), robust statistical analysis is necessary to support these results.
Additional details are included in the new supplementary material (DEM assessment).
Additionally, as you are computing differences between many DEMs, uncertainties between those should be presented at least as supplementary material.
Agreed, we included additional details in the new supplementary material (DEM assessment).
Specific comments:
P1L10-11: as details about UAV surveys were not detailed, the “rigorous procedure” is ambiguous and it is no possible to understand why it is rigorous.
Agreed, we removed “rigorous” from the abstract.
P1L19: On the phrase “we almost archived the same accuracy as the GNSS-derived velocities”, numerical comparations should be provided for this comparison.
Changed to: “We achieved uncertainties down to 0.08 m using the adequate UAV survey acquisition, processing and validation steps.”
P1L26-27; The phrase “Rock glacier analogues […] (Cliford et al.,2013)” does not contribute to the discussion of the document and is out of context.
Agreed, we remove this sentence from our manuscript.
P2L33: the word “top” is too ambiguous. I suggest changing this by “surface”.
Changed to “surface”.
P2L37-39: The phrase “The most extending […] Schneider, 2001)” should be revised
because it is no clear.
Changed to “One of the first monitoring efforts goes back to the summer of 1938 at the outer Hochebenkar in the Ötztal Alps of Western Austria”.
P2L44: Annual surveys derived from what?
Annual surveys derived “from in-situ measurements”.
P2L62-63: on the sentence “[…] more recently using differential GPS (Berthling et al., 1998”) the reference is too old.
We removed “and more recently using”.
P3L64-68: In this paragraph, you mentioned remote sensing techniques to measure rock glacier displacements and all the references are at the end. However, we do not know which corresponds to which one. I suggest changing this paragraph putting the correct references after each technique.
Changed.
P3L70: There is no only Kaab that has been working on photogrammetry and rock glacier. For example, you forgot Kaufman publications and one of your Swiss colleagues Michelleti et al 2015, Australian and French colleagues.
Andreas Kääb did a lot of work in this field, and in our view, he produced some of the most inspiring articles dealing with photogrammetry applications on rock glaciers. Furthermore, we are employing the CIAS software which he developed. We expanded, however, the list of authors. Also, we are not aware of the“Australian colleagues” working on photogrammetry and rock glacier.
P3L80-81: Ok, we are gree that UAVs are changing and improving, but it will affect the way to make photogrammetry? I think this sentence is too ambiguous.
We have changed the sentence: “how rock glacier kinematics and geomorphic changes are evaluated still presents a challenge, and there is still scope for the assessment of monitoring protocols using different UAV configurations high altitude and challenging terrain”.
P3L85: What is necessary?
We modified this sentence to: “In the context of rapid rock glacier acceleration, a robust validation of the increasing velocities from particular remote sensing techniques is necessary”.
P3L87: the benefits of UAV have been already proved for rock glaciers? Why are you
interested in proving these again?
Previous research has partly described these benefits, but as we had argued, a destabilised rock glacier entails a specific UAV monitoring strategy and particular analyses. Topics such as substantial velocity variations, scarp development and frontal erosion processes have been described and discussed in the present manuscript. See our similar responses to reviewer 1 (AR1).
P4L119: Mounty peak instead that “peak monthly”.
Changed.
P5L127: 58 points is a specific number, it cannot be “around”.
Corrected.
P5128: […] six fixed points […]. In this sentence, you write six? However, on the L127 you mentioned “58 points…” with a number. Please harmonise.
According to the “house standards” in ESurf: “For items other than units of time or measure, use words for cardinal numbers less than 10; use numerals for 10 and above (e.g. three flasks, seven trees, 6 m, 9 d, 10 desks). Therefore, we have to follow the “house standards”.
P5L141: Table 2 is mentioned before Table 1.
Revised.
P5L151: Add focal length units.
Added.
P5L152: Add focal length units.
Added.
P5L155- L152: The sentence “However […]” is too ambiguous. Poor information is provided about the independent test.
Clarified.
P6L164-165: The sentence “Moreover […] ground […] is repetitive. You already mentioned this on L146. Please check the redundancy.
Thanks for point this redundancy issue. We modified this sentence.
P7L208: are you sure that the way to present “average density of points” is the correct way? Please verify this.
