Silva, Sebastião Milton Pinheiro daTirello, Thiago Santoro Baptista2025-01-232025-01-232025-01-09TIRELLO, Thiago Santoro Baptista. Estimativas de parâmetros de qualidade da água (Índice de Estado Trófico - TSI) da Lagoa de Extremoz (RN) a partir do uso do sensoriamento remoto e da computação em nuvem.Orientação: Prof. Dr. Sebastião Milton Pinheiro da Silva. 2025. 73 f. Trabalho de Conclusão de Curso - TCC (Graduação em Geografia - Bacharelado) - Centro de Ciências Humanas, Letras e Artes, Universidade Federal do Rio Grande do Norte, Natal, 2025.https://repositorio.ufrn.br/handle/123456789/61865The Northeast region accounts for 3% of Brazil's surface water, constantly suffering from periods of water scarcity and severe droughts due to the semi-arid climate, which exposes the region to a situation of water supply vulnerability. The situation is not very different in RN, even though the state has a good network for supplying and distributing water extracted from the state's surface springs, which requires systematic monitoring of water quality by taking samples in the field in a costly, time-consuming and punctual scenario. With this process in mind, it was decided to evaluate the applicability of remote sensing to extract water quality parameters and calculate the Trophic State Index of the Extremoz Lagoon/RN using bio-optical algorithms applied to orbital images from the Sentinel 2 MSI satellite. Scenes from the years 2021, 2022 and 2023 were used and processed, and the results were compared with analyses obtained from field samples. The images were processed using the GEE platform. The results obtained were compatible, and the differences found were attributable to the fact that the samples were different, one being a point sample and the other a spatial, panoramic sample. The results obtained highlight the potential of remote sensing for water monitoring, as an alternative for managing water bodies in remote areas, as well as allowing a spatial and temporal analysis of the conditions of the water surface, even though quantitative data on chlorophyll-a and total phosphorus are not available for comparison. In addition, images without cloud cover may not be available at any given time. This research is expected to be a starting point for advances in the study of remote sensing applied to water management in the context of Rio Grande do Norte and the Brazilian semi-arid region.Attribution-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nd/3.0/br/Sensoriamento remotoGoogle Earth EngineÍndice de estado tróficoSentinelQualidade da águabachelorThesisCNPQ::CIENCIAS HUMANAS::GEOGRAFIA