A novel vegetation-water resistant soil moisture index for remotely assessing soil surface moisture content under the low-moderate wheat cover

•Current soil moisture indices (SMIs) are sensitive to VWC.•Vegetation-water Resistant SMI (VRSMI) insensitive to VWC.•VRSMI incorporates a physical relation between NIR and SWIR reflectance.•A linear relationship is found between soil VRSMI and soil moisture.•VRSMI supports SMC estimation under low...

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Veröffentlicht in:Computers and electronics in agriculture 2024-09, Vol.224, p.109223, Article 109223
Hauptverfasser: Yue, Jibo, Li, Ting, Liu, Yang, Tian, Jia, Tian, Qingjiu, Li, Suju, Feng, Haikuan, Guo, Wei, Yang, Hao, Yang, Guijun, Qiao, Hongbo
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Sprache:eng
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Zusammenfassung:•Current soil moisture indices (SMIs) are sensitive to VWC.•Vegetation-water Resistant SMI (VRSMI) insensitive to VWC.•VRSMI incorporates a physical relation between NIR and SWIR reflectance.•A linear relationship is found between soil VRSMI and soil moisture.•VRSMI supports SMC estimation under low-moderate crop cover. Soil surface moisture content (SMC) is one of the most critical and fundamental indicators of crop drought because water is vital for vegetation growth. In recent decades, satellite high-spatial-resolution optical multi-spectral remote-sensing sensors have entered a new stage. However, current optical remote sensing SMC indices (SMIs) are sensitive to cropland SMC and vegetation water content (VWC). From dry to saturated, the soil spectra decreased quickly as the SMC increased. For the vegetation spectra, the short-wave infrared (SWIR) bands decreased as the VWC increased. The differences in the responses of near-infrared (NIR) and SWIR bands to water may help distinguish soil moisture from mixed soil-vegetation spectra. This study focuses on (a) analyzing how soil and vegetation reflectance are affected by VWC and SMC, (b) designing a new vegetation-water resistant soil moisture index (VRSMI) based on the differences in the responses of NIR bands and SWIR bands to water, and (c) evaluating the potential of using VRSMI to remotely estimate SMC in low-moderate crop-covered regions. VRSMI uses SWIR1-SWIR2 as the numerator to detect the water absorption features and NIR×(SWIR1)0.5 as the denominator to weaken the vegetation effect. VRSMI and soil-VRSMI (VRSMIs) were tested using laboratory- and field-based spectra datasets. Our study presents the following conclusions: (1) The differences in the responses of NIR and SWIR bands to water help distinguish the effects of soil moisture on mixed soil-vegetation spectra. (2) VRSMIs can provide high-performance SMC estimates under low-moderate vegetation cover (NDVI 
ISSN:0168-1699
1872-7107
DOI:10.1016/j.compag.2024.109223