Estimativa do saldo de radiação de uma floresta de transição amazônia-cerrado por sensoriamento remoto

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Marques, Heloisa Oliveira
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
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
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://ri.ufmt.br/handle/1/276
Resumo: The Amazon has an important role in biodiversity, has the largest expanse of tropical rainforest in the world. Recently, the use of geotechnologies possible to identify in real time the changes that occur in the Earth's surface, resulting from natural and anthropogenic processes several phenomena. Many changes of this level can be detected by monitoring and determination of radiative exchanges that take place on the surface. In this sense, the present study aimed to determine the dynamics of the balance of radiation to the surface by means of images generated by the satellite Landsat 5 TM sensor in a Transition Forest between Amazon and Cerrado, in Maracaí Farm, located near Sinop - MT; orbit with 226 and 227, paragraph 68 for the years 2005 to 2008 were generated letters to vegetation indices, albedo and surface temperature, instantaneous radiation balance and average daily in 24 hours using the SEBAL algorithm. The data were validated with measurements carried out in micrometeorological tower that was installed in the study area. Images for each year analyzed, to better evaluate the radiative fluxes and estimates that environment selected. One can see smaller value for the balance of instantaneous radiation during the dry season, due to haze resulting from burned on site. For Rninst and Rn24h the surface with respect to the measured data were obtained the following relative and absolute mean errors with values of 2,4% and 2,0%; 18,2 Wm-2 and 14,3 Wm-2; "r", and 0,604 to 0,938 and "d" of 0.966 and 0.703 respectively. According to the results obtained in this work can be said that the methodology for estimation of Rn was effective.