SPATIO-TEMPORAL VARIABILITY OF RAINFALL AND COVERAGE AND LAND USE IN THE MUNICIPALITY OF GARANHUNS-PE

Abstract

Land cover and land use changes are influenced by several factors, and understanding their dynamics is essential to identify the limitations imposed by natural and socioeconomic processes. This study aims to classify and analyze the distribution of land cover and land use in the municipality of Garanhuns-PE, using remote sensing data in a multitemporal assessment between the years 2016 and 2022, correlating precipitation data with vegetation indices. Four images from the Sentinel 2 Satellite, with multispectral instrumentation (MSI), and accumulated precipitation data for specific years were selected. The analyses were performed using geoprocessing techniques. At first, interpolation was performed using the inverse squared distance method. Then, the SAVI was calculated, with these products interpreting the patterns in the images. The results revealed differences in precipitation behavior between the years analyzed. For 2016, the totals were lower than expected, while for 2022, the totals were high, being interpreted in accordance with sea surface temperature (SST) anomalies. The mapped classes showed differences between the dates (2016 and 2022): water reservoirs, -0.56 km²; ACE, 46.43 km²; BAF, -0.24 km²; MAF, -2.68 km² and AAF, -27.54 km². Thus, in 2022, photosynthetically active materials represented larger extensions. In this sense, the land cover and use classes analyzed occurred in a way that was reconciled with the spatiotemporal variation of precipitation. Finally, the coverage and use mapping underwent validation with an acceptable kappa index of 0.60 (2016) and 0.67 (2022). Thus, the recognition of the behavior of the coverage was determined according to the distributions of precipitation, making it possible to verify the dominance of deciduous vegetation for natural coverage, as well as the areas of fragments of arboreal vegetation. However, the predominance of coverage and use is linked to agriculture. Thus, the behavior and sensitivity of the vegetation in the context of the study area proved to be relevant, so that its applications provide important information for environmental assessment for planning and management purposes.