Definição de regiões para caracterização e monitoramento da Represa de Várzea das Flores, Minas Gerais
DOI:
https://doi.org/10.26848/rbgf.v19.02.p787-813Keywords:
K-Medoids, SKATER, clustering, Várzea das Flores, turbidityAbstract
This study aimed to regionalize the Várzea das Flores reservoir, located in Minas Gerais, Brazil, using remote sensing and statistical methods for geospatial data analysis between 2017 and 2024. Inaugurated in 1972 to meet the growing water demand of the Metropolitan Region of Belo Horizonte, the reservoir currently faces water quality issues associated with land use and occupation in its watershed. To address this, the SKATER and K-Medoids clustering techniques were applied to group the water surface into homogeneous zones. The analysis was based on bathymetry, turbidity, and water surface temperature data. Surface temperature were derived from the thermal infrared bands of sensors onboard the Landsat satellite series. Bathymetry data were obtained from the Global Lakes Bathymetry Dataset (GLOBathy), and turbidity was estimated using semi-analytical models that combined Sentinel-2 satellite imagery and field samples. The K-Medoids method showed higher efficiency in grouping homogeneous zones, with three clusters selected based on the Elbow method and Silhouette Score criteria. Multivariate analysis of variance indicated significant seasonal differences among the zones. These results contribute to supporting management and conservation actions for the reservoir.
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Copyright (c) 1969 Vinícius Lima Guimarães, Antonio Miguel Vieira Monteiro, Eduardo Celso Gerbi Camargo, Milton Kampel

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