Análise da estrutura espacial da cobertura do solo

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Acerbi Júnior, Fausto Weimar
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Lavras
Programa de Pós-Graduação em Engenharia Florestal
UFLA
brasil
Departamento de Ciências Florestais
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://repositorio.ufla.br/jspui/handle/1/10605
Resumo: The Earth's surface is constantly changing when it comes to land use and land cover. Changes in the use and cover of land, whether natural or induced by man, affect the spatial distribution and availability of natural resources. The impact of these changes on ecosystems depends on the location, extent and the conversion rates of land use. The difficulty lies in the fact that land use and land cover changes are usually determined by a complex network of biophysical and socio-economic factors, which interact in time and space as well as in different historical and geographical contexts. In this study, we used remote sensing images and geostatistic techniques to characterize the initial spatial structure of the landscape, as well as the changes occurred in these structures over the years. Later, logistic regression was used to estimate the areas with the highest probability of changes. This thesiswas divided into three articles. Article 1 (Change detection in Brazilian Savannah using semivariograms derived from NDVI images), deals with the detection of changes in the land use and land cover of Cerrado areas using semivariograms derived from NDVI images. In Article 2 (Analysis of changes in landscape structure by means of semivariograms derived from NDVI images), we analyzed the influence of the initial structure of the landscape over the behavior of semivariogram parameters in changed areas. Subsequently, we used logistic regression techniques to determine the areas with the highest probability of changes in land use and land cover. In Article 3 (Relation between landscape ecology metrics, semivariogram parameters and changes in land cover), we analyzed the relation between landscape ecology metrics and semivariogram parameters derived from NDVI images in areas changed by land use and cover, in order to identify which landscape ecology metrics can aid in understanding the behavior of the semivariogram parameters on these areas.