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Remote Sensing with Google Earth Engine

Remote Sensing is the art of digital image processing. It is not merely a technological endeavor. It's a harmonious blend of cutting-edge technology and human wisdom, aiming to unravel the intricate layers of our planet. It promotes a deeper understanding of the Earth's system and fosters an innovative approach to geographic studies. The confluence of sensors, artificial intelligence, big data, and human intellect offers a dynamic and flexible framework, making remote sensing an indispensable tool in modern geography and related fields. This approach embodies the spirit of integration, innovation, and human-centered discovery, paving the way for a more informed and sustainable future.

Schedule

Week	Topic	Readings	Labs
0	Welcome to Remote Sensing	Welcome to Remote Sensing The Earth Engine API Why JavaScript	Lab 1 - Getting Started with GEE Lab 2 - Hello LandSat!
1	JavaScript Basics Additive Color System	Introduction to JavaScript Variables Lists Objects Functions Comments Introduction to Additive Color System	Lab 3 - JS Basics Lab 4 - Night time Lights Lab 5 - Challenge Refreshers
2	Image Collections Image Manipulation: Band Arithmetic and Thresholds	Image Collections Google Earth Engine Data Catalogs Image Manipulation: Band Arithmetic and Thresholds Spectral Indices NDVI	Lab 6 - Image Collections / Filtering / Sorting Lab 7 - Challenge - Finding a dataset for your Site Lab 8 - Band Arithmetic - NDVI Lab 9 - Thresholds Lab 10 - Challenge - Mapping the Urban Areas
3	Land Cover Classes and Supervised Classification Unsupervised Classification	Introduction to Image Classification Discrete vs Continuous Data Unsupervised vs Supervised vs Object Based Land Use Versus Land Cover History of Image Classification Unsupervised Classification	Lab 11 - Supervised classification Lab 12 - Unsupervised Classification Lab 13 - Improving your Classifications
4	Interoperability, Elevation Modeling, Visualizations, and Reducers		Lab 14 - Interoperability with GEE - Exporting to ArcGIS Pro Lab 15 - Visualizing SRTM Data Lab 16 - Zonal Statistics
5	Remote Sensing Applications Case Studies	Remote Sensing Applications Case Studies	Lab 17 - Health Applications Part 1 - Preparing Data for Analysis Lab 18 - Health Applications Part 2
6	Engaging with the Public	Engaging with the Public	Lab 19 - Making Gifs and Videos of Environmental Change Lab 20 - Design UI/UX and Deploying Google Earth Engine Apps
7	RS Application 1 - River Morphology	Theory Part 1 Part 2 Part 3 Part 4 Part 5 RivWidthCloud
8	RS Application 2 - Global Snow Observatory	Introduction About MODIS Our Process Creating Image Collections Joining Collections Masking Reclassifying Calculating Snow Cover Frequency Trend Analysis Visualization Disseminating
9	RS Application 3 - Heat Islands	Introduction Data Analysis Results Discussion Conclusion
10	RS Application 4 - Fire	Introduction Theory Fire Datasets About the Fire Adding Data & Making a UI
11	Future Directions in Remote Sensing	Overview Bibliography
—	Research Methodology	Doing Research with Remote Sensing
12	Summary & Review of RS Applications	River Morphology Global Snow Observatory Heat Islands Fire

All Labs

Getting Started

JavaScript & Visualization

Image Analysis

Classification

Advanced Analysis

Applications & Deployment

Remote Sensing Applications

Research & Future Directions

Supplementary Materials

Assignment Submission

How to Submit Your Work

All lab assignments and projects should be submitted via email.

Submit lab via email.

Submission Guidelines:

Subject line should include: Lab [Number] - [Your Name]
For Google Earth Engine scripts, include the shareable link from GEE Code Editor
For written assignments, attach as PDF
Include screenshots demonstrating your work where applicable
Submit before the deadline specified in the course schedule