Geomorphological slope units of the Himalayas

References

• Alvioli, M., Guzzetti, F., & Marchesini, I. (2020). Parameter-free delineation of slope units and terrain subdivision of Italy. Geomorphology, 358(9), 107124. https://doi.org/10.1016/j.geomorph.2020.107124.
   Google Scholar
• Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., & Guzzetti, F. (2016). Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling. Geoscientific Model Development, 9(11), 3975–3991. https://doi.org/10.5194/gmd-9-3975-2016.
   Web of Science ®Google Scholar
• Alvioli, M., Mondini, A. C., Fiorucci, F., Cardinali, M., & Marchesini, I. (2018). Topography-driven satellite imagery analysis for landslide mapping. Geomatics, Natural Hazards and Risk, 9(1), 544–567. https://doi.org/10.1080/19475705.2018.1458050.
   Web of Science ®Google Scholar
• Alvioli, M., Santangelo, M., Fiorucci, F., Cardinali, M., Marchesini, I., Reichenbach, P., Rossi, M., Guzzetti, F., & Peruccacci, S. (2021). Rockfall susceptibility and network-ranked susceptibility along the Italian railway. Engineering Geology, 293(3), 106301. https://doi.org/10.1016/j.enggeo.2021.106301.
   Google Scholar
• Amato, G., Fiorucci, M., Martino, S., Lombardo, L., & Palombi, L. (2020, January). Earthquake-triggered landslide susceptibility in Italy by means of artificial neural network. https://doi.org/10.31223/X59W39.
   Google Scholar
• Belgiu, M., & Drăguţ, L. (2016). Random forest in remote sensing: A review of applications and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 114(Part A), 24–31. https://doi.org/10.1016/j.isprsjprs.2016.01.011.
   Google Scholar
• Bornaetxea, T., Rossi, M., Marchesini, I., & Alvioli, M. (2018). Effective surveyed area and its role in statistical landslide susceptibility assessments. Natural Hazards and Earth System Sciences, 18(9), 2455–2469. https://doi.org/10.5194/nhess-18-2455-2018.
   Web of Science ®Google Scholar
• Camilo, D. C., Lombardo, L., Mai, P. M., Dou, J., & Huser, R. (2017). Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through lasso-penalized generalized linear model. Environmental Modelling & Software, 97(1), 145–156. https://doi.org/10.1016/j.envsoft.2017.08.003.
   Google Scholar
• Chen, Z., Liang, S., Ke, Y., Yang, Z., & Zhao, H. (2020). Landslide susceptibility assessment using different slope units based on the evidential belief function model. Geocarto International, 35(15), 1641–1664. https://doi.org/10.1080/10106049.2019.1582716.
   Web of Science ®Google Scholar
• Cook, K. L., Andermann, C., Gimbert, F., Adhikari, B. R., & Hovius, N. (2018). Glacial lake outburst floods as drivers of fluvial erosion in the Himalaya. Science (New York, NY), 362(6410), 53–57. https://doi.org/10.1126/science.aat4981.
   Google Scholar
• Doménech, G., Alvioli, M., & Corominas, J. (2020). Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based. Landslides, 17(2), 249–265. https://doi.org/10.1007/s10346-019-01279-4.
   Web of Science ®Google Scholar
• Drăguţ, L., & Blaschke, T. (2006). Automated classification of landform elements using object-based image analysis. Geomorphology, 81(3–4), 330–344. https://doi.org/10.1016/j.geomorph.2006.04.013.
   Web of Science ®Google Scholar
• Espindola, G. M., Câmara, G., Reis, I. A., Bins, L. S., & Monteiro, A. M. (2006). Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation. International Journal of Remote Sensing, 14(14), 3035–3040. https://doi.org/10.1080/01431160600617194.
   Google Scholar
• Falcone, G., Acunzo, G., Mendicelli, A., Mori, F., Naso, G., Peronace, E., Porchia, A., Romagnoli, G., Tarquini, E., & Moscatelli, M. (2021). Seismic amplification maps of Italy based on site-specific microzonation dataset and one-dimensional numerical approach. Engineering Geology, 289, 106170. https://doi.org/10.1016/j.enggeo.2021.106170.
   Web of Science ®Google Scholar
• Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations – A new environmental record for monitoring extremes. Scientific Data, 2(1), 150066. https://doi.org/10.1038/sdata.2015.66.
