ESTIMATIVA DA RELAÇÃO ENTRE DENSIDADE POPULACIONAL E ÁREA IMPERMEÁVEL NAS CIDADES DE CORUMBÁ/BR, LADÁRIO/BR E PUERTO QUIJARRO/BO

• Ano de defesa: 2022
• Autor(a) principal: Marília Almeida Teixeira de Carvalho
• Orientador(a): Detlef Hans Gert Walde
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Fronteira; densidade populacional; área impermeável.
• Link de acesso: https://repositorio.ufms.br/handle/123456789/4875

The accentuated process of urbanization in recent decades has caused rapid and intense changes in the environment, making it urgent to reconcile the urbanization process with the use of natural resources. In the study of the urban hydrology, it is fundamental the importance to know in detail the characteristics of land use, since this factor directly influences the increase in the peak of surface runoff and the frequency of floods, in addition to other impacts, such as an increase in the production of water. Sediments due to lack of surface protection, degradation of surface and underground water quality, due to the transport of solid material and clandestine sewage connections and silting and obstruction of rivers, canals and conduits by garbage and sediments. Therefore, it is of fundamental importance to understand the logic of urban occupation, aiming at understanding the spatial, territorial and environmental circumstances that occur there. This can be done through the mapping of impermeable areas using the Geographic Information Systems (GIS) and remote sensing images in an integrated way, whose main advantage is the presentation of updated information. This research aims to quantify the percentage of impermeable areas in the Municipalities of Corumbá - BR, Ladario - BR and Puerto Quijarro - B0 and establish its relationship with population density. Quantification was performed using the supervised pixel-by-pixel classification method, using the Maximum Likelihood algorithm and special high-resolution satellite images. For the different physiognomies, through the classification, samples were collected from the classes of interest, extraction of polygons. The classes of vegetation and exposed soil were considered as permeable areas, while the samples of built-up areas (roofs, sidewalks, parking lots and buildings in general) and paved streets were considered as impermeable areas. From the classification of the images, it was possible to verify the increase in the amount of impermeable areas in all the analyzed scenarios, making it evident that the impermeable area is a variable that depends on the population density of the region.