NDLI: Comparison of KOMPSAT-5 and Sentinel-1 Radar Data for Soil Moisture Estimations Using a New Semi-Empirical Model

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Comparison of KOMPSAT-5 and Sentinel-1 Radar Data for Soil Moisture Estimations Using a New Semi-Empirical Model

Content Provider	MDPI
Author	Tao, Liangliang Ryu, Dongryeol Lee, Sun-Gu
Copyright Year	2022
Description	X-band KOMPSAT-5 provides a good perspective for soil moisture retrieval at high-spatial resolution over arid and semi-arid areas. In this paper, an intercomparison of KOMPSAT-5 and C-band Sentinel-1 radar data in soil moisture retrieval was conducted over agricultural fields in Wimmera, Victoria, Australia. Optical images from Sentinel-2 were also used to calculate the scattering contribution of vegetation. This study employed a new semi-empirical vegetation scattering model with a linear association of soil moisture with observed backscatter coefficient and vegetation indices. The Combined Vegetation Index (CVI) was proposed and first used to parameterize vegetation water content. As a result, the vegetation scattering model was developed to monitor soil moisture based on remotely sensed data and ground measurements. Application of the algorithm over dryland wheat field sites demonstrated that the estimated satellite-based soil moisture contents have good linear relationships with the ground measurements. The correlation coefficients (R) are 0.862 and 0.616, and the root mean square errors (RMSEs) have the values of 0.020 $cm^{3}/cm^{3}$ and 0.032 $cm^{3}/cm^{3}$ at X- and C-bands, respectively. Furthermore, the validation results also indicated that X-band provided higher consistent accuracy for soil moisture inversion than C-band. These results showed significant promise in retrieving soil moisture using KOMPSAT-5 and Sentinel-1 remotely sensed data at high-spatial resolution over agricultural fields, with subsequent uses for crop growth and yield estimation.
Starting Page	4042
e-ISSN	20724292
DOI	10.3390/rs14164042
Journal	Remote Sensing
Issue Number	16
Volume Number	14
Language	English
Publisher	MDPI
Publisher Date	2022-08-19
Access Restriction	Open
Subject Keyword	Remote Sensing Imaging Science Kompsat-5 Sentinel-1 Backscatter Coefficient Vegetation Water Content Soil Moisture
Content Type	Text
Resource Type	Article

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