Articles | Volume 4, issue 2
Earth Surf. Dynam., 4, 343–358, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue: Frontiers in geomorphometry
Research article 21 Apr 2016
Research article | 21 Apr 2016
Topography-based flow-directional roughness: potential and challenges
Sebastiano Trevisani and Marco Cavalli
Related subject area
Cross-cutting themes: Digital Landscapes: Insights into geomorphological processes from high-resolution topography and quantitative interrogation of topographic dataMeasurement of rock glacier surface change over different timescales using terrestrial laser scanning point cloudsCoastal Change Patterns from Time Series Clustering of Permanent Laser Scan DataShort communication: A semiautomated method for bulk fault slip analysis from topographic scarp profilesShort Communication: A simple workflow for robust low-cost UAV-derived change detection without ground control pointsComputing water flow through complex landscapes – Part 1: Incorporating depressions in flow routing using FlowFillRelationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts modelA segmentation approach for the reproducible extraction and quantification of knickpoints from river long profilesA method based on structure-from-motion photogrammetry to generate sub-millimetre-resolution digital elevation models for investigating rock breakdown featuresA comparison of structure from motion photogrammetry and the traversing micro-erosion meter for measuring erosion on shore platformsMeasuring decadal vertical land-level changes from SRTM-C (2000) and TanDEM-X ( ∼ 2015) in the south-central AndesBank erosion processes measured with UAV-SfM along complex banklines of a straight mid-sized river reachIdentification of stable areas in unreferenced laser scans for automated geomorphometric monitoringUnsupervised detection of salt marsh platforms: a topographic methodThe determination of high-resolution spatio-temporal glacier motion fields from time-lapse sequencesBumps in river profiles: uncertainty assessment and smoothing using quantile regression techniquesUnravelling earth flow dynamics with 3-D time series derived from UAV-SfM modelsTree-root control of shallow landslidesAutomated terrestrial laser scanning with near-real-time change detection – monitoring of the Séchilienne landslideValidation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau3-D models and structural analysis of rock avalanches: the study of the deformation process to better understand the propagation mechanismFrontiers in Geomorphometry and Earth Surface Dynamics: possibilities, limitations and perspectivesHow does grid-resolution modulate the topographic expression of geomorphic processes?Suitability of ground-based SfM–MVS for monitoring glacial and periglacial processesImage-based surface reconstruction in geomorphometry – merits, limits and developmentsA nondimensional framework for exploring the relief structure of landscapesTopographic roughness as a signature of the emergence of bedrock in eroding landscapesTracing the boundaries of Cenozoic volcanic edifices from Sardinia (Italy): a geomorphometric contributionTransitional relation exploration for typical loess geomorphologic types based on slope spectrum characteristicsExtracting topographic swath profiles across curved geomorphic featuresShort Communication: TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences
Veit Ulrich, Jack G. Williams, Vivien Zahs, Katharina Anders, Stefan Hecht, and Bernhard Höfle
Earth Surf. Dynam., 9, 19–28,Short summary
In this work, we use 3D point clouds to detect topographic changes across the surface of a rock glacier. These changes are presented as the relative contribution of surface change during a 3-week period to the annual surface change. By comparing these different time periods and looking at change in different directions, we provide estimates showing that different directions of surface change are dominant at different times of the year. This demonstrates the benefit of frequent monitoring.
Mieke Kuschnerus, Roderik Lindenbergh, and Sander Vos
Earth Surf. Dynam. Discuss.,
Revised manuscript accepted for ESurfShort summary
Sandy coasts are areas that undergo a lot of changes, which are caused by different influences, such as tides, wind or human activity. Permanent laser scanning is used to generate a 3-dimensional representations of a part of the coast continuously over an extended period. By comparing three unsupervised learning algorithms, we develop a methodology to analyse the resulting data set and derive which processes are dominating changes in the beach and dunes.
