Introduction
Google Earth Engine (GEE) has revolutionized the way researchers, scientists, and developers access and analyze geospatial data. Building upon our previous exploration of GEE’s capabilities, this comprehensive guide delves into the vast array of datasets available within Earth Engine’s catalog. Understanding the breadth and depth of available data is crucial for maximizing the platform’s potential in your geospatial analysis projects.
The Scale of Earth Engine’s Data Catalog
The Earth Engine data catalog represents one of the largest publicly available collections of Earth observation data, containing over 90 petabytes of analysis-ready satellite imagery and more than 1,000 curated geospatial datasets. This massive repository spans more than 50 years of historical imagery, updated and expanded daily, with resolutions as fine as one meter per pixel. The catalog offers comprehensive global coverage, enabling users to understand Earth changes relevant to sustainability, climate monitoring, and environmental research goals.
Major Dataset Categories in Google Earth Engine
1. Satellite Imagery Collections
Landsat Program Data
The Landsat program provides the longest continuous satellite-based observation record of Earth’s surface, dating back to 1972. Earth Engine hosts the complete EROS (USGS/NASA) Landsat catalog, including:
- Landsat 5, 7, and 8 Collections: Raw imagery and surface reflectance products
- Landsat Collection 2: The most recent processing version with improved geometric accuracy
- Surface Reflectance Products: Atmospherically corrected data that removes atmospheric interference effects
Sentinel Satellite Data
The European Space Agency’s Copernicus program contributes several high-quality datasets:
- Sentinel-1: C-band Synthetic Aperture Radar (SAR) data for all-weather monitoring
- Sentinel-2: High-resolution optical imagery with 10-20 meter resolution, ideal for land monitoring
- Sentinel-3: Ocean and land monitoring with specialized sensors
- Sentinel-5P: Atmospheric monitoring for air quality assessment
MODIS Collections
The Moderate Resolution Imaging Spectroradiometer (MODIS) provides global coverage with high temporal frequency:
- Terra and Aqua MODIS: Land surface temperature, vegetation indices, and ocean color data
- MOD13Q1/MOD13A1: Vegetation indices at 250m and 500m resolution
- MOD21A1D/MOD21A1N: Day and nighttime land surface temperature products
2. Climate and Weather Datasets
ERA5 Reanalysis Data
The European Centre for Medium-Range Weather Forecasts (ECMWF) provides comprehensive atmospheric reanalysis:
- ERA5 Hourly: Complete atmospheric state variables with global coverage
- ERA5 Daily Aggregates: Daily summaries of key meteorological parameters
- ERA5-Land: Enhanced resolution land surface variables
GRIDMET and Climate Datasets
- GRIDMET: High spatial resolution (~4-km) daily surface meteorological data for the contiguous United States
- GLDAS: Global Land Data Assimilation System providing land surface model outputs
- PRISM Climate Dataset: 800m resolution climate data for the United States
- Global Daily Air Temperature: 1-km resolution temperature data (2003-2020)
3. Digital Elevation Models and Terrain Data
Global Elevation Products
Earth Engine provides several high-quality digital elevation models:
- SRTM (Shuttle Radar Topography Mission): 30-meter resolution global DEM
- ASTER GDEM V3: Global 30-meter resolution elevation data
- Copernicus DEM: Available in 10m, 30m, and 90m resolutions
- FABDEM: Forest and Buildings removed DEM for more accurate terrain representation
Derived Terrain Products
- HydroSHEDS: Hydrological derivatives from SRTM data
- WWF Terrestrial Ecoregions: Global ecosystem classification
- Slope and Aspect: Automatically calculated terrain derivatives
4. Land Cover and Land Use Data
Global Land Cover Products
- ESA WorldCover: Global land cover at 10m resolution using Sentinel data
- Dynamic World: Near real-time land use/land cover classification
- MODIS Land Cover: Annual global land cover classifications
- ESA WorldCereal: Global crop mapping and active cropland identification
Regional Specialized Products
- USDA NASS Cropland Data Layers: Detailed crop classification for the United States
- EUCROPMAP: European crop type mapping using Sentinel data
- Global Food Security-Support Analysis Data (GFSAD): Cropland extent and characteristics
5. Vegetation and Forest Monitoring Data
Vegetation Indices
- MODIS Vegetation Indices: 16-day NDVI and EVI products at multiple resolutions
- GIMMS NDVI: Long-term vegetation monitoring dataset (1982-2022)
- Landsat-derived indices: NDVI, EVI, and other vegetation health indicators
Forest-Specific Datasets
- Global Forest Change: Annual forest loss and gain mapping by Hansen et al.
