Estimation of Surface Moisture Content and Evapotranspiration Using Weightage Approach.

Soil moisture (MC) and evapotranspiration (ET) are considered as the most
significant boundary conditions controlling most of the hydrological cycle’s
processes. However, monitoring them continuously over large areas using the high
temporal-resolution optical satellites is very demanding. Satellites such as the
Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution
Imaging Spectroradiometer (MODIS), have a coarse spatial resolution in their images.
Thus it not only impedes the acquisition of an accurate MC and ET but also represents
multispectral reflections from the holistic surface features. This beside their
dependence on vegetation and ground coefficient when assessing MC and ET. The
study aims to enhance the spatial accuracy by weighting the MC produced from
different surface cover classes within the pixel. MC for each pixel is segmented into
three (3) different classes namely urban, vegetation and multi surface cover according
to their respective MC weightage. Secondly, to generate an improved actual ETa map
by overlaying the segmented MC with a rectified ETo. Images from AVHRR and
MODIS satellites were selected in order to generate MC and ET maps. Two powerful
MC algorithms were used based on land Surface Temperature (Ts), vegetation Indices
(VI) and field measurements of MC; which were conducted at variable depths to
examine the depth influence on MC and Ts magnitudes.