Franklin D. Wolfe, Timothy A. Stahl, Pilar Villamor, and Biljana Lukovic
Earth Surf. Dynam., 8, 211–219,Short summary
This short communication presents an efficient method for analyzing large fault scarp data sets. The programs and workflow required are open-source and the methodology is easy to use; thus the barrier to entry is low. This tool can be applied to a broad range of active tectonic studies. A case study in the Taupo Volcanic Zone, New Zealand, exemplifies the novelty of this tool by generating results that are consistent with extensive field campaigns in only a few hours at a work station.
Kristen L. Cook and Michael Dietze
Earth Surf. Dynam., 7, 1009–1017,Short summary
UAVs have become popular tools for detecting topographic changes. Traditionally, detecting small amounts of change between two UAV surveys requires each survey to be highly accurate. We take an alternative approach and present a simple processing workflow that produces survey pairs or sets that are highly consistent with each other, even when the overall accuracy is relatively low. This greatly increases our ability to detect changes in settings where ground control is not possible.
Kerry L. Callaghan and Andrew D. Wickert
Earth Surf. Dynam., 7, 737–753,Short summary
Lakes and swales are real landscape features but are generally treated as data errors when calculating water flow across a surface. This is a problem because depressions can store water and fragment drainage networks. Until now, there has been no good generalized approach to calculate which depressions fill and overflow and which do not. We addressed this problem by simulating runoff flow across a landscape, selectively flooding depressions and more realistically connecting lakes and rivers.
Erika E. Lentz, Nathaniel G. Plant, and E. Robert Thieler
Earth Surf. Dynam., 7, 429–438,Short summary
Our findings examine several data inputs for probabilistic regional sea-level rise (SLR) impact predictions. To predict coastal response to SLR, detailed information on the landscape, including elevation, vegetation, and/or level of development, is needed. However, we find that the inherent relationship between elevation and land cover datasets (e.g., beaches tend to be low lying) is used to reduce error in a coastal response to SLR model, suggesting new applications for areas of limited data.
Boris Gailleton, Simon M. Mudd, Fiona J. Clubb, Daniel Peifer, and Martin D. Hurst
Earth Surf. Dynam., 7, 211–230,Short summary
The shape of landscapes is influenced by climate changes, faulting or the nature of the rocks under the surface. One of the most sensitive parts of the landscape to these changes is the river system that eventually adapts to such changes by adapting its slope, the most extreme example being a waterfall. We here present an algorithm that extracts changes in river slope over large areas from satellite data with the aim of investigating climatic, tectonic or geologic changes in the landscape.
Ankit Kumar Verma and Mary Carol Bourke
Earth Surf. Dynam., 7, 45–66,Short summary
The article describes the development of a portable triangle control target to register structure-from-motion-derived topographic data. We were able to generate sub-millimetre-resolution 3-D models with sub-millimetre accuracy. We verified the accuracy of our models in an experiment and demonstrated the potential of our method by collecting microtopographic data on weathered Moenkopi sandstone in Arizona. The results from our study confirm the efficacy of our method at sub-millimetre scale.
Niamh Danielle Cullen, Ankit Kumar Verma, and Mary Clare Bourke
Earth Surf. Dynam., 6, 1023–1039,Short summary
This research article provides a comparison between the traditional method of measuring erosion on rock shore platforms using a traversing micro-erosion meter (TMEM) and a new approach using structure from motion (SfM) photogrammetry. Our results indicate that SfM photogrammetry offers several advantages over the TMEM, allowing for erosion measurement at different scales on rock surfaces with low roughness while also providing a means to identify different processes and styles of erosion.
Benjamin Purinton and Bodo Bookhagen
Earth Surf. Dynam., 6, 971–987,Short summary
We show a new use for the SRTM-C digital elevation model from February 2000 and the newer TanDEM-X dataset from ~ 2015. We difference the datasets over hillslopes and gravel-bed channels to extract vertical land-level changes. These signals are associated with incision, aggradation, and landsliding. This requires careful correction of the SRTM-C biases using the TanDEM-X and propagation of significant uncertainties. The method can be applied to moderate relief areas with SRTM-C coverage.
