Title :
Soil properties estimates from SAR data by using a bayesian approach combined with IEM
Author :
Paloscia, S. ; Santi, E. ; Pettinato, S. ; Angiulli, M.
Author_Institution :
IFAC, CNR, Firenze
Abstract :
An experiment aimed at investigating the potential of ENVISAT/ASAR in measuring soil moisture is described in this paper. Two test areas were chosen as test sites: Montespertoli and Alessandria, in Central and Northern Italy, respectively. After a preliminary analysis of the direct relationship between the backscattering coefficient at C-band and the soil moisture content of individual fields, a Bayesian approach was attempted for retrieving soil moisture. To obtain a statistically significant data set, simulations performed with the integral equation model were added to experimental data. Moreover, an artificial neural network was tested on Alessandria area
Keywords :
Bayes methods; integral equations; moisture; neural nets; soil; synthetic aperture radar; Alessandria; Bayesian approach; C-band backscattering coefficient; Central/Northern Italy; ENVISAT/ASAR; IEM; Integral Equation Model; Montespertoli; SAR data; artificial neural network; integral equation model; soil moisture measurement; soil properties; Artificial neural networks; Backscatter; Bayesian methods; Content based retrieval; Integral equations; Moisture measurement; Soil measurements; Soil moisture; Soil properties; Testing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-8742-2
DOI :
10.1109/IGARSS.2004.1368530
