Land Cover (MapBiomas)
Annual land cover classification from MapBiomas, derived from satellite imagery and machine learning, tracking changes in landscapes since 2000.
Description
This indicator, developed by MapBiomas, provides annual, high-resolution information on land cover and land use change. It is produced through a collaborative initiative focused primarily on South America, combining satellite imagery with machine learning classifiers to generate consistent, accurate maps of land cover.
The classification allows monitoring of environmental, social, and policy-relevant landscape changes over time. It improves ecosystem monitoring for conservation and supports sustainable planning by offering adaptable tools that can be applied in multiple contexts with high precision.
What it measures
- Land cover classes (e.g., forest, agriculture, urban, water).
- Changes in extent and condition of land cover over time.
- Landscape transformation from 2000 to 2022 at 30 m resolution.
How to interpret
- Provides spatially explicit land cover classes per year.
- Changes in land cover reveal pressures such as deforestation, agricultural expansion, or urbanisation.
Unit / Scale
Classes (categorical).
Temporal coverage: 2000–2022.
Spatial resolution: 30 m.
Update frequency: Annual.
Author / Source
MapBiomas.
🔗 https://mapbiomas.org/en
📄 Souza et al. (2020). Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine. Remote Sensing, 12(17), 2735.
Applications in Atlas
- Detect and quantify land-use and land-cover change over two decades.
- Support deforestation monitoring, restoration, and land management strategies.
- Provide baseline data for biodiversity, carbon, and ecosystem service assessments.
- Strengthen conservation and policy design with robust land cover evidence.