Gonzalo Duró, Alessandra Crosato, Maarten G. Kleinhans, and Wim S. J. Uijttewaal
Earth Surf. Dynam., 6, 933–953,Short summary
The challenge to measure three-dimensional bank irregularities in a mid-sized river reach can be quickly solved in the field flying a drone with ground-control points and later applying structure from motion photogrammetry. We tested a simple approach that achieved sufficient resolution and accuracy to identify the full bank erosion cycle, including undermining. This is an easy-to-use and quickly deployed survey alternative to measure bank erosion processes along extended distances.
Daniel Wujanz, Michael Avian, Daniel Krueger, and Frank Neitzel
Earth Surf. Dynam., 6, 303–317,Short summary
The importance of increasing the degree of automation in the context of monitoring natural hazards or geological phenomena is apparent. A vital step in the processing chain of monitoring deformations is the transformation of captured epochs into a common reference systems. This led to the motivation to develop an algorithm that realistically carries out this task. The algorithm was tested on three different geomorphic events while the results were quite satisfactory.
Guillaume C. H. Goodwin, Simon M. Mudd, and Fiona J. Clubb
Earth Surf. Dynam., 6, 239–255,Short summary
Salt marshes are valuable environments that provide multiple services to coastal communities. However, their fast-paced evolution poses a challenge to monitoring campaigns due to time-consuming processing. The Topographic Identification of Platforms (TIP) method uses high-resolution topographic data to automatically detect the limits of salt marsh platforms within a landscape. The TIP method provides sufficient accuracy to monitor salt marsh change over time, facilitating coastal management.
Ellen Schwalbe and Hans-Gerd Maas
Earth Surf. Dynam., 5, 861–879,Short summary
The simple use of time-lapse cameras as a visual observation tool may already be a great help for environmental investigations. However, beyond that, they have the potential to also deliver precise measurements with high temporal and spatial resolution when applying appropriate processing techniques. In this paper we introduce a method for the determination of glacier motion fields from time-lapse images, but it might also be adapted for other environmental motion analysis tasks.
Wolfgang Schwanghart and Dirk Scherler
Earth Surf. Dynam., 5, 821–839,Short summary
River profiles derived from digital elevation models are affected by errors. Here we present two new algorithms – quantile carving and the CRS algorithm – to hydrologically correct river profiles. Both algorithms preserve the downstream decreasing shape of river profiles, while CRS additionally smooths profiles to avoid artificial steps. Our algorithms are able to cope with the problems of overestimation and asymmetric error distributions.
François Clapuyt, Veerle Vanacker, Fritz Schlunegger, and Kristof Van Oost
Earth Surf. Dynam., 5, 791–806,Short summary
This work aims at understanding the behaviour of an earth flow located in the Swiss Alps by reconstructing very accurately its topography over a 2-year period. Aerial photos taken from a drone, which are then processed using a computer vision algorithm, were used to derive the topographic datasets. Combination and careful interpretation of high-resolution topographic analyses reveal the internal mechanisms of the earthflow and its complex rotational structure, which is evolving over time.
Denis Cohen and Massimiliano Schwarz
Earth Surf. Dynam., 5, 451–477,Short summary
Tree roots reinforce soils on slopes. A new slope stability model is presented that computes root reinforcement including the effects of root heterogeneities and dependence of root strength on tensile and compressive strain. Our results show that roots stabilize slopes that would otherwise fail under a rainfall event. Tension in roots is more effective than compression. Redistribution of forces in roots across the hillslope plays a key role in the stability of the slope during rainfall events.
Ryan A. Kromer, Antonio Abellán, D. Jean Hutchinson, Matt Lato, Marie-Aurelie Chanut, Laurent Dubois, and Michel Jaboyedoff
Earth Surf. Dynam., 5, 293–310,Short summary
We developed and tested an automated terrestrial laser scanning (ATLS) system with near-real-time change detection at the Séchilienne landslide. We monitored the landslide for a 6-week period collecting a point cloud every 30 min. We detected various slope processes including movement of scree material, pre-failure deformation of discrete rockfall events and deformation of the main landslide body. This system allows the study of slope processes a high level of temporal detail.
