IO uses a unique machine learning approach to classify land use and land cover (LULC) categories globally using Sentinel-2 imagery. Custom LULC results are available for any area of interest over user-specified time periods, beginning in 2018, and including the most recently available Sentinel-2 data. Results have an average accuracy of 85% (compared to human expert labels).
The LULC Map on Demand provides users with a custom map of land use/land cover for a user-specified area of interest and time period (2018-2022). The map is derived from ESA Sentinel-2 imagery at 10m resolution. It is a composite of LULC predictions for 9 classes over the specified time period (3 months or more is usually required for sufficient cloud-free scenes), generating a representative snapshot of LULC.