Free Satellite Imagery Sources Every GIS Analyst Should Know
Satellite imagery is one of the most powerful inputs in any GIS workflow. It drives land cover classification, change detection, environmental monitoring, disaster response, and urban planning. But access to high-quality imagery has historically come with a high price tag.
That has changed significantly over the last decade. Governments, space agencies, and open-data initiatives have made an enormous volume of satellite imagery freely available. The challenge today is not finding imagery. It is knowing which source fits your use case.
This article walks through the most valuable free satellite imagery sources available to GIS analysts, what each offers, and when to use them.
1. Landsat (USGS / NASA)
Landsat is the longest-running satellite imagery program in history, with continuous Earth observation data going back to 1972. It is operated jointly by USGS and NASA.
Key specifications:
- Spatial resolution: 30 meters (multispectral), 15 meters (panchromatic), 100 meters (thermal)
- Temporal resolution: 16-day revisit cycle
- Spectral bands: 11 bands (Landsat 8 and 9), including visible, near-infrared, shortwave infrared, and thermal
- Coverage: Global
What it is good for:
Landsat is the go-to source for long-term temporal analysis. Its archive depth makes it uniquely suited for studying land use change, deforestation, glacial retreat, urban expansion, and agricultural trends over decades. It is the standard for NDVI time series, burn scar mapping, and water body monitoring.
Where to access it:
- USGS EarthExplorer: earthexplorer.usgs.gov
- USGS LandsatLook: landsatlook.usgs.gov
- Google Earth Engine (as a managed dataset)
- Microsoft Planetary Computer
2. Sentinel (ESA Copernicus Programme)
The Sentinel satellite family is operated by the European Space Agency under the Copernicus programme. Multiple Sentinel missions exist, each designed for specific observation types.
Sentinel-2:
- Spatial resolution: 10 meters (visible and NIR), 20 meters (red edge, SWIR), 60 meters (atmospheric bands)
- Temporal resolution: 5-day revisit cycle (with both Sentinel-2A and 2B)
- Spectral bands: 13 bands
- Best for: Land monitoring, vegetation analysis, agriculture, coastal observation
Sentinel-2 is arguably the most widely used free imagery source for current-day land cover work. Its 10-meter resolution and 5-day revisit make it suitable for near-real-time analysis at a scale that Landsat cannot match.
Sentinel-1:
- Type: Synthetic Aperture Radar (SAR)
- Resolution: 5 to 20 meters depending on acquisition mode
- Best for: Flood mapping, soil moisture, subsidence monitoring, all-weather imaging
SAR imagery is cloud-independent, which makes Sentinel-1 invaluable in tropical regions with persistent cloud cover and in rapid-onset disaster scenarios.
Sentinel-3:
- Best for: Ocean color, sea surface temperature, fire radiative power
- Resolution: 300 meters to 1 kilometer
Where to access Sentinel data:
- Copernicus Data Space Ecosystem: dataspace.copernicus.eu
- Copernicus Open Access Hub (legacy): scihub.copernicus.eu
- Google Earth Engine
- Microsoft Planetary Computer
- AWS Open Data Registry
3. MODIS (NASA Terra and Aqua)
MODIS stands for Moderate Resolution Imaging Spectroradiometer. It is carried on NASA’s Terra and Aqua satellites and provides daily global coverage.
Key specifications:
- Spatial resolution: 250 meters, 500 meters, and 1 kilometer depending on the band
- Temporal resolution: Daily global coverage
- Spectral bands: 36 bands
What it is good for:
MODIS trades spatial resolution for temporal frequency. Its daily revisit makes it ideal for monitoring large-scale, fast-moving phenomena: wildfires, dust storms, algal blooms, and seasonal vegetation cycles. MODIS-derived products like the NDVI 16-day composite and the land surface temperature product are widely used in climate and ecological research.
At 250 to 1000-meter resolution, MODIS is not appropriate for local or site-level analysis. Think continental scale and regional scale.
Where to access it:
- NASA Earthdata: earthdata.nasa.gov
- NASA Worldview: worldview.earthdata.nasa.gov
- Google Earth Engine
- LP DAAC (Land Processes Distributed Active Archive Center)
4. VIIRS (Suomi NPP / NOAA-20)
VIIRS (Visible Infrared Imaging Radiometer Suite) is the successor to MODIS and is carried on the Suomi NPP and NOAA-20 satellites operated jointly by NASA and NOAA.
Key specifications:
- Spatial resolution: 375 meters (I-bands), 750 meters (M-bands)
- Temporal resolution: Daily global coverage
- Includes a day/night band (DNB) capable of detecting low-light emissions
What it is good for:
VIIRS is especially useful for nighttime lights analysis, which supports economic activity mapping, electrification monitoring, and disaster impact assessment. The VIIRS active fire product is widely used in near-real-time fire detection and is the data source behind NASA FIRMS (Fire Information for Resource Management System).
Where to access it:
- NASA FIRMS: firms.modaps.eosdis.nasa.gov
- NASA Earthdata
- NOAA CLASS (Comprehensive Large Array-data Stewardship System)
5. NASA Earthdata and the LP DAAC
NASA Earthdata is a centralized portal for all NASA Earth observation data. It provides access to hundreds of datasets spanning land, ocean, atmosphere, and cryosphere domains.
Within Earthdata, the LP DAAC (Land Processes Distributed Active Archive Center) is specifically focused on land surface data products derived from MODIS, VIIRS, ASTER, and Landsat. These are processed, analysis-ready products with documented quality flags and standard naming conventions.
If you need analysis-ready surface reflectance, land cover classification, or vegetation index products rather than raw imagery, LP DAAC is where to look.
