ANALYSIS OF THE EFFECT OF INCIDENCE ANGLE AND MOISTURE CONTENT ON THE PENETRATION DEPTH OF L- AND S-BAND SAR SIGNALS INTO THE GROUND SURFACE

This study uses high resolution hydro-meteorological measurements to model the moisture retention dynamics in a subsurface soil column in response to rainfall events. We report in-situ measurement of soil moisture at 10–40 cm soil depth (each 10 cm) and corresponding meteorological parameters (rainfall, relative humidity, evaporation, etc.) at every 10 minute interval. We have used these measurements to develop an automated machine learning based model and assess its prediction capabilities.

This study demonstrates an innovative methodology to estimate the formative discharge of alluvial rivers from remote sensing images. We have developed an automated algorithm in Python 3 to extract the width of a river channel from satellite images. Finally, this channel width is translated into discharge using a semi-empirical regime equation developed from field measurements and threshold channel theory that explains the first-order geometry of alluvial channels.