Articles | Volume 22, issue 3
https://doi.org/10.5194/nhess-22-753-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-753-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Mar 2022
Research article |
| 09 Mar 2022
| 09 Mar 2022
Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine
Alexander L. Handwerger
CORRESPONDING AUTHOR
Joint Institute for Regional Earth System Science and Engineering,
University of California, Los Angeles, Los Angeles, CA, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Department of Geology, University of Maryland, College Park, MD, USA
Shannan Y. Jones
Department of Geology, University of Maryland, College Park, MD, USA
Pukar Amatya
University of Maryland, Baltimore County, Baltimore, MD, USA
Goddard Earth Sciences Technology and Research II, Baltimore, MD, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Hannah R. Kerner
Department of Geography, University of Maryland, College Park, MD, USA
Dalia B. Kirschbaum
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
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Short summary
Rapid detection of landslides is critical for emergency response and disaster mitigation. Here we develop a global landslide detection tool in Google Earth Engine that uses satellite radar data to measure changes in the ground surface properties. We find that we can detect areas with high landslide density within days of a triggering event. Our approach allows the broader hazard community to utilize these state-of-the-art data for improved situational awareness of landslide hazards.
Rapid detection of landslides is critical for emergency response and disaster mitigation. Here...
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