Articles | Volume 12, issue 5
https://doi.org/10.5194/esurf-12-1121-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-12-1121-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Oct 2024
Research article |
| 01 Oct 2024
| 01 Oct 2024
Tracking slow-moving landslides with PlanetScope data: new perspectives on the satellite's perspective
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24–25, 14476 Potsdam-Golm, Germany
Bodo Bookhagen
Institute of Geosciences, University of Potsdam, Karl-Liebknecht-Str. 24–25, 14476 Potsdam-Golm, Germany
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Cited articles
Aati, S. and Avouac, J.-P.: Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery, Remote Sensing, 12, 3418, https://doi.org/10.3390/rs12203418, 2020. a, b
Aati, S., Avouac, J.-P., Rupnik, E., and Deseilligny, M.-P.: Potential and Limitation of PlanetScope Images for 2-D and 3-D Earth Surface Monitoring With Example of Applications to Glaciers and Earthquakes, IEEE T. Geosci. Remote, 60, 1–19, https://doi.org/10.1109/TGRS.2022.3215821, 2022a. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Aati, S., Milliner, C., and Avouac, J.-P.: A new approach for 2-D and 3-D precise measurements of ground deformation from optimized registration and correlation of optical images and ICA-based filtering of image geometry artifacts, Remote Sens. Environ., 277, 113038, https://doi.org/10.1016/j.rse.2022.113038, 2022b. a
Amici, L., Yordanov, V., Oxoli, D., Truong, X. Q., and Brovelli, M. A.: MONITORING LANDSLIDE DISPLACEMENTS THROUGH MAXIMUM CROSS-CORRELATION OF SATELLITE IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 27–34, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-27-2022, 2022. a
Andreuttiova, L., Hollingsworth, J., Vermeesch, P., Mitchell, T. M., and Bergman, E.: Revisiting the 1959 Hebgen Lake Earthquake Using Optical Image Correlation; New Constraints on Near-Field 3D Ground Displacement, Geophys. Res. Lett., 49, e2022GL098666, https://doi.org/10.1029/2022GL098666, 2022. a
Beyer, R., Alexandrov, O., ScottMcMichael, Broxton, M., Lundy, M., Husmann, K., Edwards, L., Nefian, A., SmithB, Shean, D., Smith, T., mstyer, Annex, A., Moratto, Z., harguess, Aravkin, A., Meyer, J., PicoJr, Bhushan, S., and jlaura: NeoGeographyToolkit/StereoPipeline 3.1.0, Zenodo [software], https://doi.org/10.5281/zenodo.6562267, 2022. a
Beyer, R. A., Alexandrov, O., and McMichael, S.: The Ames Stereo Pipeline: NASA’s open source software for deriving and processing terrain data, Earth and Space Science, 5, 537–548, https://doi.org/10.1029/2018EA000409, 2018. a, b, c, d
Bookhagen, B. and Strecker, M. R.: Spatiotemporal trends in erosion rates across a pronounced rainfall gradient: Examples from the southern Central Andes, Earth Planet. Sc. Lett., 327–328, 97–110, https://doi.org/10.1016/j.epsl.2012.02.005, 2012. a
Castino, F., Bookhagen, B., and Strecker, M. R.: Rainfall variability and trends of the past six decades (1950–2014) in the subtropical NW Argentine Andes, Clim. Dynam., 48, 1049–1067, https://doi.org/10.1007/s00382-016-3127-2, 2017. a
Chudley, T. R., Howat, I. M., Yadav, B., and Noh, M.-J.: Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers, The Cryosphere, 16, 2629–2642, https://doi.org/10.5194/tc-16-2629-2022, 2022. a
Crameri, F., Shephard, G., and Heron, P.: The misuse of colour in science communication, Nat. Commun., 11, 5444, https://doi.org/10.1038/s41467-020-19160-7, 2020. a
d’Angelo, P. and Reinartz, P.: DIGITAL ELEVATION MODELS FROM STEREO, VIDEO AND MULTI-VIEW IMAGERY CAPTURED BY SMALL SATELLITES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 77–82, https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-77-2021, 2021. a
Dille, A., Kervyn, F., Handwerger, A. L., d'Oreye, N., Derauw, D., Mugaruka Bibentyo, T., Samsonov, S., Malet, J.-P., Kervyn, M., and Dewitte, O.: When image correlation is needed: Unravelling the complex dynamics of a slow-moving landslide in the tropics with dense radar and optical time series, Remote Sens. Environ., 258, 112402, https://doi.org/10.1016/j.rse.2021.112402, 2021. a, b, c
