Construction and validation of a new model for cropland soil moisture index based on MODIS data

Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring, and the spectrum interpretation of vegetation and soil are serious factors in the judgment of drought degree. To find a more real-time monitoring index of cropland soil moisture by remote sensing, a Cropland Soil Moisture Index (CSMI) was established in this paper based on the effective reflections of Normalized Difference Vegetation Index (NDVI) on deeper soil moisture and well expressions of Surface Water Content Index (SWCI) on surface soil moisture. By validation with different time-series MODIS data, the Cropland Soil Moisture Index (CSMI) not only overcome the limitation of hysteretic nature and saturated quickly of Normalized Difference Vegetation Index (NDVI), but also take the advantage of the Surface Water Content Index (SWCI) which effectively reduce the atmosphere disturbance and retrieval surface soil water content better. The index passed the significant F-tests with α = 0. 01, and is a true real-time drought monitoring index.

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