ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-3/W4-2025
https://doi.org/10.5194/isprs-annals-X-3-W4-2025-113-2026
https://doi.org/10.5194/isprs-annals-X-3-W4-2025-113-2026
13 Mar 2026
 | 13 Mar 2026

Using Brazil Data Cube and Satellite Image Time Series to map Land Use and Land Cover around the reservoir of the Batalha Hydroelectric Power Plant, Goiás (Brazil)

Izaias de Souza Silva, Felipe Carvalho de Souza, Diego Tarley Ferreira Nascimento, Cláudio Aparecido de Almeida, Luciana Souza Soler, and Marta Pereira da Luz

Keywords: Satellite Image Time Series, Soil Protection, Intensive Agricultural Lands, Hydroelectric dams

Abstract. Accurate Land Use and Land Cover (LULC) maps support the analysis of land use dynamics and provide a scientific basis for land management around water reservoirs. In recent years, technological advancements have led to significant improvements in the methodological design of these mappings. In the context of large-scale Earth Observation (EO) data, satellite image time series (SITS) represent a powerful approach for capturing and measuring surface changes. This study aimed to map LULC in a contributing watershed of the Batalha Hydroelectric Power Plant reservoir, located in eastern Goiás, Brazil. We used the Sentinel-2/MSI time series from Brazil Data Cube (BDC) for the agricultural year (July 2022 to June 2023). The classification included ten classes: Forest Formations, Savanna Formations, Grass Formations, Silviculture, Pasture, Single-Cycle Agricultural Crops, Multi-Cycle Agricultural Crops, Edification, Seasonally Flooded Areas, and Water. We used the Random Forest algorithm and the best practices for assessing mapping accuracy. The results demonstrate the potential of SITS for mapping LULC conditions around water reservoirs. The LULC map generated provides valuable information for managing land use around the reservoir, with a focus on areas where seasonal slope exposure occurs along the immediate reservoir edge. Mapping these areas represents a significant gain in information, as it contributes to the monitoring of sites susceptible to mass movements and marginal erosion processes.

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