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- W2043359667 abstract "The main aim of the analysis presented in this paper is to cross-compare two retrieval methodologies, one based onNeural Network and the other on Bayesian approach in different types of test areas and verify if they are able to retrievethe same spatial and temporal soil moisture features. The test areas are located in three regions in Italy in order to takeinto account different soil and meteorological conditions. The comparison of the backscattering coefficients as a functionof soil moisture values indicate the same sensitivity to soil moisture variations but with a different bias which maydepend on soil characteristics, vegetation presence and roughness effect. The results of the two retrieval methodologiesindicate an overall good agreement. Only in one single date, the discrepancy between the results is around 8%. Thealgorithms are also compared in terms of processing times." @default.
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- W2043359667 date "2009-09-17" @default.
- W2043359667 modified "2023-10-03" @default.
- W2043359667 title "Spatial and temporal soil moisture monitoring in semi-arid and humid areas with high resolution ASAR images" @default.
- W2043359667 doi "https://doi.org/10.1117/12.830696" @default.
- W2043359667 hasPublicationYear "2009" @default.
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