Avaliação de área de segurança hídrica por meio de modelagem computacional e estatística com imagens de sensoriamento remoto

• Ano de defesa: 2025
• Autor(a) principal: Fernandez, Basílio Fernandez
• Orientador(a): Zebende, Gilney Figueira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual de Feira de Santana
• Programa de Pós-Graduação: Programa de Pós-Graduação em Modelagem em Ciências da Terra e do Ambiente
• Departamento: DEPARTAMENTO DE CIÊNCIAS EXATAS
• País: Brasil
• Palavras-chave em Português: Dimensão fractal; Machine Learning; Pedra do Cavalo; Bandas espectrais; Macrófita em lago
• Palavras-chave em Inglês: Fractal dimension; Machine learning; Pedra do Cavalo; Spectral bands; Lake macrophytes
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS
• Link de acesso: http://tede2.uefs.br:8080/handle/tede/1966

This Thesis analyzed land use and land cover (LULC) within a water security area over a 30-year period, focusing on a polygon encompassing the Pedra do Cavalo Environmental Protection Area (EPA), its reservoir, and regions adjacent to the EPA, located in Bahia, Brazil. Descriptive statistics were performed on the areas of the main LULC classifications produced by MapBiomas, and fractal dimensions were estimated for each class. This approach allowed the inference of alternations between the relative values of forest and agricultural classes, as well as comparisons between different classes using the fractal dimension. Within the same polygon, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) were estimated, identifying time scales related to annual climatic processes affecting vegetation cover - particularly forest and agricultural classes. Furthermore, drought-related effects were observed in the region, as reflected in the amplitude values of the near-infrared (NIR) band between 2018 and 2019, a result also highlighted in the fractal dimension analysis. Subsequently, autocorrelation was examined using Detrended Fluctuation Analysis (DF A), and cross-correlation was assessed through the Detrended Cross-Correlation Coefficient (ρDCCA) between spectral bands (red, blue, and NIR) from Landsat satellites 5, 7, and 8 - used in the calculation of the aforementioned indices - over a period of six years and ten months. A nearly perfect crosscorrelation was found between these indices at time scales equivalent to 30 satellite revisits over the study region. Finally, a third study investigated the occurrence of macrophyte banks using Sentinel-2 L2A satellite imagery. The presence of these aquatic plant species has implications for lake trophic status and poses operational challenges for both water treatment plants and the hydroelectric power plant located within this water security area.