NRM4403 is a course designed for those undergraduate students that would like to get an introduction on how to acquire and process satellite imagery to derive land cover maps and assess habitat/vegetation biomass and health using the Google Earth Engine platform (https://earthengine.google.com/). These are tools that I am really excited about and I believe will change the way everybody approaches and uses remote sensing data. We will go in depth on the implementation of these tools and discuss scientific literature available on their applications. You will also get to learn basic java script coding (no previous experience needed).
Expected content:
1.- Introduction to Remote Sensing & Google Earth Engine (Basic functionality & working with the code editor).
2.- Imagery acquisition (Landsat, Sentinel, MODIS and NAIP) and preprocessing (Atmospheric correction, building cloud-free composites).
3.- Deriving time series of vegetation and moisture indices (using GEE and new functionalities in ArcGIS Pro).
4.- Land cover mapping using multiple source remote sensing and machine learning algorithms.
5.- Post-classification change detection: semi-automated methods and automated methods for ecosystem disturbance mapping (Landtrendr and Bfast).
6.-Trend analysis and Spatial Regression modeling (Using GEE and ArcGIS Pro).
If you're interested in taking this course, you can directly register (no permission needed) or please email me back at carlos.portillo@ttu.edu if you want more information about it.
The course will be taught face-to-face. It will run from May 28th until June 29th, 2024, lectures on M-F from 5pm-5:50pm with lab time on T/Th until 7:50pm maximum. Options will be available for those who would like to use remote/online coursework material.
Dr. Carlos Portillo-Quintero
Associate Professor, Department of Natural Resources Management
