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Soil Moisture Retrieval Over Crop Fields from Multi-polarization SAR Data

Shilpa, K and Suresh Raju, C and Mandal, D and Rao, YS and Shetty, A (2023) Soil Moisture Retrieval Over Crop Fields from Multi-polarization SAR Data. In: Journal of the Indian Society of Remote Sensing .

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Official URL: https://doi.org/10.1007/s12524-023-01682-4


Soil moisture estimation from agriculture fields using SAR measurements is a challenging process owing to the presence of vegetation canopy. In this study, the soil moisture (SM) is retrieved from multi-polarization airborne L- and C-band E-SAR data of different agriculture fields by using the radar parameter, Radar Vegetation Index (RVI). The retrieval methodology employs the semi-empirical Water Cloud Model (WCM) for vegetation-soil system modeling, followed by an inversion algorithm based on a Look Up Table approach. The impact of using different vegetation descriptors, both from in situ measured (Leaf Area Index, Wet Biomass and Vegetation Water Content) and radar derived (L-band RVI and C-band RVI), on the WCM inversion for SM retrieval is examined. The use of the RVI as the vegetation descriptor, which is obtained from C-band data, improves soil moisture retrieval with an RMSE of 7–8% volumetric soil moisture at L-band.

Item Type: Journal Article
Publication: Journal of the Indian Society of Remote Sensing
Publisher: Springer
Additional Information: The copyright for this article belongs to Springer.
Keywords: Model inversion; Multi-frequency; Soil moisture; Synthetic Aperture Radar; Water Cloud Model
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 13 Apr 2023 10:39
Last Modified: 13 Apr 2023 10:39
URI: https://eprints.iisc.ac.in/id/eprint/81332

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