Earth Engine
Public and private sector leaders can improve operations to become more sustainable by sourcing raw materials more responsibly and by analyzing and mitigating climate risks to their organizations.
If you would like to start using Earth Engine, click Get started.
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Originally launched more than a decade ago for research; now available for commercial use
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70+ petabytes of analysis-ready geospatial data
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Ability to integrate with powerful analytics and tools like BigQuery and Vertex AI
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Remains at no cost for nonprofit, noncommercial, and research projects; learn more
Benefits
Analysis-ready data
One-stop Earth observation data that is curated and analysis ready, including 900+ curated geospatial datasets, including near-real-time satellite imagery.
Powerful computation platform at scale
A powerful tool to analyze and visualize Earth data at scale. Parallel processing for speed and scale, with machine learning built in.
Trusted community
50,000 sustainability-focused monthly active users (and growing). Join the rich user community focused on sustainability, social and environmental impact.
Key features
Key features
Earth Engine public data catalog
Earth Engine's public data catalog provides more than 40 years of historical imagery and scientific datasets, including satellite data like Landsat, Sentinel-2, and MODIS, as well as geophysical, weather, climate, and demographic data.
Cloud Platform integration
Earth Engine is integrated with Google Cloud, enabling provisioning and permissions to be configured and monitored like other Google Cloud services.
Compute
Leverage Google Cloud to process petabytes of data with zero configuration or server management.
API
Full-featured JavaScript, Python, and REST APIs.
Code Editor
Web-based IDE for writing and running scripts. Ideal for prototyping and iteration.
Customers
Customers
Google Earth Engine has a long history of enabling environmental and social impact.
Documentation
Documentation
Google Cloud integration
Learn how to quickly get Earth Engine running through a Google Cloud project and environment of your choice using our quickstart guides.
Tutorials
Get an introduction to using the Earth Engine JavaScript API for advanced geospatial analysis.
Full-featured JavaScript, Python and REST APIs.
Use client libraries to create and manage Compute Engine resources in Go, Python, Java, Node.js, and other languages.
Use cases
Use cases
Enable global supply chain transparency and traceability to footprint.
Understand climate risk exposure for operations and investments (for example, flood, wildfire, drought, etc).
Monitoring crop health and productivity, reducing pesticide and fertilizers, and evaluating the effectiveness of sustainable agriculture practices.
Enable sustainable forest management and monitor land cover change and climate events response.
All features
All features
| Data catalog with 900+ analysis-ready, geospatial datasets | Easy access to a wide variety of data including near-real-time satellite imagery and curated scientific datasets that allow you to rapidly test new hypotheses and quickly respond to requests. |
| Deep time series of data | Easy access to a long time series of data that will give you better insight into long-term change and variation. It also enables better predictions and risk assessment. |
| Processing speed | Fast production of results enables timely answers to critical questions, and faster responses to requests, hypothesis testing, and product development. |
| Processing scale | Ability to work with massive volumes of data to produce large-scale results and/or work with deep time series of data. |
| Fully managed service | No need to manage backend infrastructure, so you can focus resources on geospatial expertise instead of backend software development. |
| Code Editor | Web-based IDE coding environment focused on hypothesis testing enables you to test new hypotheses and quickly respond to requests. |
| Client libraries with hundreds of functions | Includes JavaScript and Python wrapper functions to translate complex geospatial analysis into Earth Engine requests. Flexibility in defining analysis to test a wide range of hypotheses and develop a wide range of analyses. |
| Interactive applications | Create interactive experiences of analyses with Earth Engine’s library of UI components. Share geospatial tools with non-coders and deliver insights into the hands of decision-makers. |
| Active user ecosystem | Deeply knowledgeable community of users to interact with to help solve problems faster and apply best-in-class methods. |
| Integration with machine learning tools | Build geospatial ML models to derive better geospatial insights and spend less effort building data pipelines. |
Pricing
Pricing
The pricing model is based on consumption of Earth Engine
resources (compute units and storage) and a monthly
subscription fee. Earth Engine Compute Units (EECUs) consist
of Earth Engine managed workers used to execute customer
tasks. There are two kinds of EECUs: “Batch” and “Online.”
Batch EECUs are typically used for very large jobs (for
example, exports), and online EECUs provide near-real-time
responses in the Code Editor, apps, etc. One EECU-hour is an
online or batch managed worker executing customer tasks for
one hour. Earth Engine automatically records the number of
EECUs used to complete an analysis as requests are
processed.
Partners
