Detalhes bibliográficos
Ano de defesa: |
2015 |
Autor(a) principal: |
Maia, Anthony Rafael Soares |
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: |
Não Informado pela instituição
|
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://www.repositorio.ufc.br/handle/riufc/16872
|
Resumo: |
The dynamic of land use/cover in Brazilian semiarid watershed is under influence not only by human actions in these areas, but also by the climatic seasonality in this region. It is necessary know the relationship between the mapping of the use and land cover using remote sensing techniques and the climate seasonality of semiarid regions. Thus, the aim of this study was to use remote sensing techniques to map and classify the land use/cover in the catchment of the Orós reservoir and identify the influence of the climate on the variations of type of classes mapped during the studied period. The Orós reservoir is located in the Southwestern of the state of Ceará, Brazil, and its catchment has 24,900 km². The survey of land use/cover of Catchment in Orós Reservoir (BHAO) was performed by MAXVER method (Maximum Likelihood) classification image objects using satellites image Landsat 5 - TM and Landsat 8 – OLI. The LANDSAT 5 images to 2003, 2005 and 2008 were obtained from the National Institute of Spatial Research (INPE), and the Landsat 8 image to 2013 was obtained by the United States Geological Survey (USGS). Satellite images from the second semester period to each year were used to avoid clouds and rainfall above the vegetation of the studied area. The classes of land use/cover of the catchment in the Orós reservoir presented a dynamic that is influenced not only by human activity in that region, but they were influenced also by factors such as climate, topography and vegetation physiology, specifically the deciduous. It was observed that in those years that occurred heavy rainfall this factor helped the classes as Caatinga Rala and Caatinga Densa. However in those years named dry like 2013, the areas of the Antropizada class increased. Results showed that the changes occurred during the studied period were caused not only by the humans’ actions in that environment but they were caused by climatic factors too. Thus its important analyze the date of the satellite images were obtained. This decrease the action of the climate in the image classify. The deciduous characteristic of Caatinga vegetation, causes changes in the areas due to changes in vegetation of the region. With the leaves falling in dry season these areas present spectral response like the Antropizada class. Higher regions favored the presence of Caatinga Densa class, due to the microclimate and the greatest difficulty that these areas are under to human action. Despite the remote sensing techniques being important tools to help us classify the land use/cover, in regions with deciduous vegetation (Caatinga) it is necessary observe the climatic seasonality, because it has heavy influence in the type of land use/cover presented in regions like Caatinga. |