Sistema de informações geográficas e sensoriamento remoto visando modelagem de inundações e alagamentos em Recife, Pernambuco

Abstract

The aim of this study was to develop a Geographic Information System integrated with Remote Sensing, with a focus on modeling susceptibility to flooding in Recife, Pernambuco. Seven conditioning factors were selected: average daily rainfall, land use and occupation, urban density, proximity to water bodies, slope, hypsometry and pedology. This data was obtained from official sources and organized into a geospatial database, after being cleaned, processed, reclassified and normalized using fuzzy logic. The methodology was based on applying technical and bibliographic criteria to reclassify the variables into influence classes, enabling integrated spatial analysis in the GIS environment. Limitations were identified regarding the quality and updating of some layers, such as hydrography, digital terrain model and precipitation. The system developed, called SIGExtrem, provided efficient data visualization and integration, enabling the construction of thematic maps and support for urban risk management. The proposal proved to be effective and replicable, with the emphasis on the need for constant updates and the incorporation of complementary data, such as sea level and drainage infrastructure. The conclusion is that the combination of GIS and RS is an effective tool for predictive analysis of extreme weather events, contributing to urban planning and mitigation actions in contexts of increasing climate vulnerability.