   PubMed Web of Science ®Google Scholar
• Gnyawali, K. R., & Adhikari, B. R. (2017). Spatial relations of earthquake induced landslides triggered by 2015 Gorkha earthquake Mw = 7.8. In M. Mikoš, N. Casagli, Y. Yin, and K. Sassa (Eds.), Advancing culture of living with landslides (pp. 85–93). Springer International Publishing. ISBN 978–3–319–53485–5.
   Google Scholar
• Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), 100–108. https://doi.org/10.2307/2346830.
   Google Scholar
• Hartmann, J., & Moosdorf, N. (2012). The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochemistry, Geophysics, Geosystems, 13(12), 119. https://doi.org/10.1029/2012GC004370.
   Google Scholar
• Heckmann, T., Cavalli, M., Cerdan, O., Foerster, S., Javaux, M., Lode, E., Smetanová, A., Vericat, D., & Brardinoni, F. (2018). Indices of sediment connectivity: opportunities, challenges and limitations. Earth–Science Reviews, 187(12), 77–108. https://doi.org/10.1016/j.earscirev.2018.08.004.
   Google Scholar
• Hofierka, J., Mitášová, H., & Neteler, M. (2009). Chapter 17 geomorphometry in grass gis. In T. Hengl and H. I. Reuter (Eds.), Geomorphometry, Vol. 33 of Developments in soil science (pp. 387–410). Elsevier. https://doi.org/10.1016/S0166-2481(08)00017-2.
   Google Scholar
• Iwahashi, J., Kamiya, I., Matsuoka, M., & Yamazaki, D. (2018, January). Global terrain classification using 280 m dems: Segmentation, clustering, and reclassification. Progress in Earth and Planetary Science, 5(1), 1. https://doi.org/10.1186/s40645-017-0157-2.
   Google Scholar
• Iwahashi, J., & Yamazaki, D. (2021). Global polygons for terrain classification divided into uniform slopes and basins. Preprint.
   Google Scholar
• Jacobs, L., Kervyn, M., Reichenbach, P., Rossi, M., Marchesini, I., Alvioli, M., & Dewitte, O. (2020). Regional susceptibility assessments with heterogeneous landslide information: Slope unit- vs. pixel-based approach. Geomorphology, 356, 107084. https://doi.org/10.1016/j.geomorph.2020.107084.
   Google Scholar
• Jasiewicz, J., & Stepinski, T. F. (2013). Geomorphons -- A pattern recognition approach to classification and mapping of landforms. Geomorphology, 182(10), 147–156. https://doi.org/10.1016/j.geomorph.2012.11.005.
   Google Scholar
• Kargel, J. S., Leonard, G. J., Shugar, D. H., Haritashya, U. K., Fielding, E. J., Bevington, A., Fujita, K., Geertsema, M., Miles, E. S., Steiner, J., Bajracharya, S., Anderson, E., Bawden, G. W., Breashears, D. F., Byers, A., Collins, B., Donnellan, A., Dhital, M. R., Evans, T. L., … Young, N. (2016). Geomorphic and geologic controls of geohazards induced by Nepal's 2015 Gorkha earthquake. Science (New York, NY), 351(6269), aac8353. https://doi.org/10.1126/science.aac8353.
   Google Scholar
• López-Vinielles, J., Fernández-Merodo, J. A., Ezquerro, P., García-Davalillo, J. C., Sarro, R., Reyes-Carmona, C., Barra, A., Navarro, J. A., Krishnakumar, V., Alvioli, M., & Herrera, G. (2021). Combining satellite insar, slope units and finite element modeling for stability analysis in mining waste disposal areas. Remote Sensing, 13(10). https://doi.org/10.3390/rs13102008.
   Google Scholar
• Li, L., & Lan, H. (2020). Integration of spatial probability and size in slope–unit–based landslide susceptibility assessment: A case study. International Journal of Environmental Research and Public Health, 17(21), 8055. https://doi.org/10.3390/ijerph17218055.
   PubMed Web of Science ®Google Scholar
• Marc, O., Behling, R., Andermann, C., Turowski, J. M., Illien, L., Roessner, S., & Hovius, N. (2019). Long-term erosion of the Nepal Himalayas by bedrock landsliding: The role of monsoons, earthquakes and giant landslides. Earth Surface Dynamics, 7(1), 107–128. https://doi.org/10.5194/esurf-7-107-2019.
