Google Earth Engine (GEE) Resources

Google Earth Engine (GEE) is a cloud-based platform that revolutionizes geospatial analysis by combining a vast catalog of satellite imagery and geospatial datasets with powerful analytical capabilities. This tool has become essential for researchers, scientists, and students across various disciplines at the University of Chicago.

Key Features

Data Catalog

• Petabytes of satellite imagery (Landsat, Sentinel, MODIS, etc.)
• Climate and weather datasets
• Global elevation and terrain data
• Nighttime lights and population data

Processing Capabilities

• Cloud-based processing
• Parallel computation
• Time series analysis
• Machine learning integration

Accessing GEE at UChicago

Eligibility

• Current UChicago faculty, staff, and students
• Must have a UChicago email address
• Research or academic use only

Getting Started

1. Sign Up

   • Visit Earth Engine Signup
   • Use your UChicago email
   • Select “University of Chicago” as your institution

2. Access Methods

   • Web-based Code Editor
   • Python API
   • JavaScript API

3. Authentication

   • OAuth 2.0 with UChicago credentials
   • Service accounts for automated workflows

Tutorials and Learning Resources

Getting Started

• GEE Documentation
• GEE Code Editor Guide
• GEE Python API Guide

UChicago-Specific Resources

• RCC GEE Workshop Materials
• Example Scripts Repository
• Tutorial Videos

Online Courses

• Coursera: GIS Data Acquisition
• edX: Big Data, Artificial Intelligence, and Ethics
• Google Earth Engine User Summit

Common Use Cases

Research Applications

• Land cover/land use change detection
• Time series analysis of environmental variables
• Natural hazard monitoring and assessment
• Agricultural monitoring and yield prediction
• Urban growth analysis

Example Code Snippets

Load and Display Landsat 8 Imagery

// Load a Landsat 8 image collection
var landsat = ee.ImageCollection('LANDSAT/LC08/C01/T1_SRT')
    .filterDate('2020-01-01', '2021-01-01')
    .filterBounds(geometry);

// Create a median composite
var composite = landsat.median();

// Display the composite
Map.addLayer(composite, {bands: ['B4', 'B3', 'B2'], min: 0, max: 3000}, 'Landsat 8');

Calculate NDVI

// Calculate NDVI from Landsat 8
var ndvi = composite.normalizedDifference(['B5', 'B4']).rename('NDVI');

// Add NDVI layer to map
Map.addLayer(ndvi, {min: -1, max: 1, palette: ['blue', 'white', 'green']}, 'NDVI');

Best Practices

Data Management

• Use appropriate scale and projection
• Be mindful of computation limits
• Export results when needed
• Clean up temporary assets

Performance Optimization

• Minimize the number of operations
• Use appropriate scale for analysis
• Leverage client vs. server operations
• Use appropriate data types

Reproducibility

• Document all processing steps
• Include metadata in exports
• Version control your scripts
• Share code and data when possible

Support and Help

UChicago Resources

• Research Computing Center (RCC)

  • Email: rcc-help@uchicago.edu
  • Office Hours: Tuesdays 2-4 PM (Zoom)
  • RCC Help Desk

• Library GIS Services

  • Email: gis@lib.uchicago.edu
  • Consultation Requests: Library GIS

Online Communities

• GEE Developer Forum
• GIS Stack Exchange
• GitHub Issues

Data Export and Integration

Export Options

• Google Drive
• Google Cloud Storage
• Asset export
• Direct download (small datasets)

Integration with Other Tools

• Python: earthengine-api, geemap
• R: rgee
• QGIS: GEE Plugin
• Jupyter notebooks

Training and Workshops

Upcoming Workshops

• Introduction to GEE (Monthly)
• Advanced GEE Analysis (Quarterly)
• GEE for Environmental Science (Fall Quarter)

Custom Training

• Departmental workshops
• Research group training
• One-on-one consultations

Policies and Compliance

Data Usage

• Follow data provider terms of service
• Attribute data sources properly
• Be aware of any redistribution restrictions

Compute Quotas

• Default processing limits apply
• Request quota increases for large projects
• Monitor your usage

Data Privacy

• Do not upload sensitive data
• Be aware of spatial resolution and privacy
• Follow UChicago data security policies

Case Studies

Urban Heat Island Analysis

• Used Landsat thermal bands
• Analyzed 10-year temperature trends
• Identified heat vulnerability hotspots

Agricultural Monitoring

• Monitored crop health
• Predicted yields
• Detected irrigation patterns

Deforestation Tracking

• Mapped forest loss
• Identified drivers of deforestation
• Monitored conservation areas

Additional Resources

Documentation

• GEE Developer Guide
• GEE API Reference
• GEE Data Catalog

Example Scripts

• GEE Code Editor Examples
• Awesome GEE
• GEE Community Tutorials

Related Tools

• Google Earth Studio
• Google Maps Platform
• Google Cloud Geospatial

Contact

For GEE-related questions and support:

• Email: gee-support@uchicago.edu
• Office: John Crerar Library, Room 134
• Hours: Monday-Friday, 10:00 AM - 4:00 PM