Understanding how land is being used on the Earth’s surface is a fundamental part of environmental research, agriculture planning, disaster management, water resource monitoring, and urban development. In recent years, high-resolution satellite-based land cover datasets have become freely available, allowing researchers, students, planners, and GIS professionals to use them without cost.
Among these, two datasets stand out due to their global coverage and 10-meter spatial resolution:
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ESRI Global Land Cover
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ESA WorldCover
Both look similar at first glance, but they have different strengths and use cases. Let’s explore each one, how they are made, and where they can be downloaded.
1. ESRI Global Land Cover
The ESRI Global Land Cover dataset is developed by Esri, in collaboration with Impact Observatory and Microso
ft AI for Earth. It uses deep learning models trained on large volumes of Sentinel-2 imagery to classify land cover into multiple classes like cropland, forest, grassland, built-up area, snow, barren land, and more.
Key Characteristics
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Spatial Resolution: 10 meters
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Available Years: 2017 to 2024
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Coverage: Entire globe
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Source Imagery: Sentinel-2 optical data
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Processing: AI-based image classification
Because the dataset is generated using AI models, ESRI continues to update it annually, making it especially useful for change detection and monitoring recent land cover shifts, such as urban expansion or agricultural pattern changes.
Why This Dataset Is Useful
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Ideal for time-series analysis (seeing how land use changes year to year)
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Works directly in ArcGIS, and can also be used in QGIS
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Great for regional monitoring, environmental assessments, and teaching GIS concepts
Access / Download Link
https://livingatlas.arcgis.com/landcover/
2. ESA WorldCover
The ESA WorldCover dataset is produced by the European Space Agency (ESA) as part of its land monitoring initiative. What makes this dataset special is the combination of Sentinel-1 (Radar) and Sentinel-2 (Optical) data. This helps improve accuracy in regions where clouds often block optical imagery — such as monsoon-affected and tropical regions (like much of India, Southeast Asia, and Africa).
Key Characteristics
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Spatial Resolution: 10 meters
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Years Available: 2020 and 2021
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Coverage: Entire globe
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Source Imagery: Sentinel-1 + Sentinel-2
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Processing: Hybrid satellite fusion + machine learning classification
Why This Dataset Is Useful
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Performs very well in vegetation and agricultural landscapes
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More stable and consistent classification — suitable for research and reports
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Excellent option for district-level land use analysis and crop area mapping
Download Links
| Access Format | Link |
|---|---|
| Direct Download (GeoTIFF / Tiles) | https://worldcover2020.esa.int/downloader |
| Google Earth Engine Dataset | https://developers.google.com/earth-engine/datasets/catalog/ESA_WorldCover_v200 |
Using Google Earth Engine makes it easy to:
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Clip to your study area
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Reclassify land cover
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Visualize and analyze time series
So, Which Dataset Should You Use?
| Purpose | Recommended Dataset | Reason |
|---|---|---|
| Detecting recent changes (new buildings, land clearing, crop shifts) | ESRI Land Cover | Updated regularly |
| Stable classification for research reports or academic publications | ESA WorldCover | More consistent and validated |
| Working in cloudy / monsoon-prone regions | ESA WorldCover | Uses Radar + Optical |
| Creating land use change animations (multi-year) | ESRI Land Cover | Available year-by-year |
The availability of high-resolution 10-meter global land cover is a major advantage for GIS and remote sensing users. Whether you are a student working on a project, a researcher analyzing environmental change, or a planner preparing land use assessments, both ESRI and ESA datasets offer reliable and free resources to support your analysis.
The best part — you don’t need expensive satellite data or paid subscriptions anymore.
Everything is accessible, open, and ready to use.
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