   Web of Science ®Google Scholar
• Marchesini, I., Salvati, P., Rossi, M., Donnini, M., Sterlacchini, S., & Guzzetti, F. (2021). Data-driven flood hazard zonation of Italy. Journal of Environmental Management, 294(11), 112986. https://doi.org/10.1016/j.jenvman.2021.112986.
   Google Scholar
• Mazzoglio, P., Butera, I., Alvioli, M., & Claps, P. (2022). The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy. Hydrology and Earth System, 26, 1659–1672. https://doi.org/10.5194/hess-26-1659-2022
   Web of Science ®Google Scholar
• Minár, J., & Evans, I. S. (2008). Elementary forms for land surface segmentation: The theoretical basis of terrain analysis and geomorphological mapping. Geomorphology, 95(3–4), 236–259. https://doi.org/10.1016/j.geomorph.2007.06.003.
   Web of Science ®Google Scholar
• Mori, F., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., & Naso, G. (2020). A new Vs30 map for Italy based on the seismic microzonation dataset. Engineering Geology, 275, 105745. https://doi.org/10.1016/j.enggeo.2020.105745.
   Web of Science ®Google Scholar
• Panagos, P., Van Liedekerke, M., Jones, A., & Montanarella, L. (2012). European soil data centre: Response to European policy support and public data requirements. Land Use Policy, 29(2), 329–338. https://doi.org/10.1016/j.landusepol.2011.07.003.
   Web of Science ®Google Scholar
• Pokharel, B., Alvioli, M., & Lim, S. (2020). Relevance of morphometric parameters in susceptibility modelling of earthquake-induced landslides. In M. Alvioli, I. Marchesini, L. Melelli, P. Guth, and S. Peckham, (Eds), Proceedings of the sixth Geomorphometry conference: Geomorphometry 2020. CNR Edizioni. https://doi.org/10.30437/geomorphometry2020_49.
   Google Scholar
• Pokharel, B., Alvioli, M., & Lim, S. (2021). Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics. Scientific Reports, 11(1), 21333. https://doi.org/10.1038/s41598-021-00780-y.
   PubMed Web of Science ®Google Scholar
• Roback, K., Clark, M. K., West, A. J., Zekkos, D., Li, G., Gallen, S. F., Chamlagain, D., & Godt, J. W. (2018). The size, distribution, and mobility of landslides caused by the 2015 Mw7.8 Gorkha earthquake, Nepal. Geomorphology, 301(B4), 121–138. https://doi.org/10.1016/j.geomorph.2017.01.030.
   Google Scholar
• Roback, K., Clark, M. K., West, A. J., Zekkos, D., Li, G., Gallen, S. F., Champlain, D., & Godt, J. W. (2017). Map data of landslides triggered by the 25 April 2015 Mw 7.8 Gorkha, Nepal earthquake. U.S. Geological Survey data release.
   Google Scholar
• Sappington, J. M., Longshore, K. M., & Thompson, D. B. (2007). Quantifying landscape ruggedness for animal habitat analysis: A case study using bighorn sheep in the Mojave Desert. Journal of Wildlife Management, 71(5), 1419–1426. https://doi.org/10.2193/2005-723.
   Web of Science ®Google Scholar
• Schlögel, R., Marchesini, I., Alvioli, M., Reichenbach, P., Rossi, M., & Malet, J.-P. (2018). Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models. Geomorphology, 301(1), 10–20. https://doi.org/10.1016/j.geomorph.2017.10.018.
   Google Scholar
• Tanyaş, H., Rossi, M., Alvioli, M., van Westen, C. J., & Marchesini, I. (2019). A global slope unit-based method for the near real-time prediction of earthquake-induced landslides. Geomorphology, 327(2), 126–146. https://doi.org/10.1016/j.geomorph.2018.10.022.
   Google Scholar
• Tanyaş, H., van Westen, C. J., Persello, C., & Alvioli, M. (2019, April). Rapid prediction of the magnitude scale of landslide events triggered by an earthquake. Landslides, 16(4), 661–676. https://doi.org/10.1007/s10346-019-01136-4.
   Web of Science ®Google Scholar
• Zhang, J.-Q., Liu, R.-K., Deng, W., Khanal, N. R., Gurung, D. R., Murthy, M. S. R., & Wahid, S. (2016). Characteristics of landslide in Koshi River Basin, Central Himalaya. Journal of Mountain Science, 13(10), 1711–1722. https://doi.org/10.1007/s11629-016-4017-0.
   Web of Science ®Google Scholar