The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Automatic delineation of geomorphological slope units with <tt>r.slopeunits v1.0</tt> and their optimization for landslide susceptibility modeling
Open accessAbstract
Abstract. Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.
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Cites
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Self-citationEstimating the quality of landslide susceptibility models
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., & Galli, M. (2006) · Geomorphology · doi:10.1016/j.geomorph.2006.04.007 · Cited by 935
Self-citationDrăguţ, L., Dirk Tiede, A., & Levick, S. R. (2010) · International Journal of Geographical Information Systems · doi:10.1080/13658810903174803 · Cited by 806
Sedimentology and Stratigraphy
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Open Source GIS: A Grass GIS Approach
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Automated parameterisation for multi-scale image segmentation on multiple layers
Drăguţ, L., Csillik, O., Eisank, C., & Tiede, D. (2014) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2013.11.018 · Cited by 621
Comparing landslide inventory maps
Galli, M., Ardizzone, F., Cardinali, M., Guzzetti, F., & Reichenbach, P. (2008) · Geomorphology · doi:10.1016/j.geomorph.2006.09.023 · Cited by 580
Self-citationGis Technology in Mapping Landslide Hazard
Carrara, A., Cardinali, M., Guzzetti, F., & Reichenbach, P. (1995) · Advances in Natural and Technological Hazards Research · doi:10.1007/978-94-015-8404-3_8 · Cited by 574
Self-citationAutomated classification of landform elements using object-based image analysis
Drăguţ, L., & Blaschke, T. (2006) · Geomorphology · doi:10.1016/j.geomorph.2006.04.013 · Cited by 521
Cited by
A review of statistically-based landslide susceptibility models
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018) · Earth-Science Reviews · doi:10.1016/j.earscirev.2018.03.001 · Cited by 2,347
Self-citationMapping landslide susceptibility using data-driven methods
Zêzere, J. L., Pereira, S., Melo, R., Oliveira, S. C., & Garcia, R. A. C. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.02.188 · Cited by 344
Administrative boundaries and urban areas in Italy: A perspective from scaling laws
Alvioli, M. (2020) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2020.103906 · Cited by 34
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Metadata
- Authors
- Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., & Guzzetti, F.
- Venue
- Geoscientific Model Development
- Publisher
- Copernicus GmbH
- Published
- 2016-11-09
- Volume
- 9
- Issue
- 11
- Pages
- 3975-3991
- ISSN
- 1991-959X (ISSN-L)
- 1991-9603
- OpenAlex
- W2554357049
- Cited by
- 355
- References
- 20
- FWCI
- 25.57
- Type
- journal article
- Language
- en
- Open access
- gold
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- Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., & Guzzetti, F. (2016). Automatic delineation of geomorphological slope units with <tt>r.slopeunits v1.0</tt> and their optimization for landslide susceptibility modeling. Geoscientific Model Development. https://doi.org/10.5194/gmd-9-3975-2016
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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