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Published March 25, 2021 | Published
Journal Article Open

High-Resolution Soil-Moisture Maps Over Landslide Regions in Northern California Grassland Derived From SAR Backscattering Coefficients

Abstract

Slow-moving landslides are destabilized by accumulated precipitation and consequent soil moisture. Yet, the continuous high-resolution soil-moisture measurements needed to aid the understanding of landslide processes are generally absent in steep terrain. Here, we produce soil-moisture time-series maps for a seasonally active grassland landslide in the northern California coast ranges, USA, using backscattering coefficients from NASA's uninhabited aerial vehicle synthetic aperture radar at 6-m resolution. A physically based radar scattering model is used to retrieve the near-surface (5-cm depth) soil moisture for the landslide. Both forward modeling (backscattering estimation) and the retrieval (soil-moisture validation) show good agreement. The root-mean-square errors (RMSE) for vertical transmit vertical receive (VV) and horizontal transmit horizontal receive (HH) polarizations in forward model comparison are 1.93 dB and 1.88 dB, respectively. The soil-moisture retrieval shows unbiased RMSE of 0.054 m³/m³. Our successful retrieval benefits from the surface and double-bounce scattering, which is common in grasslands. The retrieved maps show saturated wetness conditions within the active landslide boundaries. We also performed sensitivity tests for incidence angle and found that the retrieval is weakly dependent on the angle, especially while using copolarized HH and VV together. Using the two copolarized inputs, the retrieval is also not sensitive to the change of orientation angles of grass cylinders. The physical model inversion presented here can be generally applied for soil-moisture retrieval in areas with the same vegetation cover types in California.

Additional Information

© 2021 IEEE. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/. Manuscript received November 24, 2020; revised January 25, 2021; accepted March 9, 2021. Date of publication March 25, 2021; date of current version May 14, 2021. This work was supported in part by National Aeronautics and Space Administration under Contract 80NM0018D0004, which was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and in part by Earth Surface and Interior Focus Area. The authors would like to thank USDA-NRCS-National Soil Survey Center for processing and providing the soil clay fraction map over the study area, the UAVSAR flight and data processing teams for their help with acquiring and processing the data, and Planet Labs for providing imagery to A.L.H. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Created:
August 20, 2023
Modified:
October 20, 2023