Benjamin Purinton and Bodo Bookhagen
Earth Surf. Dynam., 5, 211–237,Short summary
We evaluate the 12 m TanDEM-X DEM for geomorphometry and compare elevation accuracy (using over 300 000 dGPS measurements) and geomorphic metrics (e.g., slope and curvature) to other modern satellite-derived DEMs. The optically generated 5 m ALOS World 3D is less useful due to high-frequency noise. Despite improvements in radar-derived satellite DEMs, which are useful for elevation differencing and catchment analysis, lidar data are still necessary for fine-scale analysis of hillslope processes.
Céline Longchamp, Antonio Abellan, Michel Jaboyedoff, and Irene Manzella
Earth Surf. Dynam., 4, 743–755,Short summary
The main objective of this research is to analyze rock avalanche dynamics by means of a detailed structural analysis of the deposits coming from data of 3-D measurements. The studied deposits are of different magnitude: (1) decimeter level scale laboratory experiments and (2) well-studied rock avalanches. Filtering techniques were developed and applied to a 3-D dataset in order to detect fault structures present in the deposits and to propose kinematic mechanisms for the propagation.
Giulia Sofia, John K. Hillier, and Susan J. Conway
Earth Surf. Dynam., 4, 721–725,Short summary
The interdisciplinarity of geomorphometry is its greatest strength and one of its major challenges. This special issue showcases exciting developments that are the building blocks for the next step-change in the field. In reading and compiling the contributions we hope that the scientific community will be inspired to seek out collaborations and share ideas across subject-boundaries, between technique-developers and users, enabling us as a community to gather knowledge from our digital landscape
Stuart W. D. Grieve, Simon M. Mudd, David T. Milodowski, Fiona J. Clubb, and David J. Furbish
Earth Surf. Dynam., 4, 627–653,Short summary
High-resolution topographic data are becoming more prevalent, yet many areas of geomorphic interest do not have such data available. We produce topographic data at a range of resolutions to explore the influence of decreasing resolution of data on geomorphic analysis. We test the accuracy of the calculation of curvature, a hillslope sediment transport coefficient, and the identification of channel networks, providing guidelines for future use of these methods on low-resolution topographic data.
Livia Piermattei, Luca Carturan, Fabrizio de Blasi, Paolo Tarolli, Giancarlo Dalla Fontana, Antonio Vettore, and Norbert Pfeifer
Earth Surf. Dynam., 4, 425–443,Short summary
We investigated the applicability of the SfM–MVS approach for calculating the geodetic mass balance of a glacier and for the detection of the surface displacement rate of an active rock glacier located in the eastern Italian Alps. The results demonstrate that it is possible to reliably quantify the investigated glacial and periglacial processes by means of a quick ground-based photogrammetric survey that was conducted using a consumer grade SRL camera and natural targets as ground control points.
Anette Eltner, Andreas Kaiser, Carlos Castillo, Gilles Rock, Fabian Neugirg, and Antonio Abellán
Earth Surf. Dynam., 4, 359–389,Short summary
Three-dimensional reconstruction of earth surfaces from overlapping images is a promising tool for geoscientists. The method is very flexible, cost-efficient and easy to use, leading to a high variability in applications at different scales. Performance evaluation reveals that good accuracies are achievable but depend on the requirements of the individual case study. Future applications and developments (i.e. big data) will consolidate this essential tool for digital surface mapping.
Stuart W. D. Grieve, Simon M. Mudd, Martin D. Hurst, and David T. Milodowski
Earth Surf. Dynam., 4, 309–325,Short summary
Relationships between the erosion rate and topographic relief of hillslopes have been demonstrated in a number of diverse settings and such patterns can be used to identify the impact of tectonic plate motion on the Earth's surface. Here we present an open-source software tool which can be used to explore these relationships in any landscape where high-resolution topographic data have been collected.