Density is usually quantified as a quantity per unit of volume (pts m-3). We will verify this with the Copernicus typesetting and language copy-editing services.
P8L223: I am confused. On the L210 you said that you generate ortho-mosaics at 0.1 m resolution. But here on the L223, you calculate surface displacements using orthomosaics at “one-tenth of the original pixel size (i.e. 0.01m)” which is not coherent. Please verify.
We added the following sentence: “To achieve displacements at sub-pixel precisions (Debella-Gilo and Kääb, 2011) the original orthomosaics were resampled to one-tenth of the original pixel size (i.e. 0.01 m).”
P8L229: Dis you check the influence of shadows on very high-resolution ortho-mosaics? This aspect is not even mentioned.
The investigated area inside the orthomosaics is normally free from deep shadows caused by high mountain relief. Therefore, we did not observe such influence in the CIAS results. We included this explanation.
P8l234-237: Disagree. Please see my general comment. No detailed information is presented about this issue (i.e. differences in stable areas, x-y shifts, etc.).
Please, see our previous response to this comment.
P8L240: Again, 69 is a specific number, it cannot be “around”. Also, these 69 “rock surfaces” are not displayed anywhere.
We removed “around”. Please, see our response to reviewer 1 (AR1).
P8L241: x-y-shift translation vectors are not mentioned anywhere. Please provide a detailed description of the specific values obtained from the Helmert similarity.
The x-y-shift translation vectors are included in a new supplementary material (Table) related to this manuscript.
P9L255: What means ca? Please check this. Moreover, no information on this comparison was presented. Please provide Z differences of these 35 points.
We removed “ca”. Also, the Z differences of these 35 points are included in a new supplementary material (Table) related to this manuscript.
P9L261-262: Uncertainties of DEMs, as well as uncertainties propagated, thought DoD calculation should be shown.
We included the DEM evaluation in a new supplementary material (Table) related to this manuscript. As the DoD calculation is not the main facet in our contribution, we refer to the original work of Wheaton et al. (2010) for further details.
P9L265: how much is this area examination? Please presents values on square meters.
Added. 50 064 m2.
P9L272: Did you measure the displacement of these 35 points? Additionally, these are the same used in section 3.4 (DEM assessment)?
Yes, they are the same. We made this more evident.
P11L335-339: Disagree. I think this paragraph is too ambiguous because it depends on your goals. Recent developments of satellite photogrammetry (i.e. world-view 2 and 3, Pleiades, etc) showed the high quality of their products even on rock glaciers.
In the framework of remote sensing approaches, our sentence makes a discussion about platform operation between classical aerial surveys or satellite programs (notably companies) and new UAV surveys (primarily researchers). We argued that UAV devices could help to close the gap between expensive commercial providers and small research initiatives (Eltner et al., 2016). We improved the paragraph accordingly.
P11L242: Disagree. Again, too ambiguous. The UAV survey can early take more than 30 minutes because it is weather-dependent. In this case. In case the conditions are not optimal, the acquisition time can easily exceed 30 minutes. I suggest changing this part.
To our experience, the typical UAV setup and pre-flight checks take less than 5 minutes. Since the geodetic measurements are fixed and already provided, this step is not needed for subsequent UAV surveys. In any case, we now indicated that the actual data capture from the first to the last images usually takes no more than 30 minutes (for the size of Tsarmine rock glacier), which is considerably less time than the regular GNSS data capture. Please, check Table 1, where the individual UAV survey times are indicated.
P12L344: Disagree. The limits of detection depend on the size of the window used for correlation and it should be tested on fixed areas. Some information about these values is partially reported in Table 3, however, more detailed information needs to be provided.
We improved the evaluation of sequential orthomosaics in stable areas and included the results in a new table. We also indicated that the estimated LoD takes into account the orthorectification and NCC uncertainties.
P12L350-356: This paragraph does not contribute anything to the study. It is maybe a general discussion about “optimal conditions” but this topic is already known.
Thanks for point out this. We included more precise details about the pros and cons. We made clear that the investigated area size, weather conditions and specific UAV regulations are all potential limiting factors for our study area.
P12L258-269: Disagree. This paragraph is redundant and a repetition of what the others already do. However, no technical comparisons are given about your protocol against the others (i.e. planning, processing, etc). I suggest revising or excluding this paragraph.
