Temporal and Spatial Soil Moisture Change Pattern Detection Using Multi-Temporal Radarsat SCANSAR Images

摘要

Monitoring soil moisture dynamics is very important for understanding soil-vegetation interactions in both space and time. The currently available satellites, however, are single polarization, single frequency sensors such as ERS-1/2, Radarsat, and JERS-1. There is a need to develop a technique to estimate soil moisture information from these available data sources at both regional and local scales. rnIn this study, we demonstrate a technique using the multi-temporal C band HH polarized Radarsat SCANSAR data to estimate the relative soil moisture change. The experiment data from SGP97 covered a whole range of vegetation growing season and different type agriculture fields. This technique is mainly involved two steps:1. derived from TM and AVHRR measurements for spatial and temporal variations of vegetation covers at different scales. Using a simple radiative transfer model for vegetation volume scattering and the Integral Equation Model (IEM) for surface scattering with the field in situ measurements as the input, we compared the simulated and SAR measured backscattering coefficients in different agricultural fields. We, then, parameterized a semi-empirical model for the different land surface cover types. This semi-empirical model was applied to minimize the effects of the vegetation volume scattering and extinction in radar measurements. 2. Radar incidence angle and surface roughness correction: To make radar incidence correction and eliminate the surface roughness effects, a wide range of surface parameters (soil moisture, surface RMS height, correlation length, incidence angle) was input to the IEM model to simulate the effect of surface roughness and radar incidence angle on the sensitivity of soil moisture to the radar backscattering coefficient. A simple model was established to simulate the effects of incidence angle and surface roughness. Inversion results show that for the C band HH polarized Radarsat SCANSAR data with a range of incidence angle from 20° to 40°, the soil moisture change value can be derived with an acceptable accuracy. The temporal and spatial soil moisture change patterns are associated with rainfall and vegetation cover, as well as the soil hydraulic characteristics.