D. T. Milodowski, S. M. Mudd, and E. T. A. Mitchard
Earth Surf. Dynam., 3, 483–499,Short summary
Rock is exposed at the Earth surface when erosion rates locally exceed rates of soil production. This transition is marked by a diagnostic increase in topographic roughness, which we demonstrate can be a powerful indicator of the location of rock outcrop in a landscape. Using this to explore how hillslopes in two landscapes respond to increasing erosion rates, we find that the transition from soil-mantled to bedrock hillslopes is patchy and spatially heterogeneous.
M. T. Melis, F. Mundula, F. DessÌ, R. Cioni, and A. Funedda
Earth Surf. Dynam., 2, 481–492,
S. Zhao and W. Cheng
Earth Surf. Dynam., 2, 433–441,
S. Hergarten, J. Robl, and K. Stüwe
Earth Surf. Dynam., 2, 97–104,
W. Schwanghart and D. Scherler
Earth Surf. Dynam., 2, 1–7,
Atkinson, P. M. and Lewis, P.: Geostatistical classification for remote sensing: an introduction, Comput. Geosci., 26, 361–371, 2000.
Balaguer, A., Ruiz, L. A., Hermosilla, T., and Recio, J. A.: Definition of a Comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification, Comput. Geosci., 36, 231–240, 2010.
Benito-Calvo, A., Pérez-González, A., Magri, O., and Meza, P.: Assessing regional geodiversity: The Iberian Peninsula, Earth Surf. Proc. Land., 34, 1433–1445, 2009.
Berti, M., Corsini, A., and Daehne, A.: Comparative analysis of surface roughness algorithms for the identification of active landslides, Geomorphology, 182, 1–18, 2013.
Booth, A. M., Roering J. J., and Perron, J. T.: Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon. Geomorphology, 109, 132–147, 2009.
Borselli, L., Cassi, P., and Torri, D.: Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment, Catena, 75, 268–277, 2008.
Bue, B. D. and Stepinski, T. F.: Automated classification of landforms on Mars, Comput. Geosci., 32, 604–614, 2006.
Castellarin, A., Dal Piaz, G. V., Picotti, V., Selli, L., Cantelli, L., Martin, S., Montresor, L., Rigatti, G., Prosser, G., Bollettinari, G., Pellegrini, G. B., Carton, A., and Nardin, M.: Note illustrative della carta geologica d'Italia alla scala 1:50000, foglio 059 Tione di Trento, in: APAT and Dipartimento Difesa del Suolo – Servizio Geologico d'Italia, edited by: Trento, S. G.-P. A. T., 159 pp., 2005.
Cavalli, M. and Marchi, L.: Characterisation of the surface morphology of an alpine alluvial fan using airborne LiDAR, Nat. Hazards Earth Syst. Sci., 8, 323–333, https://doi.org/10.5194/nhess-8-323-2008, 2008.
Cavalli, M. and Tarolli, P.: Application of LiDAR Technology for Rivers Analysis, Ital. J. Eng. Geol. Environ, 33–44, https://doi.org/10.4408/IJEGE.2011-01.S-03, 2011.
Cavalli, M., Tarolli, P., Marchi, L., and Dalla Fontana, G.: The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology, CATENA, 73, 249–260, https://doi.org/10.1016/j.catena.2007.11.001, 2008.
Cavalli, M., Trevisani, S., Comiti, F., and Marchi, L.: Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments, Geomorphology, 188, 31–41, https://doi.org/10.1016/j.geomorph.2012.05.007, 2013a.
Cavalli, M., Trevisani, S., Goldin, B., Mion, E., Crema, S., and Valentinotti, R.: Semi-automatic derivation of channel network from a high-resolution DTM: The example of an italian alpine region, Eur. J. Remote Sens., 46, 152–174, https://doi.org/10.5721/EuJRS20134609, 2013b.
Chilès, J.-P. and Delfiner, P.: Geostatistics – Modeling Spatial Uncertainty, John Wiley & Sons, Inc., New Jersey, 734 pp., ISBN-13: 978-0470183151, 2012.
