Mapeamento multitemporal do uso da terra no entorno da floresta estadual Edmundo Navarro de Andrade em de Rio Claro -SP

• Autor(a) principal: Diotto, Marina Gama [UNESP]
• Data de Publicação: 2017
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/156322; http://www.athena.biblioteca.unesp.br/exlibris/bd/capelo/2018-01-24/000895815.pdf
• topic: Solo - Uso; Geoprocessamento; Florestas; Rio Claro (SP)

The knowledge of the dynamics of a landscape in a given region is an important factor in regional and local planning. In this way, the analysis of aerial photographs and those of remote orbital sensors becomes a remarkable tool in the acquisition of information for land use mapping. The classification of an image is nothing more than the identification of elements in it by the association of each of its pixels to a certain thematic class, and when followed to a temporality associated with its low cost, it is possible to analyze constant modifications made by the action of the human being in the dynamics of economic processes, urban expansion and those related to the environment. At the end of the 19th century, with the need to supply the raw material demand for the construction and maintenance of the railways, forestry plantations were created. In this way, was created in 1909 the Horto Florestal Edmundo Navarro de Andrade, the largest among the towns of São Paulo, classified as Forest by State Decree n. 46,819 in 2002, becoming the State Forest Edmundo Navarro de Andrade (FEENA), located in the municipality of Rio Claro, in São Paulo State. Over the years, the Forest had its functions changed, becoming a tourist attraction in the municipality, as well as important role in the scientific area, with the possibility of studying the biodiversity present. Under this premise, the objective of this work was to evaluate the changes in land use and occupation in the FEENA environment, with a temporal cut in the years 1978, 1995, 2005 and 2015. The segmentation classification method was carried out using aerial photographs and images of the Landsat-5 TM and Landsat-8 / OLI satellite, to identify the different types of use and through the Kappa Index calculation...