European Space Agency, S.: Copernicus Global Digital Elevation Model, OpenTopography [data set], https://doi.org/10.5069/G9028PQB, 2021. a
Facciolo, G., Franchis, C. D., and Meinhardt, E.: MGM: A Significantly More Global Matching for Stereovision, in: BMVC 2015, edited by: Press, B., Swansea, United Kingdom, https://bmva-archive.org.uk/bmvc/2015/papers/paper090/paper090.pdf (last access: 24 September 2024), 2015. a
Feng, Z., Feng, G., Chen, H., Xu, W., Li, Z., He, L., and Ren, Z.: A Block Ramp Errors Correction Method of Planet Subpixel Offset: Application to the 2018 Mw 7.5 Palu Earthquake, Indonesia, IEEE Access, 7, 174924–174931, https://doi.org/10.1109/ACCESS.2019.2956198, 2019. a, b, c
Figueroa, S., Weiss, J. R., Hongn, F., Pingel, H., Escalante, L., Elías, L., Aranda-Viana, R. G., and Strecker, M. R.: Late Pleistocene to Recent Deformation in the Thick-Skinned Fold-and-Thrust Belt of Northwestern Argentina (Central Calchaquí Valley, 26° S), Tectonics, 40, e2020TC006394, https://doi.org/10.1029/2020TC006394, 2021. a
Frazier, A. E. and Hemingway, B. L.: A Technical Review of Planet Smallsat Data: Practical Considerations for Processing and Using PlanetScope Imagery, Remote Sensing, 13, 3930, https://doi.org/10.3390/rs13193930, 2021. a
Gardner, A. S., Moholdt, G., Scambos, T., Fahnstock, M., Ligtenberg, S., van den Broeke, M., and Nilsson, J.: Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years, The Cryosphere, 12, 521–547, https://doi.org/10.5194/tc-12-521-2018, 2018. a, b
Ghuffar, S.: DEM Generation from Multi Satellite PlanetScope Imagery, Remote Sensing, 10, 1462, https://doi.org/10.3390/rs10091462, 2018. a
Graber, A., Santi, P., and Meza, P.: Constraining the critical groundwater conditions for initiation of large, irrigation-induced landslides, Siguas River Valley, Peru, Landslides, 18, 3753–3767, https://doi.org/10.1007/s10346-021-01767-6, 2021. a, b, c
Grodecki, J. and Dial, G.: Block Adjustment of High-Resolution Satellite Images Described by Rational Polynomials, Photogram. Eng. Rem. S., 69, 59–68, https://doi.org/10.14358/PERS.69.1.59, 2003. a
Handwerger, A., Huang, M.-H., Fielding, E., Booth, A., and Burgmann, R.: A shift from drought to extreme rainfall drives a stable landslide to catastrophic failure, Sci. Rep., 9, 1569, https://doi.org/10.1038/s41598-018-38300-0, 2019. a
Handwerger, A. L., Roering, J. J., and Schmidt, D. A.: Controls on the seasonal deformation of slow-moving landslides, Earth Planet. Sc. Lett., 377–378, 239–247, https://doi.org/10.1016/j.epsl.2013.06.047, 2013. a
Handwerger, A. L., Fielding, E. J., Sangha, S. S., and Bekaert, D. P. S.: Landslide Sensitivity and Response to Precipitation Changes in Wet and Dry Climates, Geophys. Res. Lett., 49, e2022GL099499, https://doi.org/10.1029/2022GL099499, 2022. a
Hermanns, R., Valderrama Murillo, P., Fauqué, L., Penna, I., Sepúlveda, S., Moreiras, S., and Zavala, B.: Landslides in the Andes and the need to communicate on an interandean level on landslide mapping and research, Revista de la Asociacion Geologica Argentina, 69, 321–327, https://revista.geologica.org.ar/raga/article/view/518 (last access: 24 September 2024), 2012. a, b, c
Hermle, D., Keuschnig, M., Hartmeyer, I., Delleske, R., and Krautblatter, M.: Timely prediction potential of landslide early warning systems with multispectral remote sensing: a conceptual approach tested in the Sattelkar, Austria, Nat. Hazards Earth Syst. Sci., 21, 2753–2772, https://doi.org/10.5194/nhess-21-2753-2021, 2021. a
Hilley, G. E., Bürgmann, R., Ferretti, A., Novali, F., and Rocca, F.: Dynamics of Slow-Moving Landslides from Permanent Scatterer Analysis, Science, 304, 1952–1955, https://doi.org/10.1126/science.1098821, 2004. a
