Análise de parâmetros biofísicos estimados pelo algoritmo SEBAL em áreas de cerrado na bacia do Alto Rio Paraguai

• Ano de defesa: 2014
• Autor(a) principal: Fausto, Marcos Alves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Mato Grosso; Brasil; Instituto de Física (IF); UFMT CUC - Cuiabá; Programa de Pós-Graduação em Física Ambiental
• Palavras-chave em Português: Saldo de radiação; SEBAL; Cerrado; CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA; Radiation balance; Savannah
• Link de acesso: http://ri.ufmt.br/handle/1/676

The savannah is diverse biome. The coexistence of fields, forests and savanna draws attention to this biome research on the use and changes in land cover, since these transformations changes the dynamics of net radiation (Rn) to the surface. In this sense, the research examined the biophysical parameters estimated by SEBAL algorithm in savannah areas in the upper Paraguay River Basin. The first stage of the study was to compare the Rn estimated by SEBAL with data measured in micrometeorological towers Farm Miranda (FMI) and Experimental (FEX), and then analyzes the biophysical parameters related to soil cover. 10 Landsat TM sensor images from orbit 226 5 point and 71 were used in 2009. The statistical parameters adopted in the research presented excellent results. Linear correlation coefficient of Person were found in the order of 0.997 of Rninst and 0.979 of Rn24h in the FEX and 0.993 of Rninst and 0.967 of Rn24h in the FMI, and Willmontt coefficient greater than 0.9 between the measured and predicted values by the model. Rn had a seasonal pattern and was higher in areas of Riparian Forest and savannah Grassland and there was an increase in the rainy season and lower in comparison areas with permanent vegetation. Vegetation indices (NDVI, SAVI and LAI) were sensitive to changes in land cover between the dry and rainy seasons, and the Cerrado areas and riparian forest, the albedo and the surface temperature were smaller and larger pastures. The study proved the applicability of the algorithm SEBAL in the study area.