Avaliação da dinâmica espacial e temporal da vulnerabilidade ambiental da zona costeira sul do estado da Paraíba

The evolution of the occupation of the Brazilian coastal geographical space has been an important issue to be faced by environmental planners, as there is a need for compatibility between anthropic activities and the carrying capacity of the land, seeking to minimize environmental vulnerability in the their various ecosystems. Knowledge of environmental vulnerability should be extended over time by analyzing spatial growth trends with a view to establishing appropriate environmental zoning policies. The southern coastal zone of Paraíba State (ZC-Sul / PB), object of this study, has suffered over the centuries with the destruction of the Atlantic Forest, replaced by the majority occupation of agricultural activity, especially sugar cane, besides of urban sprawl. The research, reported in this thesis, aimed to elaborate cartograms of the degrees of environmental vulnerability to soil loss destined to the evaluation of the relative stability of the morphodynamic categories, associated with the morphogenesis / pedogenesis relationship, in ZC-Sul / PB for past and predictive scenarios. Issues related to the Coastal Zone (ZC) are addressed with emphasis on the delimitation of its geographical space in the international and Brazilian context. Integrated management within the river basin and ZC has guidelines set out from the environment, sea and water resources policies. Therefore, a conceptual diagram concerning the water resources planning zones and the coastal zone was presented, as well as the delimitation of the ZC-Sul/PB, in the light of criteria established in the literature, and the arbitrary criterion, regarding to the BR-101 highway layout, was considered to be the most appropriate. The mapping of the dynamics of land use and occupation classes (UOS) changes in the ZC-Sul/PB was performed, in the past scenarios for 1988, 2001 and 2013, using satellite images for processing through of supervised automatic interpretation and classification techniques software. UOS predictions were also made for the years 2023 ...