Hirt, C.: Artefact detection in global digital elevation models (DEMs): The Maximum Slope Approach and its application for complete screening of the SRTM v4.1 and MERIT DEMs, Remote Sens. Environ., 207, 27–41, https://doi.org/10.1016/j.rse.2017.12.037, 2018. a
Huang, D., Tang, Y., and Qin, R.: An evaluation of PlanetScope images for 3D reconstruction and change detection – experimental validations with case studies, GISci. Remote Sens., 59, 744–761, https://doi.org/10.1080/15481603.2022.2060595, 2022. a
Kääb, A., Altena, B., and Mascaro, J.: River-ice and water velocities using the Planet optical cubesat constellation, Hydrol. Earth Syst. Sci., 23, 4233–4247, https://doi.org/10.5194/hess-23-4233-2019, 2019. a
Keefer, D.: Investigating Landslides Caused by Earthquakes – A Historical Review, Surv. Geophys., 23, 473–510, https://doi.org/10.1023/A:1021274710840, 2002. a
Kääb, A., Winsvold, S. H., Altena, B., Nuth, C., Nagler, T., and Wuite, J.: Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity, Remote Sensing, 8, 598, https://doi.org/10.3390/rs8070598, 2016. a, b
Lacroix, P., Berthier, E., and Maquerhua, E. T.: Earthquake-driven acceleration of slow-moving landslides in the Colca valley, Peru, detected from Pléiades images, Remote Sens. Environ., 165, 148–158, https://doi.org/10.1016/j.rse.2015.05.010, 2015. a
Lacroix, P., Dehecq, A., and Taipe, E.: Irrigation-triggered landslides in a Peruvian desert caused by modern intensive farming, Nat. Geosci., 13, 1–5, https://doi.org/10.1038/s41561-019-0500-x, 2020a. a, b, c
Lacroix, P., Handwerger, A., and Bièvre, G.: Life and death of slow-moving landslides, Nat. Rev. Earth Environ., 1, 404–419, https://doi.org/10.1038/s43017-020-0072-8, 2020b. a
Lacroix, P., Huanca, J., Albinez, L., and Taipe, E.: Precursory Motion and Time-Of-Failure Prediction of the Achoma Landslide, Peru, From High Frequency PlanetScope Satellites, Geophys. Res. Lett., 50, e2023GL105413, https://doi.org/10.1029/2023GL105413, 2023. a, b, c, d
Lei, Y., Gardner, A., and Agram, P.: Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement, Remote Sensing, 13, 749, https://doi.org/10.3390/rs13040749, 2021. a, b
Leprince, S., Ayoub, F., Klinger, Y., and Avouac, J.-P.: Co-Registration of Optically Sensed Images and Correlation (COSI-Corr): an operational methodology for ground deformation measurements, in: 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain, 23–28 July 2007, 1943–1946, https://doi.org/10.1109/IGARSS.2007.4423207, 2007. a, b
Mansour, M., Morgenstern, N., and Martin, D.: Expected damage from displacement of slow-moving slides, Landslides, 8, 117–131, https://doi.org/10.1007/s10346-010-0227-7, 2011. a
Mazzanti, P., Caporossi, P., and Muzi, R.: Sliding Time Master Digital Image Correlation Analyses of CubeSat Images for landslide Monitoring: The Rattlesnake Hills Landslide (USA), Remote Sensing, 12, 592, https://doi.org/10.3390/rs12040592, 2020. a
Mehrparvar, A., Pignatelli, D., Carnahan, J., Munakat, R., Lan, W., Toorian, A., Hutputanasin, A., and Lee, S.: Cubesat design specification rev. 13, The CubeSat Program, Cal Poly San Luis Obispo, US, 1, https://static1.squarespace.com/static/5418c831e4b0fa4ecac1bacd/t/56e9b62337013b6c063a655a/1458157095454/cds_rev13_final2.pdf (last access: 1 May 2023), 2014. a
Milliner, C., Sammis, C., Allam, A., Dolan, J., Hollingsworth, J., Leprince, S., and Ayoub, F.: Resolving Fine-Scale Heterogeneity of Co-seismic Slip and the Relation to Fault Structure, Sci. Rep., 6, 27201, https://doi.org/10.1038/srep27201, 2016. a
Mueting, A. and Bookhagen, B.: UP-RS-ESP/PlanetScope_landslide_tracking: Initial Release (v0.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.13826198, 2024. a, b, c
Mueting, A., Bookhagen, B., and Strecker, M. R.: Identification of Debris-Flow Channels Using High-Resolution Topographic Data: A Case Study in the Quebrada del Toro, NW Argentina, J. Geophys. Res.-Earth, 126, e2021JF006330, https://doi.org/10.1029/2021JF006330, 2021. a
