Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness
dc.contributor.author | Kirschbaum, Dalia | |
dc.contributor.author | Stanley, Thomas | |
dc.date.accessioned | 2022-10-06T13:25:35Z | |
dc.date.available | 2022-10-06T13:25:35Z | |
dc.date.issued | 2018-03-22 | |
dc.description.abstract | Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a “nowcast” is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability. | en_US |
dc.description.sponsorship | The authors gratefully acknowledge the end user groups that provided feedback on the utility of the LHASA model, including the Pacific Disaster Center, the Army Geospatial Center, and the Mayor's office in Rio de Janeiro, Brazil. The authors are also extremely thankful for the scientists and research staff that worked to populate the Global Landslide Catalog. Thank you also to David Petley for providing the additional landslide inventory data for Nepal used to evaluate the system, Matthew Lammers, who implemented and maintains the online version of this model and Pat Cappelaere who developed the preliminary Python version of LHASA and API for this code. This work was funded by the NASA Precipitation Measurement Mission. The data used to develop and implement LHASA are available through the following sites. The global landslide susceptibility map is available for download at: https://pmm.nasa.gov/applications/global-landslide-model. IMERG 30 min precipitation data is available for download at https://pmm.nasa.gov/data-access/downloads/gpm or https://pmm.nasa.gov/precip-apps. LHASA nowcasts are available from the past 60 days at https://pmm.nasa.gov/precip-apps. The Global Landslide Catalog data is available at: https://data.nasa.gov/Earth-Science/Global-Landslide-Catalog-Export/dd9e-wu2v. The LHASA nowcasts, GLC data, and IMERG data can also be accessed and downloaded at https://landslides.nasa.gov/viewer. For more information on the Cooperative Open Online Landslide Repository (COOLR) please visit https://landslides.nasa.gov. The LHASA code is open source and available for download at https://github.com/vightel/ojo-bot/tree/master/python. | en_US |
dc.description.uri | https://agupubs.onlinelibrary.wiley.com/doi/10.1002/2017EF000715 | en_US |
dc.format.extent | 19 pages | en_US |
dc.genre | journal articles | en_US |
dc.identifier | doi:10.13016/m2tpjb-54jq | |
dc.identifier.citation | Kirschbaum, D., & Stanley, T. (2018). Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness. Earth's Future, 6, 505– 523. https://doi.org/10.1002/2017EF000715 | en_US |
dc.identifier.uri | https://doi.org/10.1002/2017EF000715 | |
dc.identifier.uri | http://hdl.handle.net/11603/26101 | |
dc.language.iso | en_US | en_US |
dc.publisher | AGU | 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 | Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness | en_US |
dc.type | Text | en_US |
dcterms.creator | https://orcid.org/0000-0003-2288-0363 | en_US |
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