Title :
Soil moisture retrieval from ASAR measurements over natural surfaces with a large roughness variability
Author :
Satalino, G. ; Mattia, F. ; Pasquariello, G. ; Dente, L.
Author_Institution :
CNR-ISSIA, Bari, Italy
Abstract :
In this work, the accuracy of soil moisture retrieved from ASAR data over bare or sparsely vegetated surfaces is investigated by means of a simulation study. The soil moisture retrieval method is based on an optimization algorithm that appropriately inverts theoretical direct models by assimilating a priori information on surface parameters. In order to account for a large variability of roughness conditions, two complementary models have been used, namely the integral equation method model and the geometrical optics model. The performance of the inversion method has been assessed on simulated noisy ASAR data, as a function of different a priori information quality level.
Keywords :
backscatter; data acquisition; hydrological techniques; integral equations; inverse problems; moisture measurement; remote sensing by radar; soil; synthetic aperture radar; vegetation mapping; ASAR measurements; IEM model; geometrical optics model; integral equation method model; inversion method; natural surfaces; optimization algorithm; roughness conditions; roughness variability; soil moisture retrieval; sparsely vegetated surfaces; Geometrical optics; Information retrieval; Integral equations; Moisture measurement; Optimization methods; Rough surfaces; Soil measurements; Soil moisture; Solid modeling; Surface roughness;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International
Print_ISBN :
0-7803-9050-4
DOI :
10.1109/IGARSS.2005.1526191