33 citations as recorded by crossref.

1. The influence of mechanical properties on the link between tectonic and topographic evolution P. Koons et al. https://doi.org/10.1016/j.geomorph.2010.11.012
2. Multi-scale characterization of topographic anisotropy S. Roy et al. https://doi.org/10.1016/j.cageo.2015.09.023
3. A simplified geostatistical approach for characterizing key aspects of short-range roughness S. Trevisani et al. https://doi.org/10.1016/j.catena.2023.106927
4. Comparative analysis of surface roughness algorithms for the identification of active landslides M. Berti et al. https://doi.org/10.1016/j.geomorph.2012.10.022
5. Geomorphic features extraction from high-resolution topography: landslide crowns and bank erosion P. Tarolli et al. https://doi.org/10.1007/s11069-010-9695-2
6. Alluvial Fan Dynamics – Revisiting the Field C. Scheinert et al. https://doi.org/10.1111/gec3.12004
7. MAD: robust image texture analysis for applications in high resolution geomorphometry S. Trevisani & M. Rocca https://doi.org/10.1016/j.cageo.2015.04.003
8. Analysis of Karst Surface Anisotropy Using Directional Semivariograms, Slovenia T. Verbovšek https://doi.org/10.1007/s00024-023-03411-x
9. The role of morphometric parameters in Digital Terrain Models interpolation accuracy: a case study D. Godone & G. Garnero https://doi.org/10.5721/EuJRS20134611
10. Terrain Analysis According to Multiscale Surface Roughness in the Taklimakan Desert S. Trevisani & P. Guth https://doi.org/10.3390/land13111843
11. A morphologic characterisation of the 1963 Vajont Slide, Italy, using long-range terrestrial photogrammetry A. Wolter et al. https://doi.org/10.1016/j.geomorph.2013.10.006
12. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments M. Cavalli et al. https://doi.org/10.1016/j.geomorph.2012.05.007
13. Madograms help to quantify mountain frontal zones—An approach towards comparative spatial analysis of complex landforms M. Szymanowski et al. https://doi.org/10.1111/tgis.12822
14. Semi-automatic derivation of channel network from a high-resolution DTM: the example of an Italian alpine region M. Cavalli et al. https://doi.org/10.5721/EuJRS20134609
15. A MS‐lesion pattern discrimination plot based on geostatistics R. Marschallinger et al. https://doi.org/10.1002/brb3.430
16. Surface Roughness in Geomorphometry: From Basic Metrics Toward a Coherent Framework S. Trevisani & P. Guth https://doi.org/10.3390/rs17233864
17. Mapping and monitoring geological hazards using optical, LiDAR, and synthetic aperture RADAR image data K. Joyce et al. https://doi.org/10.1007/s11069-014-1122-7
18. Semi-automated mapping of landforms using multiple point geostatistics E. Vannametee et al. https://doi.org/10.1016/j.geomorph.2014.05.032
19. Geostatistical Analysis of White Matter Lesions in Multiple Sclerosis Identifies Gender Differences in Lesion Evolution R. Marschallinger et al. https://doi.org/10.3389/fnmol.2018.00460
20. Extraction of multi-scale landslide morphological features based on local G i * using airborne LiDAR-derived DEM W. Shi et al. https://doi.org/10.1016/j.geomorph.2017.12.005
21. Evaluation of different DTMs in sediment connectivity determination in the Mascarada River Watershed, southern Brazil F. Zanandrea et al. https://doi.org/10.1016/j.geomorph.2019.02.005
22. Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping L. Drăguţ & A. Dornik https://doi.org/10.1080/13658816.2015.1131828
23. Reading the bed morphology of a mountain stream: a geomorphometric study on high-resolution topographic data S. Trevisani et al. https://doi.org/10.5194/hess-14-393-2010
24. UAV‐derived habitat predictors contribute strongly to understanding avian species–habitat relationships on the Eastern Qinghai‐Tibetan Plateau A. Fritz et al. https://doi.org/10.1002/rse2.73
25. High-resolution morphologic characterization of conservation agriculture P. Tarolli et al. https://doi.org/10.1016/j.catena.2018.08.026
26. Hacking the topographic ruggedness index S. Trevisani et al. https://doi.org/10.1016/j.geomorph.2023.108838
27. Use of LIDAR in landslide investigations: a review M. Jaboyedoff et al. https://doi.org/10.1007/s11069-010-9634-2
28. Topography-based flow-directional roughness: potential and challenges S. Trevisani & M. Cavalli https://doi.org/10.5194/esurf-4-343-2016
29. Anisotropic Characteristics of Post Sheared Fracture Surface G. Wang et al. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001697
30. A R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots R. Marschallinger et al. https://doi.org/10.3390/brainsci11010090
31. Evaluating roadside rockmasses for rockfall hazards using LiDAR data: optimizing data collection and processing protocols M. Lato et al. https://doi.org/10.1007/s11069-011-9872-y
32. Soil surface roughness modelling with the bidirectional autocorrelation function R. Dusséaux & E. Vannier https://doi.org/10.1016/j.biosystemseng.2022.05.012
33. Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin S. Trevisani et al. https://doi.org/10.1016/j.geomorph.2012.03.031