Urban Greening and Climate Resilience Through AI-Powered Reforestation

To combat rising temperatures, Rio de Janeiro has implemented an innovative reforestation plan that began in January 2024. The city, known for its culture and natural beauty, faces challenges such as heat waves, flooding, and landslides, making sustainable solutions more urgent than ever.

In partnership with MORFO, the city is running a reforestation project as part of the ReflorestaRio program, an initiative aimed at mitigating the effects of climate change by accelerating forest recovery in hard-to-reach areas using artificial intelligence and drone technology.

The project was officially launched on July 5, 2024, with the first scattering of MORFO’s native species seeds in Serra de Inhoaíba, in the presence of Mayor Eduardo Paes, Secretary for the Environment and Climate Eliana Cacique, and Deputy Secretary for Biodiversity Hélio Wanderley.

Since then, the project has expanded operations to other strategic areas across the city.

CHALLENGES

‍Difficult terrain: Steep slopes make traditional planting methods impractical, requiring drones for safe and efficient seed dispersal.

Extreme climate: High temperatures and severe weather conditions pose challenges for the growth and survival of new vegetation.

Biodiversity and soil health: The project includes detailed soil analyses and a careful selection of native species to ensure effective restoration and ecological balance.

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DEPLOYMENTS

The project aims to reforest 30 hectares and enrich an additional 30 hectares with native Atlantic Forest species by 2027.

Continuous monitoring: MORFO will oversee the regeneration of 100 hectares of restored land in Serra de Inhoaíba and other project areas.

PROJECT MONITORING

The reforestation efforts span four key areas: Serra de Inhoaíba, Serra da Posse, Serra do Quitungo, and Serra do Cantagalo. At each stage, soil conditions, biodiversity, and vegetation growth are analyzed.

Multispectral drones provide detailed aerial assessments, while permanent sample plots allow for long-term ecosystem monitoring.