We agree that this section needs revision. However, from previous studies, we highlighted two main protocols issues that we have accounted for in the present contribution. The assessment of the stable areas (uncertainty estimation) and surface velocity validation by independent GNSS data were explained for five consecutive periods. We have indicated the most relevant survey and processing details, particularly in sections 2 and 3. Additional details are included on the new supplementary material (UAV surveys settings, DEM assessment and Helmert results).
P12L367-369: Ok, you are using stable terrain to validate your products but detailed information about these areas is not presented anywhere. Also, these areas are very small compared to the total extension of your DEMs. Please see my remark on P8l234-237.
Please see our previous comments about the stable terrain.
P12L375. The fact that you perform all working steps does not guarantee high-quality results. It should be proved by comparing independent methods. Additionally, a detailed report is needed to support this argument. I suggest revising or exclude this paragraph.
Agreed, we removed this sentence.
P13L404: "[…] net frontal retreats (Fig. 6)" reference is missing.
We added new references (Kääb and Reichmuth, 2005; Kummert et al., 2018).
P14L411: Surface velocities are showed instead of kinematic points. Please change this and also on Figure 9.
Changed “kinematic points” to “velocities values derived from…”
P14L428-430. Agree, but what is the contribution of this paragraph to your work? This paragraph takes place at the introduction instead than in the discussion section. Please revise this or exclude this paragraph.
We excluded this sentence.
P14L430-432: I could not find an uncertainty analysis. You are relating this to GNSS comparison? The fact that you are using very high-resolution products needs a robust statistical analysis concerning the uncertainties between photogrammetric products notable on stable areas (for DEMs) and surface velocities.
Changed to “The quality of the high-resolution UAV-derived datasets leads us to stress that regular and spatially distributed surface velocity measurements would permit landform-wide kinematics to be better monitored.”
P14L434: What are the differences between your UAV protocol against others? More details are needed to be related to “customisable data acquisition”.
Our protocol is tested and validated on a rock glacier during a destabilised period. See our similar responses to reviewer 1 (AR1).
P14L436-437: Agree. With your data, you could explain more extensively this process regarding even into sub-periods.
Thanks for acknowledging this. We included this in the new supplementary material.
P15L449-450: Even this works shows a detailed description of UAV surveys on rock glaciers, I difficult to me what’s is the main difference against a normal UAV survey. The current status of the manuscript does not show in detail the relevant differences of SfM photogrammetric studies.
We showed a detailed description of a destabilised rock glacier with a suitable UAV monitoring strategy. We changed the sentence: “This work detailed the use of UAV surveys to monitor rapid kinematic and geomorphological changes on destabilised rock glacier with enhanced temporal and spatial details.” Please, see our similar responses to reviewer 1 (AR1).
P18L564: the list of references needs revision. The reference Fugazza […] is not cited in the text.
Thanks for spotting! We added this reference to the manuscript.
Figures and tables
Figure 1. Panel b: add a north arrow to make clear the image.
Added
Figure 2 Panel b. Disagree with multitemporal co-registration. Please see my remark in general comments.
Changed to “Sequential SfM processing using four permanent GCP outside the rock glacier.”
Figure 4: I think that the community has much more interest to know which are the values of these limits of detection (LoD) instead than only the text. Please show specific values of LoD.
Agreed. Information about the mean LoD is indicated on each panel. Information about the LoD for each period is shown in Table 3.
Figure 5. This figure is nice. However, there is not always clear to relate a 3D view to a plane view as shown in Figure 4. I suggest changing the 3D image by a more explicit figure that shows the localisation of the longitudinal profile.
Thank you for the feedback. We included the localisation of the profile in Figure 1.
Figure 6. It is difficult to see front evolutions because the lines overlay. You said the mean “front line displacements” did you calculate this displacement over the entire line? If yes, precise which method did you use?
As suggested by the first reviewer, we modified the hillshade of this figure. We indicated the method on the figure caption.
Figure 7. These results could be showed better. Is too difficult to interpret this figure because even if the intervals are regular, there is not obvious to see ±0.8. The intervals should be divided by entire numbers (-1.0 - -2.0 as an example) instead of 0.8. Also, on the color scale, you say that you found values greater (less) than +6.8m (-6.8m), I suggest that you present the min and max values as well as the north arrow. Finally, please use a color scale adapted for colorblind people.
