Gain an overview of remote sensing, its core concepts, and what can be accomplished with this technology
Understand the background and current state of remote sensing, beginning before cloud computing through the fundamentals of GEE
Study the most commonly used datasets available on the GEE platform and how to upload your own dataset
Employ data visualization and simple image processing workflows
Examine geospatial analysis app publication for facilitating data-, analysis-, and idea-sharing
About this course:
The course will have eleven units: 0) Why Google Earth Engine, 1) Google Earth Engine 101, 2) Client vs. Server, 3) Core Remote Sensing Concepts, 4) Image Collection, 5) Feature Collection, 6) Image Processing, 7) Feature Processing, 8) Image Classification, 9) Accuracy Assessment, and 10) App Publishing. Unit 0 first provides a background of remote sensing before cloud computing then introduces why Google Earth Engine is superior to other remote sensing platforms. Unit 1 introduces the fundamentals of Google Earth Engine. Unit 2 introduces the two core concepts related to cloud computing. Unit 3 emphasizes several core remote sensing concepts such as reflectance. Unit 4 introduces Image Collections available in Google Earth Engine. Unit 5 introduces Feature Collection available in Google Earth Engine. Unit 6 introduces image processing techniques such as band mathematics. Unit 7 introduces feature processing such as zonal statistics. Unit 8 introduces basic concepts of linear models to facilitate the understanding of more complicated machine learning models. Unit 9 introduces the concepts of classification vs. regression in remote sensing. Unit 10 introduces geospatial analysis app publication to facilitate data, analysis and idea sharing.
The ultimate goal of this class is for you to be comfortable using the GEE platform to share your remote sensing work and/or research with your peers and to help promote geospatial awareness for the general public.
Recommended prerequisite: GEOG XL 7: Introduction to GIS (or equivalent)
Required course in the Geospatial Imagery Analysis specialization.
This is an online course, wherein all course content is delivered online and all interaction among the instructor and the participants will take place online; additional requirements include microphone, headphones/speakers, and webcam.
Technical requirements: Students are responsible for providing a personal computer with a minimum of 4GB of RAM that is capable of running Windows 10. Apple hardware running macOS can be used provided that Windows 10 is installed either using Boot Camp or virtualization (VirtualBox, Parallels, etc.) with at least 4GB of RAM allocated to Windows. Hardware specifications in excess of these minimum requirements will offer better performance and a better student experience. Students will be provided with a student license for ArcGIS as long as they are enrolled in program courses for which ArcGIS is required.
Enrollment limited to 50 students; early enrollment recommended. Visitors not permitted. Internet access required. Materials required.
No refunds after October 09, 2023
Internet access required to retrieve course materials
Our team members are here to help. Hours: Mon-Fri, 8am-5pm.