# About Google Earth Engine

Google Earth Engine is a [Google Cloud product](https://cloud.google.com/earth-engine) for geospatial
analysis at scale. It combines a multi-petabyte catalog of satellite imagery and
geospatial datasets with planetary-scale computation to accelerate environmental
research and applications.

## Key Features

### Geospatial analysis, simplified and scalable

Earth Engine integrates an extensive geospatial [data
catalog](https://developers.google.com/earth-engine/datasets) with distributed computing, accessible through
client libraries. Users can access a wide range of satellite and environmental
data, as well as [incorporate their own datasets](https://developers.google.com/earth-engine/guides/image_upload). The platform
simplifies geospatial analysis by automatically handling data projection,
scaling, and compositing based on user-specified parameters. Its [analytical
functions](https://developers.google.com/earth-engine/guides/objects_methods_overview) operate efficiently across different scales without
requiring explicit data preparation steps or chunking. By managing complex data
processing and computational scaling internally, Earth Engine enables users to
focus on analysis rather than technical setup.

### Processing environments

Earth Engine supports [two modes of analysis](https://developers.google.com/earth-engine/guides/processing_environments):

- **Interactive mode**: For rapid real-time data exploration and visualization of small amounts of data.
- **Batch mode**: For large-scale computationally intensive tasks on large amounts of data.

### Development environments

Developers can choose between two primary development environments:

- **Python client library**: A flexible interface to Earth Engine for integration with the broader Python ecosystem, facilitating advanced workflows, and interactive analysis in Jupyter notebooks.
- **JavaScript Code Editor**: A dedicated web-based development environment for rapid prototyping, exploration, and Earth Engine App creation.

### Visualization and results

Earth Engine supports geospatial analysis from initial prototyping to final data
export. Its efficient tiling and computation system, integrated with interactive
map widgets, provides rapid visualization and inspection capabilities in both
the Code Editor and Python environments. This allows for immediate data
exploration and iteration. When ready, users can [export](https://developers.google.com/earth-engine/guides/exporting) raster
and vector results to Google Cloud Storage, BigQuery, or Google Drive, as well
as download data locally in formats compatible with pandas, NumPy, and Xarray.
Additionally, Earth Engine supports the creation of [interactive web
applications](https://developers.google.com/earth-engine/guides/apps), enabling users to share their geospatial insights with
a wide audience.

### Machine learning

[Machine learning tools](https://developers.google.com/earth-engine/guides/machine-learning) for regression, classification, image
segmentation, and accuracy assessment are built into Earth Engine. Once trained,
models can be saved and applied repeatedly. Classical ML workflows are
streamlined within Earth Engine's integrated system. For more advanced options
or externally trained models, integration with [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform) is
provided, allowing models to be brought to Earth Engine's data or enabling the
construction of deep learning models and neural network-based analyses.

## Access and management

Earth Engine is available for both [commercial](https://earthengine.google.com/commercial/) and
[noncommercial](https://earthengine.google.com/noncommercial/) use. Noncommercial use is offered free of
charge, while commercial use is subject to a [subscription fee and compute
charges](https://cloud.google.com/earth-engine/pricing). All computation and private data are associated with Google
Cloud projects, providing users with control over access, resource management,
and usage monitoring through the Google Cloud Console. This integration allows
for centralized project management, detailed billing information, and the
application of Google Cloud's robust security and compliance features. Users can
take advantage of Identity and Access Management (IAM) to [control
permissions](https://developers.google.com/earth-engine/cloud/access-control) and can [log activities](https://developers.google.com/earth-engine/guides/audit_logging) and [monitor
resource usage](https://developers.google.com/earth-engine/guides/monitoring_usage) with Cloud Monitoring and Cloud Logging.