Access: lpdaac.usgs.gov
6. Planet Labs (Education and Research Access)
Planet Labs operates the largest commercial constellation of small satellites, with daily imaging of the entire Earth at 3 to 5-meter resolution. While Planet is a commercial provider, it offers free access through several programs.
Free access programs:
- Education and Research Program: Available to students and researchers at accredited institutions. Provides access to PlanetScope imagery (3-meter daily).
- NICFI (Norway’s International Climate and Forests Initiative): Provides free access to Planet’s high-resolution tropical basemaps for organizations working on tropical forest monitoring. Data covers the tropics at 4.77-meter resolution, updated monthly.
The NICFI dataset in particular is a significant resource for anyone working on deforestation, land degradation, or REDD+ monitoring in tropical regions.
Where to access it:
- Planet Education and Research: planet.com/education
- NICFI data via Planet Explorer, QGIS plugin, or Google Earth Engine
7. OpenAerialMap
OpenAerialMap is an open registry of openly licensed aerial and satellite imagery contributed by organizations and individuals around the world. It focuses heavily on high-resolution imagery collected during and after disaster events.
The imagery on OpenAerialMap is typically very high resolution (sub-meter to 1 meter) and is made available under open licenses, meaning it can be freely used, shared, and built upon.
It is a critical resource for humanitarian response teams, particularly for imagery from the Humanitarian OpenStreetMap Team (HOT) and partner organizations following earthquakes, floods, and conflict events.
Access: openaerialmap.org
8. NOAA CoastWatch and Environmental Satellites
NOAA operates a range of satellites and provides free access to several imagery and data products particularly relevant to coastal and marine environments.
Key offerings:
- GOES-East and GOES-West: Geostationary weather satellites providing near-continuous imagery of the Western Hemisphere. Useful for weather monitoring, storm tracking, and fire detection.
- AVHRR (Advanced Very High Resolution Radiometer): Legacy sensor used for sea surface temperature and vegetation analysis.
- CoastWatch: A NOAA program providing satellite data tailored to coastal managers, including sea surface temperature, ocean color, and chlorophyll.
Access: coastwatch.noaa.gov, NOAA Environmental Visualization Laboratory (nnvl.noaa.gov)
9. Google Earth Engine Public Data Catalog
Google Earth Engine is not a satellite in itself, but it hosts one of the most extensive collections of free, analysis-ready satellite imagery and geospatial datasets in the world. Access is free for research, education, and nonprofit use.
The public data catalog includes Landsat (all missions), Sentinel-1, Sentinel-2, MODIS, VIIRS, SRTM, and dozens of derived products. All imagery is hosted on Google’s infrastructure and can be processed in the cloud without downloading anything.
For GIS analysts who are comfortable with JavaScript or Python, Earth Engine dramatically reduces the friction of working with large imagery archives. The Python client library (earthengine-api) integrates well with tools like GeoPandas, Folium, and the ArcGIS Python API.
Access: earthengine.google.com (requires registration for research/nonprofit use)
10. Microsoft Planetary Computer
Microsoft Planetary Computer is a cloud-based geospatial analysis platform that hosts a large catalog of open environmental datasets, including satellite imagery. It is built on STAC (SpatioTemporal Asset Catalog) standards, making it easy to query and access data programmatically.
Key datasets hosted:
- Landsat Collection 2
- Sentinel-2 L2A
- MODIS products
- NAIP (National Agriculture Imagery Program) for the United States
- Harmonized Global Land Use
The platform uses a Jupyter-based environment and integrates with Python tools like pystac-client, rasterio, xarray, and stackstac. It is particularly well suited to analysts building cloud-native, scalable imagery workflows.
Access: planetarycomputer.microsoft.com
Choosing the Right Source
The right imagery source depends on four variables: spatial resolution, temporal resolution, spectral depth, and the geographic extent of your area of interest.
| Use Case | Recommended Source |
|---|---|
| Long-term change detection (decades) | Landsat |
| Current land cover and vegetation analysis | Sentinel-2 |
| Near-real-time fire or flood mapping | Sentinel-1, VIIRS, MODIS |
| Nighttime lights analysis | VIIRS DNB |
| Tropical deforestation monitoring | Planet (NICFI) |
| Post-disaster high-resolution imagery | OpenAerialMap |
| Ocean and coastal monitoring | NOAA CoastWatch, Sentinel-3 |
| Large-scale cloud processing workflows | Google Earth Engine, Microsoft Planetary Computer |
Working with Free Imagery in ArcGIS
Most of these sources can be brought into an ArcGIS workflow through multiple pathways.
Esri provides Living Atlas layers that include Sentinel-2 imagery, Landsat imagery, and MODIS-derived products accessible directly in ArcGIS Online and ArcGIS Pro without any download. The Image Analyst extension in ArcGIS Pro supports multispectral analysis, band combination, and raster function chains on these datasets.
For custom workflows, the ArcGIS Python API supports raster analysis on imagery layers, and third-party libraries like rasterio, GDAL, stackstac, and xarray integrate well for processing downloaded tiles in Python environments.
Final Thoughts
Free satellite imagery has removed one of the biggest barriers to entry in geospatial analysis. The sources covered here represent years of investment by space agencies and governments in making Earth observation data a public good.
The skill lies not in finding imagery, but in selecting the right source for the task, understanding the preprocessing steps needed, and building efficient workflows that scale. A GIS analyst who knows these sources and how to work with them programmatically is operating at a significant advantage.
Start with the dataset best matched to your resolution and temporal needs, explore it in Google Earth Engine or Planetary Computer to avoid heavy local downloads, and integrate it into your ArcGIS or Python workflow from there.
The data is free. The insight is yours to derive.
