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Monitoring Surface Soil Moisture Content over the Vegetated Area by Integrating Optical and SAR Satellite Observations in the Permafrost Region of Tibetan Plateau

Chenyang Xu, John J. Qu, Xianjun Hao and 1 more

Remote Sensing · 2020

doi:10.3390/rs12010183 (opens in a new tab)

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Abstract

Surface soil moisture (SSM), the average water content of surface soil (up to 5 cm depth), plays a key role in the energy exchange within the ecosystem. We estimated SSM in areas with vegetation cover (grassland) by combining microwave and optical satellite measurements in the central Tibetan Plateau (TP) in 2015. We exploited TERRA moderate resolution imaging spectroradiometer (MODIS) and Sentinel-1A synthetic aperture radar (SAR) observations to estimate SSM through a simplified water-cloud model (sWCM). This model considers the impact of vegetation water content (VWC) to SSM retrieval by integrating the vegetation index (VI), the normalized difference water index (NDWI), or the normalized difference infrared index (NDII). Sentinel-1 SAR C-band backscattering coefficients, incidence angle, and NDWI/NDII were assimilated in the sWCM to monitor SSM. The soil moisture and temperature monitoring network on the central TP (CTP-SMTMN) measures SSM within the study area, and ground measurements were applied to train and validate the model. Via the proposed methods, we estimated the SSM in vegetated area with an <i>R<sup>2</sup></i> of 0.43 and a ubRMSE of 0.06 m<sup>3</sup>/m<sup>3</sup> when integrating the NDWI and with an <i>R<sup>2</sup></i> of 0.45 and a ubRMSE of 0.06 m<sup>3</sup>/m<sup>3</sup> when integrating the NDII.

Abstract licence: CC BY

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