SENTINEL-2/MSI IMAGES AND GEOBIA METHODOLOGY IN MAPPING LAND USE AND LAND COVER IN A SEASONALLY DRY TROPICAL FOREST AREA IN BRAZIL - Oliveira, Janaína Silva de; Lima, Eduardo Rodrigues Viana de; Souza, Bartolomeu Israel de; Seabra, Vinícius da Silva; Santos, Mikaella Pereira dos (Ra'e Ga: o Espaço Geográfico em Análise, 2024)
Caatinga is an endemic Seasonallly Dry Tropical Forest in Brazil that covers about 10% of the national territory. Characterized by a mosaic of vegetation with predominance of deciduous species adapted to the irregular rainfall and a semi-arid climate, the degradation of that biome has been historically neglected by science and public policies. Despite the advance of geo-technology, such features make mapping of land use and land cover through remote sense a high-complexity task when compared to humid environments. The purpose of this study was to differentiate areas with predominance of exotic woods(Prosopis juliflora)from Caatinga’s area of Cariri in Paraíba state, Brazil, through remote sense techniques and analyze the occupation of the studied area. By using the MSI sensor of Sentinel-2 Satellite and the Geographic Object-Based Image Analysis (GEOBIA) methodology, the results showed the efficiency in the identification of targets spectrally difficult to individualize, herein represented by the distinction between areas occupied by alien species and native vegetation (dense/rarefied),allowed identify a pattern of distribution of the areas invaded by P. juliflora and analyzing the occupation of the studied region, with focuson the conservation of biodiversity and geodiversity local areas.By the innovative results obtained,it´s concluded that GEOBIA was a facilitator in distinguishing targets that are spectrally difficult to be individualized and can be widely used in vegetation monitoring in FTSS by remote sensing.