Maps on Demand
On-demand geospatial data to understand the places you care about
Our Land Use & Land Cover Maps on Demand
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).
Forest fires in 2020 ravaged Butte County, California, resulting in significant tree loss in the 2021 land-cover.
Comparing the maximum snow extent at austral winter 2020 and 2021 in the Andes mountains east of Santiago, Chile
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.
For detailed information of our Land Use & Land Cover's 9 classes, explore our behind the scenes section of our Automated Annual Global Maps product.
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Contact us today, if you are ready to see your map on demand come to life.
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Urban expansion highlights from the annual 2017 and 2021 LULC maps over Bujumbura, Burundi.