Generating Urban Forest Datasets from Satellite Imagery: Application to the City of São Paulo - Amazonas, Normando; Negri, Rogério; Nonato, Luis Gustavo (Anais da Conference on Graphics, Patterns and Images (SIBGRAPI), 2025)
The connection between urban forests and phenomena such as heat islands, air pollution, property values, and public perceptions of safety has been the subject of extensive research over the years. A fundamental requirement for such studies is the accurate mapping of the spatial distribution of green areas. In this context, this work presents a concise and reproducible framework to map urban forests and generate datasets detailing their location and distribution within metropolitan regions. The proposed methodology relies on freely available imagery from the CBERS-4A satellite and the open-source QGIS software. While auxiliary layers such as city layout and shadow masks are used during the modeling process, their purpose is solely to enhance the accuracy of urban forest classification, not to serve as final outputs. The true merit of this approach lies in its ability to identify urban tree cover patterns with high accuracy, making it a scalable solution for urban green infrastructure studies. The framework is applied to map urban forests in the central area of the city of São Paulo, Brazil.