Introduction to Remote Sensing


The main objective of this course is to introduce the fundamentals of remote sensing and related applications in the era of cloud computing.

Starting at $1,800.00
As few as 10 weeks

About this course:

The main objective of this course is to introduce the fundamentals of remote sensing and related applications in the era of cloud computing. Our goal is to transition from GUI and/or code based remote sensing software that runs on PCs, MACs and/or local servers to code based remote sensing APIs that runs in the cloud to better facilitate geospatial data exploration and idea sharing. Currently, one of the most prominent cloud based remote sensing and spatial analysis platforms is Google Earth Engine (GEE). We will rely heavily on this platform (Javascript API) to accomplish all of our mapping and geospatial analysis needs. The course will have six units: 0) Introduction, 1) Core remote sensing concepts, 2) GEE 101, 3) Geospatial data in the cloud, 4) Geospatial data visualization and 5) App publishing for data and analysis sharing. Unit 0 is an overview of what is remote sensing and what we can accomplish with this technology through example applications in various different fields. Unit 1 introduces core concepts that are unique to remote sensing. Unit 2 first provides a background of remote sensing before cloud computing then introduces the current state of the art through the fundamentals of GEE. Unit 3 introduces the most commonly used datasets available on the GEE platform and how to upload your own dataset to GEE if needed. Unit 4 introduces data visualization and simple image processing workflows. Unit 5 introduces geospatial analysis app publication to facilitate data, analysis and idea sharing. All units will also include lab sessions with code examples to help start the transition from local GUI and/or coding environment into a cloud-based coding environment. 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. SUGGESTED PREREQUISITES It is advisable that you complete the following (or equivalent): GEOG XL 7: Introduction to Geographic Information Systems (GIS)
Recommended prerequisite: GEOG XL 7: Introduction to GIS (or equivalent)

Spring 2023 Schedule

Date & Time
This section has no set meeting times.
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ENROLL BY: Apr 10, 2023
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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.

Refund Deadline
No refunds after April 17, 2023
Course Requirements
Internet access required to retrieve course materials

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