Muhammad, M., Williams-Jones, G., Stead, D., Tortini, R., Falorni, G., and Donati, D.: Applications of Image-Based Computer Vision for Remote Surveillance of Slope Instability, Front. Earth Sci., 10, 909078, https://doi.org/10.3389/feart.2022.909078, 2022. a, b
NASA JPL: NASADEM Merged DEM Global 1 arc second V001, OpenTopography [data set], https://doi.org/10.5069/G93T9FD9, 2021. a, b
Nuth, C. and Kääb, A.: Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change, The Cryosphere, 5, 271–290, https://doi.org/10.5194/tc-5-271-2011, 2011. a
Planet: What does the “ground_control” field in the metadata signify?, https://support.planet.com/hc/en-us/articles/360016420313-What-does-the-ground-control-field-in-the-metadata-signify- (last access: 1 May 2023), 2019. a
Planet Team: Planet Application Program Interface: In Space for Life on Earth, San Francisco, CA, https://api.planet.com (last access: 1 May 2023), 2022. a
Purinton, B. and Bookhagen, B.: Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau, Earth Surf. Dynam., 5, 211–237, https://doi.org/10.5194/esurf-5-211-2017, 2017. a
Purinton, B. and Bookhagen, B.: Measuring decadal vertical land-level changes from SRTM-C (2000) and TanDEM-X (∼ 2015) in the south-central Andes, Earth Surf. Dynam., 6, 971–987, https://doi.org/10.5194/esurf-6-971-2018, 2018. a, b
Purinton, B. and Bookhagen, B.: Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes, Front. Earth Sci., 9, 758606, https://doi.org/10.3389/feart.2021.758606, 2021. a, b
Purinton, B., Mueting, A., and Bookhagen, B.: Image Texture as Quality Indicator for Optical DEM Generation: Geomorphic Applications in the Arid Central Andes, Remote Sensing, 15, 85, https://doi.org/10.3390/rs15010085, 2023. a, b
Rupnik, E., Daakir, M., and Deseilligny, M.: MicMac – a free, open-source solution for photogrammetry, Open Geospatial Data, Software and Standards, 2, 1–9, https://doi.org/10.1186/s40965-017-0027-2, 2017. a
Savi, S., Schildgen, T. F., Tofelde, S., Wittmann, H., Scherler, D., Mey, J., Alonso, R. N., and Strecker, M. R.: Climatic controls on debris-flow activity and sediment aggradation: The Del Medio fan, NW Argentina, J. Geophys. Res.-Earth, 121, 2424–2445, https://doi.org/10.1002/2016JF003912, 2016. a, b, c
Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., and Morin, P.: An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery, ISPRS J. Photogramm., 116, 101–117, https://doi.org/10.1016/j.isprsjprs.2016.03.012, 2016. a, b
Socquet, A., Hollingsworth, J., Pathier, E., and Bouchon, M.: Evidence of supershear during the 2018 magnitude 7.5 Palu earthquake from space geodesy, Nat. Geosci., 12, 192–199, https://doi.org/10.1038/s41561-018-0296-0, 2019. a
Strecker, M. R., Alonso, R. N., Bookhagen, B., Carrapa, B., Hilley, G. E., Sobel, E. R., and Trauth, M. H.: Tectonics and climate of the southern central Andes, Annu. Rev. Earth Pl. Sc., 35, 747–787, https://doi.org/10.1146/annurev.earth.35.031306.140158, 2007. a
Stumpf, A., Malet, J.-P., Allemand, P., and Ulrich, P.: Surface reconstruction and landslide displacement measurements with Pléiades satellite images, ISPRS J. Photogramm., 95, 1–12, https://doi.org/10.1016/j.isprsjprs.2014.05.008, 2014. a
Stumpf, A., Malet, J.-P., and Delacourt, C.: Correlation of satellite image time-series for the detection and monitoring of slow-moving landslides, Remote Sens. Environ., 189, 40–55, https://doi.org/10.1016/j.rse.2016.11.007, 2017. a
Short summary
This study investigates the use of optical PlanetScope data for offset tracking of the Earth's surface movement. We found that co-registration accuracy is locally degraded when outdated elevation models are used for orthorectification. To mitigate this bias, we propose to only correlate scenes acquired from common perspectives or base orthorectification on more up-to-date elevation models generated from PlanetScope data alone. This enables a more detailed analysis of landslide dynamics.
This study investigates the use of optical PlanetScope data for offset tracking of the Earth's...
