Análise de estágios sucessionais em um fragmento florestal no município de Corumbataí do Sul – PR

• Autor(a) principal: Silva, Cayo Murillo Araujo da
• Data de Publicação: 2015
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Texto Completo: http://repositorio.utfpr.edu.br/jspui/handle/1/6957
• topic: Sensoriamento remoto; Satélites artificiais em sensoriamento remoto; Pesquisa florestal; Remote sensing; Artificial satellites in remote sensing; Forests and forestry - Research; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA::SENSORIAMENTO REMOTO DA ATMOSFERA

Currently, there remain few Forest fragments, however of great ecological importance. Several technologies exist que can help not Knowledge and biological physical characteristics of Forest remnants. The remote sensing and one of these tools and can be used to classify the different successional stages local hum. The area of study and a forest fragment of 42.5 ha located in Corumbataí do Sul - PR. It aimed to identification of the main vegetation stages, defined in the agreement with CONAMA Resolution No. 10 of 1993 as eels, initial stage, medium and advanced. For Image Processing has been used satellite images RapidEye® acquired next to Geo catalog do MMA. Were these images georeferenced and suffered hum pre-processing an End to minimize the atmospheric effects of radiance. After This procedure, used the QGIS 2.8.3, paragraph a classification of visual images of pixel by pixel. Verification of the accuracy of the mapping, there was in expeditions half a field with the use of hum Precision GPS and help. As a result, it was made hum thematic map with as ratings of successional stages, being possible to realize what the fragment presents greater middle stage and advanced, can complete so that there is a certain degree of preservation, and que as forest characteristics Semideciduous may have influence this result, depending on the year season in what were these images raised. The use of remote sensing proved to be efficient, given the fact that OS scanned points in the visit on the field really correspond with a rating've done SPRING according to the program, demonstrating que this tool can be used in several related studies one vegetation.