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Citació: Talone, M.; Camps, A.; Monerris, A.; Vall-llossera, M.; Ferrazzoli, P.; Piles, M. Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures. IEEE Transactions on geoscience and remote sensing, 2003, vol. 45, núm. 7, p. 1996-2003.
Títol: Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures.
Autor: Talone, Marco Veure Producció científica UPC; Camps Carmona, Adriano José Veure Producció científica UPC; Monerris Belda, Alessandra Veure Producció científica UPC; Vall-Llossera Ferran, Mercedes Magdalena Veure Producció científica UPC; Ferrazzoli, P.; Piles, Maria
Editorial: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Data: 31-jul-2007
Tipus de document: Article
Resum: The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the soil moisture and ocean salinity (SMOS) end-to-end performance simulator (SEPS). The brightness temperature generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This high-resolution generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. Results are compared to brightness temperatures that are computed under the assumption of an ellipsoidal Earth.
Descripció: The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the Soil Moisture and Ocean Salinity (SMOS) End-to-End Performance Simulator (SEPS). The brightness temperature (TB) generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This highresolution TB generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. THE AVAILABILITY of high-resolution brightness temperature (TB) maps at L-band is crucial to analyze important issues dealing with bare and vegetation-covered land emission and to develop inversion algorithms in preparation for real Soil Moisture and Ocean Salinity (SMOS) mission data. Mixed-pixel, coastlines, shadowing, and topography effects on the measured brightness temperatures need further study, but the lack of global geophysical data at sufficient temporal and spatial resolution and the large amount of data involved in the generation of high-resolution TB maps on a global basis complicate the issue. In fact, in spite of the existence of global digital elevation models with sufficient spatial resolution, accurate land cover data do not exist for most parts of the world. To address these issues, a series of simulations has been performed with an improved version of the SMOS End-to-End Performance Simulator (SEPS) [1], [2], in which, to date, all points on Earth have been assumed to be at sea level. The study has been done over the region of Catalonia, on the northeastern coast of Spain, because of its many different land cover types, topography, and the presence of a coastline. A 30-m-resolution digital elevation map [3] and a 100-m-resolution land coverage map of Catalonia [4] have been used as inputs, and SEPS has been conveniently modified to generate high-resolution TB maps of this area. A variety of soil and land cover types (crops, bushes, marshes, etc.) have been parameterized using the values obtained from field experiments and literature [5]–[10], [12].
ISSN: 0196-2892
URI: http://hdl.handle.net/2117/9111
Apareix a les col·leccions:RSLAB - Remote Sensing Research Group. Articles de revista
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