Articles | Volume 22, issue 3
Nat. Hazards Earth Syst. Sci., 22, 753–773, 2022
https://doi.org/10.5194/nhess-22-753-2022

Special issue: Remote sensing and Earth observation data in natural hazard...

Nat. Hazards Earth Syst. Sci., 22, 753–773, 2022
https://doi.org/10.5194/nhess-22-753-2022
Research article
09 Mar 2022
Research article | 09 Mar 2022

Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine

Alexander L. Handwerger et al.

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Cited articles

Adriano, B., Yokoya, N., Miura, H., Matsuoka, M., and Koshimura, S.: A semiautomatic pixel-object method for detecting landslides using multitemporal ALOS-2 intensity images, Remote Sens., 12, 561, https://doi.org/10.3390/rs12030561, 2020. 
Amatya, P., Kirschbaum, D., and Stanley, T.: Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal, Remote Sens., 11, 2284, https://doi.org/10.3390/rs11192284, 2019. 
Amatya, P., Kirschbaum, D., Stanley, T., and Tanyas, H.: Landslide mapping using object-based image analysis and open source tools, Eng. Geol., 282, 106000, https://doi.org/10.1016/j.enggeo.2021.106000, 2021. 
Benz, S. A. and Blum, P.: Global detection of rainfall-triggered landslide clusters, Nat. Hazards Earth Syst. Sci., 19, 1433–1444, https://doi.org/10.5194/nhess-19-1433-2019, 2019. 
Bessette-Kirton, E. K., Cerovski-Darriau, C., Schulz, W. H., Coe, J. A., Kean, J. W., Godt, J. W., Thomas, M. A., and Hughes, K. S.: Landslides triggered by Hurricane Maria: Assessment of an extreme event in Puerto Rico, GSA Today, 29, 4–10, https://doi.org/10.1130/GSATG383A.1, 2019. 
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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.
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