Articles | Volume 22, issue 3
https://doi.org/10.5194/nhess-22-753-2022
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, Mong-Han Huang, Shannan Y. Jones, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum

Related authors

Alpine hillslope failure in the western US: insights from the Chaos Canyon landslide, Rocky Mountain National Park, USA
Matthew C. Morriss, Benjamin Lehmann, Benjamin Campforts, George Brencher, Brianna Rick, Leif S. Anderson, Alexander L. Handwerger, Irina Overeem, and Jeffrey Moore
Earth Surf. Dynam., 11, 1251–1274, https://doi.org/10.5194/esurf-11-1251-2023,https://doi.org/10.5194/esurf-11-1251-2023, 2023
Short summary
Contribution of rock glacier discharge to late summer and fall streamflow in the Uinta Mountains, Utah, USA
Jeffrey S. Munroe and Alexander L. Handwerger
Hydrol. Earth Syst. Sci., 27, 543–557, https://doi.org/10.5194/hess-27-543-2023,https://doi.org/10.5194/hess-27-543-2023, 2023
Short summary
Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars
Chuxuan Li, Alexander L. Handwerger, Jiali Wang, Wei Yu, Xiang Li, Noah J. Finnegan, Yingying Xie, Giuseppe Buscarnera, and Daniel E. Horton
Nat. Hazards Earth Syst. Sci., 22, 2317–2345, https://doi.org/10.5194/nhess-22-2317-2022,https://doi.org/10.5194/nhess-22-2317-2022, 2022
Short summary
InSAR-based characterization of rock glacier movement in the Uinta Mountains, Utah, USA
George Brencher, Alexander L. Handwerger, and Jeffrey S. Munroe
The Cryosphere, 15, 4823–4844, https://doi.org/10.5194/tc-15-4823-2021,https://doi.org/10.5194/tc-15-4823-2021, 2021
Short summary
Rapid landslide identification using synthetic aperture radar amplitude change detection on the Google Earth Engine
Alexander L. Handwerger, Shannan Y. Jones, Mong-Han Huang, Pukar Amatya, Hannah R. Kerner, and Dalia B. Kirschbaum
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-315,https://doi.org/10.5194/nhess-2020-315, 2020
Manuscript not accepted for further review
Short summary

Related subject area

Landslides and Debris Flows Hazards
Addressing class imbalance in soil movement predictions
Praveen Kumar, Priyanka Priyanka, Kala Venkata Uday, and Varun Dutt
Nat. Hazards Earth Syst. Sci., 24, 1913–1928, https://doi.org/10.5194/nhess-24-1913-2024,https://doi.org/10.5194/nhess-24-1913-2024, 2024
Short summary
Assessing the impact of climate change on landslides near Vejle, Denmark, using public data
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024,https://doi.org/10.5194/nhess-24-1897-2024, 2024
Short summary
Analysis of three-dimensional slope stability combined with rainfall and earthquake
Jiao Wang, Zhangxing Wang, Guanhua Sun, and Hongming Luo
Nat. Hazards Earth Syst. Sci., 24, 1741–1756, https://doi.org/10.5194/nhess-24-1741-2024,https://doi.org/10.5194/nhess-24-1741-2024, 2024
Short summary
Assessing landslide damming susceptibility in Central Asia
Carlo Tacconi Stefanelli, William Frodella, Francesco Caleca, Zhanar Raimbekova, Ruslan Umaraliev, and Veronica Tofani
Nat. Hazards Earth Syst. Sci., 24, 1697–1720, https://doi.org/10.5194/nhess-24-1697-2024,https://doi.org/10.5194/nhess-24-1697-2024, 2024
Short summary
Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico
Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello
Nat. Hazards Earth Syst. Sci., 24, 1579–1605, https://doi.org/10.5194/nhess-24-1579-2024,https://doi.org/10.5194/nhess-24-1579-2024, 2024
Short summary

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. 
Download
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.
Altmetrics
Final-revised paper
Preprint