- GEDI Ecosystem Dynamics: Vegetation structure metrics from NASA’s GEDI LiDAR
- Forest/Non-Forest maps: Binary forest classification products
6. Water and Ocean Datasets
Surface Water Monitoring
- JRC Global Surface Water: Historical water presence and changes (1984-2020)
- Global Surface Water Transitions: Water persistence and seasonal variations
Ocean and Marine Data
- Ocean Color Products: Chlorophyll-a concentration and ocean productivity
- Sea Surface Temperature: Global gridded SST from multiple sensors
- GLODAP: Ocean biogeochemistry data with over 1.4 million water samples
- Ocean Color SMI: MODIS and SeaWiFS ocean color data
7. Population and Socioeconomic Datasets
Population Data
- WorldPop Global Population: High-resolution population estimates at 100m resolution
- Gridded Population of the World (GPW): Global population counts and density
- Global Urban and Rural Settlement Dataset (GURS): Urban-rural classification at 100m resolution
Administrative Boundaries
- geoBoundaries: Global political administrative boundaries at multiple levels
- Large Scale International Boundary (LSIB): Country boundaries from the US State Department
- Global Administrative Unit Layers (GAUL): FAO administrative boundaries
8. Agriculture and Food Security Data
Crop Monitoring
- MODIS Crop Calendar: Growing season timing and patterns
- Crop Dominance Mapping: Identification of primary crop types
- Agricultural Land Systems: Farming system classifications
Food Security Indicators
- Normalized Difference Vegetation Index (NDVI): Crop health monitoring
- Enhanced Vegetation Index (EVI): Improved vegetation assessment
- Crop yield estimates: Statistical crop production data
9. Disaster and Hazard Monitoring Data
Natural Disaster Datasets
- MODIS Fire and Thermal Anomalies: Global fire detection and monitoring
- Global Flood Database: Historical flood extent mapping
- Drought Indices: GRIDMET-based drought monitoring for CONUS
- Cyclone and Storm Tracking: Historical tropical cyclone data
Risk Assessment Data
- Landslide susceptibility mapping: Terrain-based risk assessment
- Earthquake hazard data: Seismic risk indicators
- Coastal vulnerability: Sea-level rise impact assessments
10. Specialized and Community Datasets
Night-time Lights
- DMSP-OLS: Long-term nighttime lights data (1992-2013)
- VIIRS DNB: High-resolution nighttime lights from 2012-present
- NPP-VIIRS-like: Harmonized nighttime light products
Transportation Infrastructure
- Global Roads Inventory Project (GRIP): Global roadways database
- Global Power System Data: Transmission lines and electrical infrastructure
- OpenStreetMap: Vector data including roads, buildings, and infrastructure
Applications Across Different Domains
Environmental Monitoring
The comprehensive dataset collection in Google Earth Engine enables robust environmental monitoring applications. Climate researchers utilize ERA5 reanalysis data combined with MODIS temperature products to track global warming patterns and temperature anomalies. Forest monitoring projects leverage the Global Forest Change dataset alongside Sentinel-2 imagery to assess deforestation rates and forest degradation in near real-time.
Agricultural Applications
Agricultural scientists and practitioners benefit from the extensive crop monitoring capabilities provided by datasets such as MODIS vegetation indices, Landsat-derived NDVI products, and the USDA NASS Cropland Data Layers. These resources enable precision agriculture applications, crop yield forecasting, and sustainable farming practice monitoring across different scales from individual farms to global food security assessments.
Urban Planning and Development
Urban planners and policymakers utilize population datasets from WorldPop, administrative boundaries from geoBoundaries, and nighttime lights data from VIIRS to understand urbanization patterns, plan infrastructure development, and assess economic activity. The integration of building footprint data with demographic information provides valuable insights for sustainable urban development strategies.
Disaster Risk Reduction
Emergency management professionals rely on multiple datasets for comprehensive disaster risk assessment and response. MODIS fire detection products combined with weather data enable wildfire risk mapping, while flood monitoring applications utilize surface water datasets alongside elevation models to predict flood-prone areas and assess post-disaster impacts.
Data Quality and Reliability
Standardization and Processing
Google Earth Engine datasets undergo rigorous quality control and standardization processes to ensure consistency and reliability. Most satellite imagery collections are provided in Analysis Ready Data (ARD) format, meaning they have been geometrically corrected, radiometrically calibrated, and often atmospherically corrected. This standardization eliminates many preprocessing steps traditionally required in remote sensing workflows.
Temporal Consistency
The platform maintains temporal consistency across dataset collections, ensuring that long-term trend analysis and time-series studies can be conducted with confidence. Historical data archives are regularly reprocessed using updated algorithms to maintain consistency with newer acquisitions, providing seamless temporal coverage for multi-decade studies.
Conclusion
Google Earth Engine’s extensive dataset catalog represents an unprecedented resource for Earth observation and geospatial analysis. From historical Landsat archives spanning five decades to cutting-edge real-time monitoring products, the platform provides researchers and practitioners with the data infrastructure needed to address complex environmental and societal challenges.
The diversity of available datasets—encompassing satellite imagery, climate data, elevation models, population statistics, and specialized thematic products—enables comprehensive multi-disciplinary research approaches. As the catalog continues to grow through both institutional partnerships and community contributions, Earth Engine solidifies its position as the premier platform for planetary-scale geospatial analysis.
Understanding the breadth of available datasets and their characteristics is essential for maximizing the analytical potential of Google Earth Engine. Whether conducting climate research, agricultural monitoring, disaster management, or urban planning studies, the rich data resources within Earth Engine provide the foundation for evidence-based decision making and scientific discovery.
References :
- 1. Google Earth Engine Data Catalog – https://developers.google.com/earth-engine/datasets/catalog
- 2. Google Earth Engine Developer Guide – https://developers.google.com/earth-engine
- 3. Copernicus Open Access Hub – https://scihub.copernicus.eu/
- 4. Google Cloud Earth Engine – https://cloud.google.com/earth-engine
- 5. Awesome GEE Community Catalog – https://gee-community-catalog.org
- 6. USGS Earth Resources Observation and Science (EROS) Center – https://www.usgs.gov/centers/eros
- 7. NASA Earth Science Data – https://earthdata.nasa.gov/
- 8. Spatial Thoughts GEE Course – https://courses.spatialthoughts.com/end-to-end-gee.html
LinkedIn: https://www.linkedin.com/in/suyash-bhosale-544077225
