A heuristic approach to global landslide susceptibility mapping
dc.contributor.author | Stanley, Thomas | |
dc.contributor.author | Kirschbaum, Dalia B. | |
dc.date.accessioned | 2022-10-06T13:25:44Z | |
dc.date.available | 2022-10-06T13:25:44Z | |
dc.date.issued | 2017-02-07 | |
dc.description.abstract | Landslides can have significant and pervasive impacts to life and property around the world. Several attempts have been made to predict the geographic distribution of landslide activity at continental and global scales. These efforts shared common traits such as resolution, modeling approach, and explanatory variables. The lessons learned from prior research have been applied to build a new global susceptibility map from existing and previously unavailable data. Data on slope, faults, geology, forest loss, and road networks were combined using a heuristic fuzzy approach. The map was evaluated with a Global Landslide Catalog developed at the National Aeronautics and Space Administration, as well as several local landslide inventories. Comparisons to similar susceptibility maps suggest that the subjective methods commonly used at this scale are, for the most part, reproducible. However, comparisons of landslide susceptibility across spatial scales must take into account the susceptibility of the local subset relative to the larger study area. The new global landslide susceptibility map is intended for use in disaster planning, situational awareness, and for incorporation into global decision support systems. | en_US |
dc.description.sponsorship | Thank you to all of the contributors to the Global Landslide Catalog since its creation in 2007. Thank you also to all of those who provided landslide inventories for analysis, including Deo Raj Gurung and Jianqiang Zhang (ICIMOD), Mauro Rossi (CNR IRPI), Graziella Devoli, Manuel Diaz (MARN), the Oregon DOGAMI, the USGS, and the Utah Geological Survey. This work was supported by NASA’s Precipitation Measurement Missions. | en_US |
dc.description.uri | https://link.springer.com/article/10.1007/s11069-017-2757-y | en_US |
dc.format.extent | 20 pages | en_US |
dc.genre | journal articles | en_US |
dc.identifier | doi:10.13016/m2tgdh-6bs2 | |
dc.identifier.citation | Stanley, T., Kirschbaum, D.B. A heuristic approach to global landslide susceptibility mapping. Nat Hazards 87, 145–164 (2017). https://doi.org/10.1007/s11069-017-2757-y | en_US |
dc.identifier.uri | https://doi.org/10.1007/s11069-017-2757-y | |
dc.identifier.uri | http://hdl.handle.net/11603/26102 | |
dc.language.iso | en_US | en_US |
dc.publisher | Springer | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC GESTAR II Collection | |
dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | en_US |
dc.rights | Public Domain Mark 1.0 | * |
dc.rights.uri | http://creativecommons.org/publicdomain/mark/1.0/ | * |
dc.title | A heuristic approach to global landslide susceptibility mapping | en_US |
dc.type | Text | en_US |
dcterms.creator | https://orcid.org/0000-0003-2288-0363 | en_US |