Comiti, F., Marchi, L., Macconi, P., Arattano, M., Bertoldi, G., Borga, M., Brardinoni, F., Cavalli, M., D'Agostino, V., Penna, D., and Theule, J.: A new monitoring station for debris flows in the European Alps: first observations in the Gadria basin, Nat. Hazards, 73, 1175–1198, https://doi.org/10.1007/s11069-014-1088-5, 2014.
Cracknell, M. J. and Reading, A. M.: Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information, Comput. Geosci., 63, 22–33, 2014.
Crema, S., Schenato, L., Goldin, B., Marchi, L., and Cavalli, M.: Toward the development of a stand-alone application for the assessment of sediment connectivity, Rendiconti Online Società Geologica Italiana, 34, 58–61, 2015.
Cressie, N. E.: Statistic for Spatial Data, revised edition, John Wiley & Sons Inc., New York, 900 pp., ISBN-13: 9780471002550, 1993.
Darboux, F., Davy, P., Gascuel-Odoux, C., and Huang, C.: Evolution of soil surface roughness and flowpath connectivity in overland flow experiments, Catena, 46, 125–139, 2002.
Dell'Agnese, A., Brardinoni, F., Toro, M., Mao, L., Engel, M., and Comiti, F.: Bedload transport in a formerly glaciated mountain catchment constrained by particle tracking, Earth Surf. Dynam., 3, 527–542, https://doi.org/10.5194/esurf-3-527-2015, 2015.
Fetter C. W.: Applied hydrogeology, Prentice Hall, New Jersey, USA, 4 edition, 598 pp., 2000.
Frankel, K. L. and Dolan, J. F.: Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data, J. Geophys. Res. Earth Surf., 112, F02025, https://doi.org/10.1029/2006JF000644, 2007.
Gadelmawla, E. S., Koura, M. M., Maksoud, T. M. A., Elewa, I. M., and Soliman, H. H.: Roughness parameters, J. Mater. Process. Tech., 123, 133–145, 2002.
Garrigues, S., Allard, D., Baret, F., and Weiss, M.: Quantifying spatial heterogeneity at the landscape scale using variogram models, Remote Sens. Environ., 103, 81–96, 2006.
Glenn, N. F., Streutker, D. R., Chadwick, D. J., Thackray, G. D., and Dorsch, S. J.: Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity, Geomorphology, 73, 131–148, 2006.
Grohmann, C. H., Smith, M. J., and Riccomini, C.: Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland, IEEE Geosci. Remote S., 49, 1200–1213, https://doi.org/10.1109/TGRS.2010.2053546, 2011.
Herzfeld, U. C.: Master of the Obscure – Automated Geostatistical Classification in Presence of Complex Geophysical Processes, Math. Geosci., 40, 587–618, 2008.
Herzfeld, U. C. and Higginson, C. A.: Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria, Comput. Geosci., 22, 35–52, 1996.
Hiller, J. K. and Smith, M.: Residual relief separation: Digital elevation model enhancement for geomorphological mapping, Earth Surf. Proc. Land., 33, 2266–2276, 2008.
Hofle, B. and Rutzinger, M.: Topographic airborne LiDAR in geomorphology: A technological perspective, Z. Geomorphol., 55, 1–29, 2011.
Jaboyedoff, M., Oppikofer, T., Abellan, A., Derron, M.-H., Loye, A., Metzger, R., and Pedrazzini, A.: Use of LIDAR in landslides investigations: a review, Nat. Hazards, 61, 5–28, https://doi.org/10.1007/s11069-010-9634-2, 2010.
Lashermes, B., Foufoula-Georgiou, E., and Dietrich, W. E.: Channel network extraction from high resolution topography using wavelets, Geophys. Res. Lett., 34, L23S04, https://doi.org/10.1029/2007GL031140, 2007.
Lucieer, A. and Stein, A.: Texture-based landform segmentation of LiDAR imagery, Int. J. Appl. Earth Obs., 6, 261–270, 2005.
