Binary impervious-surface maps at 10 m (Sentinel-2) or 3 m (PlanetScope) for stormwater, urban heat and flood-risk planning.

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IO Monitor Impervious Surfaces is a mapping product from Impact Observatory that shows which ground in a user-selected area is impervious (value 1) and which is pervious (value 0). Impervious cover drives stormwater runoff, urban heat and flood risk, and the provider positions the map as filling the gap between lower-resolution, out-of-date offerings and more costly map creation.
Each map is created from two inputs: Impact Observatory's land use and land cover (LULC) predictions and spectral data from satellite imagery for the same period. The result is a binary raster at the resolution of the source imagery: 10 m per pixel from Sentinel-2 or 3 m per pixel from PlanetScope. Maps are delivered as Cloud Optimized GeoTIFF files (8-bit, LZW compression, EPSG:3857) for a 120-day seasonal or 365-day window, with a stated revisit of 5 days where cloud-free imagery is available, so an area can be re-mapped to monitor change in impervious cover over time.
The provider names stormwater planning (assessing runoff from new development proposals), urban heat analysis (inputs to models used to cost greening and cooling interventions), urban planning and flood-risk management as uses, and shows example maps of Redmond (Washington), Bozeman (Montana), San Antonio (Texas) and Singapore. Maps are custom orders for an area of interest placed through the sales team; standard pricing covers areas up to 15,000 km², with tiered pricing for larger areas.
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Processing
Data Fusion & Analytics
Combines data sources and applies analytics to uncover patterns.
Delivered as
Data Distribution
Geographic Scope
Impact Observatory
Impact Observatory provides AI-powered geospatial monitoring: deep-learning models classify Sentinel-2 and PlanetScope satellite imagery into land use and land cover maps for custom areas and seasonal or annual date ranges. Its products include IO Monitor 10m and 3m land cover and impervious surface maps and IO Change Detection, and it publishes free annual 10m global land cover maps (Maps for Good). It is a Washington, DC based small business founded by former National Geographic Society staff.
2020
Founded
11-50
Team size
United States of America
Country
Provides processed data via standardised channels (APIs, feeds).