Land Cover 15-Class
Description
This dataset classifies land cover at 10 m spatial resolution, with global coverage for custom time periods (> 3 months) from 2017 onwards. Pixels are assigned one of 15 land cover classes.
e7a24340…Usage notes
Data are delivered as composites of predictions made on Sentinel-2 observations over a date range. Custom date ranges are permitted, although annual composites are recommended to ensure sufficient Sentinel-2 observations for reliable predictions.
Variables
land_cover_class
Description
Index of the predicted land cover class. Predictions are made using a deep learning segmentation model trained to predict > 5 billion manually annotated land cover classifications from Sentinel-2 imagery.
Usage notes
Overall accuracy is 76% compared to a majority consensus. Lowest accuracy is for Flooded Vegetation (57%) and Rangeland (58%). Highest accuracy is for Crops (90%) and Water (87%).
| Index | Name | Description |
|---|---|---|
| 11 | Water Channel Extent | Full extent of water body under normal circumstances (i.e. outside of flooding or other exceptional events). Includes seasonal water bodies. |
| 12 | Variable Water | Intermittent water flow or standing water due to fluctuation in cover, weather events, or human activity. May also occur due to turbidity, algal blooms, ice cover, pollution, or glare. |
| 13 | Persistent Water | Permanent water flow or standing water. |
| 30 | Snow/Ice | Homogenous areas of permanent snow or ice. Typically only found in mountainous and high latitude regions. |
| 40 | Bare Ground | Rock, soil, or sand with little to no vegetation. |
| 61 | Sparse Rangeland | Vegetation mixes of grasses and/or sparse, short (< 5 m), woody scrub, with or without bare ground. May contain small isolated trees. |
| 62 | Dense Rangeland | Vegetation dominated by dense, short (< 5 m), woody scrub and little to no grass or bare ground. May contain small isolated trees. Can include lawns or fields when adjacent to built areas. |
| 80 | Flooded Vegetation | Any vegetation mixed with water throughout most of the year, including seasonally flooded areas. Thick mangrove, swamp, or seasonal wetland may fall under next-best-fit classes if water is not observed during the given time period. |
| 101 | Sparse Trees | Mainly tree canopy cover (> 5 m height), but with mixing of other vegetation or bare ground due to thin leaf cover or dispersed tree cover. Can indicate gain/loss of leaves or dying/growing trees. |
| 102 | Dense Trees | Dense tree canopy cover (> 5 m height) with little to no other vegetation or bare ground. |
| 141 | Inactive Cropland | Fallow or otherwise inactive fields, sometimes interspersed with small infrastructure. |
| 142 | Active Cropland | Actively growing cereals, grasses, irrigated pastures, or other human managed crops. |
| 172 | Low Density Built | Artificial impervious surfaces, buildings, and structures mixed with vegetation that cannot be disentangled at 10 m resolution. Typically represents low-density residential/suburban areas or path networks. |
| 174 | High Density Built | Artificial impervious surfaces, buildings, and structures with little to no mixed vegetation or bare ground. |
| 240 | Clouds | No land cover information due to persistent cloud cover. |
Pricing
A data request returns a temporal composite of the requested date range. Data acquisition costs are per hectare:
| Volume | Price |
|---|---|
| > 0 ha | $0.02 / ha |
Resources
Provider
Impact Observatory
www.impactobservatory.comImpact Observatory is a nature data analytics company based in Washington DC. Impact Observatory uses AI-based approaches to build land cover products that inform environmental analysis for governments, industries, and markets.