Posters

Abstract

The use of predictive models supported by remote sensing is emerging as a strategic tool for decision-making in the planning and development of renewable energy projects. A comprehensive methodology that integrates geotechnology, territorial intelligence, and Environmental, Social, and Governance (ESG) principles into the project development cycle is critical for addressing the challenges of planning and implementing wind projects within Brazil's complex land-tenure and environmental regulatory landscape. At the core of this methodology lies the Environmental Restrictions and Fragilities Mapping (MRA), a multi-stage framework designed to identify and mitigate socio-environmental impacts from the earliest stages of prospecting through to installation and operation. An important dimension of this process is the mapping of sensitive areas with potential impacts on Indigenous communities, applying criteria such as visual exposure, shadow flicker, and noise levels in the formulation of mitigation measures and spatial buffers. The scale of application is considerable: more than 1.95 million hectares have been mapped since the methodology’s inception, including 422,153 hectares in 2025 alone—equivalent to seven times the territory of Madrid. By embedding detailed environmental analysis into decision-making, this approach contributes to the development of renewable energy assets that balance technical efficiency with sustainability and constructive community relations. It illustrates a responsible pathway for large-scale infrastructure development, aligning project objectives with environmental stewardship and social accountability.