Thanks for the suggestions to improve our figure. As suggested by the first reviewer, we modified the categories accordingly and added the north arrow. Regarding the colour scale and the min/max values, we have followed the journal style for the representation of similar results. Please, see the relevant figures published recently on ESurf (Ulrich et al., 2021; Van Woerkom et al., 2019).
Figure 8. On panel a), please indicate the photo was acquired.
Agreed. Photograph acquired during the same day of the UAV survey (24 September 2019).
Table 1. Please provide the “GSD” acronym.
Thanks. We included “ground sample distance (GSD)” directly in the text.
Table 1. if it is a rigorous protocol, all flights were made between 11h-13h. Why was your last flight in the morning? I found no justification in the text. Please specify this. Did this early flight have any consequences on the velocity calculation? (important presence of shadows).
The UAV flight is typically performed simultaneously as the TGS or vice versa, but we must adjust the survey accordingly due to weather and personnel constraints. Please, see our previous response about the influence of “shadows”.
Table 2. Change “errors” by uncertainties.
We retain “errors” as this is the case for this type of statistics.
Table 2. Why are you expressing uncertainties in pixels? It should be better expressed in meters.
Changed to “meters.”
Table 3. Additional statistical analysis is required.
Thanks for this suggestion. However, we are not aware of such “additional statistical analysis” for this kind of data. We included the LoD values for the GNSS technique.
REFERENCES
Barboux, C., Delaloye, R. and Lambiel, C.: Inventorying slope movements in an Alpine environment using DInSAR, Earth Surf. Process. Landforms, 39(15), 2087–2099, doi:10.1002/esp.3603, 2014.
Debella-Gilo, M. and Kääb, A.: Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation, Remote Sens. Environ., 115(1), 130–142, doi:10.1016/j.rse.2010.08.012, 2011.
Eltner, A., Kaiser, A., Castillo, C., Rock, G., Neugirg, F. and Abellán, A.: Image-based surface reconstruction in geomorphometry-merits, limits and developments, Earth Surf. Dyn., 4(2), 359–389, doi:10.5194/esurf-4-359-2016, 2016.
Heid, T. and Kääb, A.: Evaluation of existing image matching methods for deriving glacier surface displacements globally from optical satellite imagery, Remote Sens. Environ., 118, 339–355, doi:10.1016/j.rse.2011.11.024, 2012.
Kääb, A. and Reichmuth, T.: Advance mechanisms of rock glaciers, Permafr. Periglac. Process., 16(2), 187–193, doi:10.1002/ppp.507, 2005.
Kummert, M. and Delaloye, R.: Mapping and quantifying sediment transfer between the front of rapidly moving rock glaciers and torrential gullies, Geomorphology, 309, 60–76, doi:10.1016/j.geomorph.2018.02.021, 2018.
Kummert, M., Delaloye, R. and Braillard, L.: Erosion and sediment transfer processes at the front of rapidly moving rock glaciers: Systematic observations with automatic cameras in the western Swiss Alps, Permafr. Periglac. Process., 29(1), 21–33, doi:10.1002/ppp.1960, 2018.
Ulrich, V., Williams, J. G., Zahs, V., Anders, K., Hecht, S. and Höfle, B.: Measurement of rock glacier surface change over different timescales using terrestrial laser scanning point clouds, Earth Surf. Dyn., 9(1), 19–28, doi:10.5194/esurf-9-19-2021, 2021.
Wheaton, J. M., Brasington, J., Darby, S. E. and Sear, D. A.: Accounting for uncertainty in DEMs from repeat topographic surveys: Improved sediment budgets, Earth Surf. Process. Landforms, 35(2), 136–156, doi:10.1002/esp.1886, 2010.
Van Woerkom, T., Steiner, J. F., Kraaijenbrink, P. D. A., Miles, E. S. and Immerzeel, W. W.: Sediment supply from lateral moraines to a debris-covered glacier in the Himalaya, Earth Surf. Dyn., 7(2), 411–427, doi:10.5194/esurf-7-411-2019, 2019.
Citation: https://doi.org/10.5194/esurf-2021-8-AC2
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Sebastián Vivero
Reynald Delaloye
Christophe Lambiel
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