Abstract
The temperature vegetation dryness index (TVDI) has been commonly implemented to estimate regional soil moisture in arid and semi-arid regions. However, the parameterization of the dry edge in the TVDI model is performed with a constraint to define the maximum water stress conditions. Mismatch of the spatial scale between visible and thermal bands retrieved from remotely sensed data and terrain variations also affect the effectiveness of the TVDI. Therefore, this study proposed a new drought index named the condition vegetation drought index (CVDI) to monitor the temporal and spatial variations of soil moisture status by substituting the land surface temperature (LST) with the modified perpendicular drought index (MPDI). In situ soil moisture observations at crop and pasture sites in Victoria were used to validate the effectiveness of the CVDI. The results indicate that the dry and wet edges in the parameterization scheme of the CVDI formed a better-defined trapezoid shape than that of the TVDI. Compared with the MPDI and TVDI for soil moisture monitoring at crop sites, the CVDI exhibited a performance superior to the MPDI and TVDI in most days where the coefficients of determination (R2) achieved can reach to 0.67 on DOY023, 137, 274 and 0.71 on DOY 322 and reproduced more accurate spatial and seasonal variation of soil moisture. Moreover, the CVDI showed higher correlation with the Australian Water Resource Assessment Landscape (AWRA-L) soil moisture product on temporal scales. The R2 can reach to 0.69 and the root mean square error (RMSE) is also much better than that of the MPDI and TVDI. Overall, it can be concluded that the CVDI appears to be a feasible method and can be successfully used in regional soil moisture monitoring.
Highlights
Spatio-temporal distribution and variation of soil moisture (SM) serves as a critical parameter relative to the energy exchange in the soil–vegetation–atmosphere ecosystem, as it controls a wide range of hydrologic, meteorological and agricultural processes [1].It determines the partitioning of precipitation into surface infiltration, runoff, evapotranspiration and subsoil drainage [2,3]
The temperature vegetation dryness index based on land surface temperature (LST)-normalized difference vegetation index (NDVI) space has been widely applied to monitor SM and drought on a regional scale from remotely sensed data
modified perpendicular drought index (MPDI) was used to substitute for the LST and construct a new feature space (MPDI-NDVI trapezoidal space) with quite similar shape and spectral patterns
Summary
Spatio-temporal distribution and variation of soil moisture (SM) serves as a critical parameter relative to the energy exchange in the soil–vegetation–atmosphere ecosystem, as it controls a wide range of hydrologic, meteorological and agricultural processes [1].It determines the partitioning of precipitation into surface infiltration, runoff, evapotranspiration and subsoil drainage [2,3].
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