Standalone SAR Soil Moisture Retrieval Using Radar Vegetation Indices

Shilpa, K and Kumar, DN and Ryu, D (2023) Standalone SAR Soil Moisture Retrieval Using Radar Vegetation Indices. In: 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, 16 July 2023through 21 July 2023, Pasadena, pp. 2641-2644.

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Abstract

In this paper, we present a methodology for retrieving soil moisture using radar-derived vegetation parameters from multi-polarization SAR data. The semi-empirical Water Cloud Model (WCM) is used to retrieve soil moisture in wheat cropping fields. The ground and airborne data collected during the Soil Moisture Active Passive Validation EXperiment 2012 (SMAPVEX12) are used for this study. In a comparison of the two vegetation descriptors used in the WCM, the Radar Vegetation Index (RVI) and Dual-pol Radar Vegetation Index (DpRVI), the DpRVI in VH polarisation provides greater retrieval accuracy with an RMSE of 0.047 m3m-3 and Pearson's correlation coefficient (R) of 0.83. Our results also indicate that HH polarization outperforms the VV polarization for the wheat crop. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	International Geoscience and Remote Sensing Symposium (IGARSS)
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to IEEE Xplore
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	01 Mar 2024 05:35
Last Modified:	01 Mar 2024 05:35
URI:	https://eprints.iisc.ac.in/id/eprint/83799

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