Geospatial Intelligence Powering a New Era of Land Use Planning in Brazil

Brazil’s Data Cube and AI-Based Land Analysis Set New Standards for Global Land Administration

Brazil is emerging as a global leader in the application of geospatial intelligence to land governance, with a groundbreaking initiative that combines satellite data infrastructure and artificial intelligence. The methodology, built around the Brazil Data Cube (BDC) and object-based image analysis (GEOBIA), is transforming how the country monitors land use, manages cadastral information, and enforces environmental compliance.

High-resolution satellite view of Plano Piloto and Lago Paranoá in Brasília, Brazil, captured by Sentinel-2’s Multispectral Instrument (MSI). With its 13 spectral bands, MSI enables detailed land and water analysis — data that feeds into initiatives like the Brazil Data Cube (BDC). Developed by INPE, BDC leverages this imagery to power AI-driven land use monitoring and support environmental compliance across Brazil’s evolving landscape.

Sao Jose dos Campos, Brazil — Developed by the National Institute for Space Research (INPE), the Brazil Data Cube is an open-access platform that collects and organises vast quantities of satellite imagery into spatial-temporal grids. This structure allows for time-series analysis of land changes — tracking everything from agricultural expansion to deforestation with remarkable granularity.

Complementing this is GEOBIA, a technique that interprets satellite images not as individual pixels but as contextual “objects” — like crop fields, forest edges, or water bodies. These objects are automatically classified using AI-trained models that detect subtle shifts in land patterns.

“The Brazil Data Cube provides the infrastructure, and GEOBIA provides the intelligence,” says Dr. Gilberto Câmara, a leading geospatial scientist. “Together, they allow us to monitor land use dynamically, with the kind of precision that was unimaginable a decade ago.”

The results are striking. In recent pilots across Mato Grosso and Pará, two of Brazil’s most ecologically active states, the system distinguished between legal and illegal land conversions, pasture development, and crop cycles — all with over 90% classification accuracy.

The implications for land administration are equally significant. Municipal and federal agencies are integrating these maps into their cadastral databases, improving taxation, enforcing land-use regulations, and enhancing land tenure security. In regions where conventional field surveys are slow or impractical, this approach offers a scalable and affordable alternative.

Participants attend a workshop during FOSS4G 2024 in Belém, where the Brazil Data Cube (BDC) team demonstrated cutting-edge tools for satellite image time series analysis and Earth Observation data cubes. As highlighted in Brazil’s new geospatial strategy, BDC powers AI-driven land monitoring that is revolutionising land use planning, cadastral management, and environmental compliance across Brazil and beyond.

Importantly, the technology aligns with Brazil’s Forest Code, which mandates that rural landowners preserve certain proportions of native vegetation. The Brazil Data Cube enables automated compliance monitoring, allowing both landholders and environmental agencies to verify legal land use remotely and transparently.

The model has attracted global attention. Several countries in Latin America, Africa, and Southeast Asia are studying Brazil’s approach as a template for building their own data infrastructures. Organizations such as the World Bank and FAO are exploring how to adapt the system for smallholder farm mapping and land rights verification.

Notably, the BDC’s open-source design enhances its global relevance. With its emphasis on data accessibility, interoperability, and AI integration, the initiative stands out as a democratic and scalable solution for modern land governance.

As land becomes an increasingly scarce and contested resource, Brazil’s approach offers a timely roadmap. By fusing remote sensing, machine learning, and spatial policy frameworks, the country is showing the world how to make land administration smarter, fairer, and faster.