Macmillan, R. A., Martin, T. C., Earle, T. J., and Mcnabb, D. H.: Automated analysis and classification of landforms using high-resolution Digital Elevation Data: applications and issues, Can. J. Remote Sens., 29, 592–606, 2003.
McGarigal, K., Tagil, S., and Cushman, S. A.: Surface metrics: An alternative to patch metrics for the quantification of landscape structure, Landscape Ecol., 24, 433–450, 2009.
McKean, J. and Roering, J.: Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry, Geomorphology, 57, 331–351, 2004.
Melelli, L.: Geodiversity: A new quantitative index for natural protected areas enhancement, Geojournal of Tourism and Geosites, 13, 27–37, 2014.
Pike, R. J.: Geomorphometry –diversity in quantitative surface analysis, Prog. Phys. Geog., 24, 1–20, 2000.
Pollyea, R. M. and Fairley, J. P.: Estimating surface roughness of terrestrial laser scan data using orthogonal distance regression, Geology, 39, 623–626, 2011.
Roy, S. G., Koons, P. O., Osti, B., Upton, P., and Tucker, G. E.: Multi-scale characterization of topographic anisotropy, Comput. Geosci., 90, 102–116, https://doi.org/10.1016/j.cageo.2015.09.023, 2015.
Smith, M. W.: Roughness in the Earth Sciences, Earth-Sci. Rev., 136, 202–225, https://doi.org/10.1016/j.earscirev.2014.05.016, 2014.
Sofia, G., Pirotti, F., and Tarolli, P.: Variations in multiscale curvature distribution and signatures of LiDAR DTM errors, Earth Surf. Proc. Land., 38, 1116–1134, 2013.
Tarboton, D.: A new method for the determination of flow directions and upslope areas in grid digital elevation models, Water Resource Research, 33, 309–319, 1997.
Teza, G., Marcato, G., Pasuto, A., and Galgaro, A.: Integration of laser scanning and thermal imaging in monitoring optimization and assessment of rockfall hazard: a case history in the Carnic Alps (Northeastern Italy), Nat. Hazards, 76, 1535–1549, 2015.
Trento Province, LiDAR specifications: available at: http://www.territorio.provincia.tn.it/portal/server.pt/community/lidar/847/lidar/23954, last access: 15 April 2016,
Trevisani, S. and Rocca, M.: MAD: robust image texture analysis for applications in high resolution geomorphometry, Comput. Geosci., 81, 78–92, https://doi.org/10.1016/j.cageo.2015.04.003, 2015.
Trevisani, S., Cavalli, M., and Marchi, L.: Variogram maps from LiDAR data as fingerprints of surface morphology on scree slopes, Nat. Hazards Earth Syst. Sci., 9, 129–133, https://doi.org/10.5194/nhess-9-129-2009, 2009.
Trevisani, S., Cavalli, M., and Marchi, L.: Reading the bed morphology of a mountain stream: a geomorphometric study on high-resolution topographic data, Hydrol. Earth Syst. Sci., 14, 393–405, https://doi.org/10.5194/hess-14-393-2010, 2010.
Trevisani, S., Cavalli, M., and Marchi, L.: Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin, Geomorphology, 161–162, 26–39, 2012.
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., and Reynolds, J. M.: “Structure-from-Motion” photogrammetry: A low-cost, effective tool for geoscience applications, Geomorphology, 179, 300–314, https://doi.org/10.1016/j.geomorph.2012.08.021, 2012.
Woodcock, C. E., Strahler, A. H., and Jupp, D. L. B.: The use of variograms in remote sensing: II. Real digital images, Remote Sens. Environ., 25, 349–379, 1988.
The generalization of the concept of roughness implies the need to refer to a family of roughness indices capturing specific aspects of surface morphology. We test the application of a flow-oriented directional measure of roughness based on the geostatistical index MAD (median of absolute directional differences), computed considering gravity-driven flow direction. The use of flow-directional roughness improves geomorphometric modeling and the interpretation of landscape morphology.
The generalization of the concept of roughness implies the need to refer to a family of...