Classes in bold denote classes dedicated to intensive coding skill-building

Class Week Topic In Class Readings Due
1 1 What is Remote Sensing? What are Natural Hazards?      
2 2 History of remote sensing, critical remote sensing, natural hazards basics   The politics of pixels: A review and agenda for critical remote sensing, There’s No Such Thing as a Natural Disaster Make a Google Earth Engine Account
3 2 Working with Academic Articles, Google Earth Engine Data Catalog   UNC Libraries: What is a Peer Reviewed Article  
4 3 Introduction to JavaScript and GEE API Ex 1: Introduction to Javascript, Ex 2: Introduction to GEE API Watch Introduction to Google Earth Engine Lecture Ex. 1-2
5 3 Electromagnetic Spectrum   Watch Introduction to the Electromagnetic Spectrum Lecture (until 14:31), Chapter 1 in Introduction to Remote Sensing  
6 4 Working with Images, Working with Image Collections Ex 3: Working with Images, Ex 4: Working with Image Collections End-to-End Google Earth Engine 1.02-1.05 Ex. 3-4
7 4 Satellites, Sensors, resolution   Watch From Pixels to Products (25:18-35:56), Satellites, Sensors, and Properties  
8 5 Visualizing Single Bands, Visualizing Multiple Bands Ex 5: Visualizing Single Bands, Ex 6: Visualizing Multiple Bands Raster Interpretation and Visualization Ex. 5-6
9 5 Color Theory, Composites   Interpreting Remote Sensing Imagery  
10 6 Mosiacs and Composites, Feature Collections Ex 7: Mosaics and Composites, Ex 8: Feature Collections, Clipping, Exporting Data   Ex. 7-8
11 6 Image Transformation, Common Remote Sensing Tasks   What are the Top Applications of Remote Sensing?  
12 7 Mapping Over an Image Collection Ex 9: Mapping Over an Image Collection   Project Task 1 , Ex. 9
14 7 Sensing the Climate- Important Datasets Ex 10: Reducers An evaluation of ERA5 precipitation for climate modeling Ex. 10
15 8 Lab 1- Climate Variables      
16 8 Sensing Natural Hazards- Indices Ex 11: Band Math What is the color when black is burned? Quantifying (re)burn severity using field and satellite remote sensing indices Lab 1 , Ex. 11
17 9 Lab 2- Calculating Indices (Wildfires)      
18 9 Sensing Natural Hazards- Time Series Analysis Ex 12: Time Series Intense windstorms in the northeastern United States Lab 2, Ex. 12
19 10 Lab 3- Time Series (Hurricanes)     Project Task 2
20 10 Sensing Natural Hazards- Presenting Results   CAPA Heatwatch Report Lab 3
21 11 Lab 4- Aggregating Data (Urban Heat)      
22 11 Sensing Natural Hazards- Change Detection Ex 13: Change Detection Flood Detection in Urban Areas Using Satellite Imagery and Machine Learning Lab 4, Ex. 13
23 12 Lab 5- Change Detection (Flooding)      
24 12 Sensing Natural Hazards- Presenting Results Ex 14: GUI Development   Lab 5, Ex. 14
25 13 Lab 6- GUI Development (Previous Analysis)     Project Task 3
26 13 Developing a GUI for your Final Project     Lab 6
27 14 GUI Workday      
28 14 Catch up