Integration of Remote Sensing and in-Situ Data to Estimate Soil Moisture across Mixed Land Cover Types.

Soil moisture is an essential earth variable which has been proven to affect near-surface temperature and climate, hydrological processes, agricultural production, and health of ecological systems. However, the majority of soil moisture data currently available from in-situ monitoring networks reflect conditions only under grasslands, and soil water conditions under other land cover types often differ from those at grassland sites. Remotely-sensed vegetation index data, such as those from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, have shown strong potential to improve high-resolution soil moisture estimates across various land cover types by integration into hydrological models for enhanced large-scale soil moisture estimation. The objective of this ongoing research is to integrate remotely sensed vegetation index data and in-situ meteorological data to accurately estimate high-resolution soil moisture across areas of intermixed land cover types.