GEOG 640 Remote Sensing
Course Description
For information regarding prerequisites for this course, please refer to the Academic Course Catalog.
Course Guide
View this course’s outcomes, policies, schedule, and more.*
Rationale
Data collection and management representing the planet earth and space in general is expensive and computationally intensive. This course presents recent technologies for acquiring and converting imagery data to information helpful for decision making. To be marketable with geospatial skills, the student must possess technologies and skills that meet the current job market. Many industries, government, and researchers require the analysis of huge imagery data. This course will teach the student to utilize available recent technologies for converting raw imagery data to information.
Course Assignment
Textbook readings and lecture presentations
No details available.
Course Requirements Checklist
After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.
Discussions (2)
Discussions are collaborative learning experiences. The student is required to create a thread in response to the provided prompt for each discussion. Each thread must be at least 300 words and demonstrate course-related knowledge. In addition to the thread, the student is required to reply to 2 other classmates’ threads. Each reply must be at least 150 words. Both the thread and each reply must incorporate at least two scholarly citations in current APA format.
Lab Assignments (8)
The student will conduct a series of exercises using the ArcGIS Pro software. Each exercise will involve producing maps/data, and answering a series of questions. The labs will also incorporate concepts and key information from the text readings. The labs include:
- Lab: Introduction to ArcGIS Pro Assignment
- Lab: Earthshots Assignment
- Lab: Preprocessing Remotely Sensed Data Assignment
- Lab: Image Classification Assignment
- Lab: Introduction to Earth Engine Data Catalog Assignment
- Lab: Change Detection Assignment
- Lab: Machine Learning and Classification of Remote Sensing Data Assignment
- Lab: Accuracy Assessment Assignment
Course Project Assignments (2)
The course project has two parts: Course Project: Proposal Assignment and Course Project: Final Assignment submission. A sample course project and optional course project themes are provided in the modules.
Quizzes (7)
Each quiz will cover the Learn materials for the modules: weeks in which it is assigned, with the exception of the cumulative Quiz: Final Exam. Each quiz will be open-book and open-notes.
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