GEOG 480 - Exploring Imagery and Elevation Data in GIS Applications
This is a sample syllabus.
This sample syllabus is a representative example of the information and materials included in this course. Information about course assignments, materials, and dates listed here is subject to change at any time. Definitive course details and materials will be available in the official course syllabus, in Canvas, when the course begins.
Overview
GEOG 480, Exploring Remote Sensing in Spatial Data Science, is an introductory-level course focusing on the use of remotely sensed imagery data in GIS applications. Students enrolling in Geog 480 should have a solid conceptual foundation in geospatial information science and technology (equivalent to Geog 482 and Geog 483). Geog 480 is appropriate for those who are already working in the geospatial profession and wish to use imagery data in visualization and spatial analysis.
Objectives
Students who excel in this course will be able to:
- show understanding of the basic principles of Earth observations using remote sensing;
- communicate the results and process of using remote sensing;
- apply remote sensing to practical spatial data science problems.
Required Materials
The materials listed here represent those that may be included in this course. Students will find a definitive list in the course syllabus, in Canvas, when the course begins.
Required Textbook
Campbell, James B. 2011. Introduction to Remote Sensing, 6th edition. New York. The Guilford Press. ISBN 978-1462549405.
Optional Textbook
Parece, Tammy, McGee, John, Campbell, Jim 2019. Workbook: Remote Sensing with ArcGIS Pro. Virginia Tech. ISBN: 1797570986.
Required Software
- Administrator-level password for your computer
- ArcGIS Pro, Esri (free of charge for active students)
- 7-Zip (or similar) (free download)
- Screen Capture Utility (free versions available)
Prerequisites
GEOG 482 and GEOG 483 (or equivalent professional experience). It is expected that students are conversant in fundamental concepts of GIS and have hands-on experience with ArcGIS Pro. The following bullets are examples of knowledge and skills you should have before starting this course.
- explain the concept of map scale
- explain the concept of a map projection
- describe the difference between a vector and a raster data set
- explain the difference between an Esri SHP file and a feature class
- explain the difference between a 2D and 3D SHP file or feature class
- manage GIS data files in the Esri interface
- access data management, data conversion, and data analysis tools in the Esri interface
- add a vector data layer to a project file
- add a raster data layer to a project file
- create a new SHP file or feature class
- edit a SHP file or feature class using the Editor toolbar
- change symbols for a SHP file or feature dataset using Symbology Properties
- view and edit the attribute table for a SHP file, feature class, or raster layer
Expectations
We have worked hard to make this the most effective and convenient educational experience possible. How much and how well you learn is dependent on your attitude, diligence, and willingness to ask for clarifications or help when you need them. We are here to help you succeed. Please keep up with the class schedule and take advantage of opportunities to communicate with us and with your fellow students. You can expect to spend an average of 12 – 15 hours per week on class work.
Major Assignments
Students earn grades that reflect the extent to which they achieve the learning objectives listed above. Opportunities to demonstrate learning include:
- Online quizzes (4% of final grade)
- Discussion (12% of final grade)
- Tutorials (8% of final grade)
- Assignments - Case Studies and Final Project (76% of final grade)
Course Schedule
Week | Topic | Assignment |
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0 | Orientation |
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1 | Lesson 1: Introduction to Remote Sensing |
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2 | Lesson 2: Remote Sensing Platforms and Sensors |
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3 | Lesson 3: Acquiring Remote Sensing Data |
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4 | Lesson 4: From RS Acquisition to Mapping: Principles of Map Projections/Geodesy |
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5 | Lesson 5: Case Study: Using Landsat to Evaluate Crop Health |
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6 | Lesson 6: Case Study: Wildfire Analysis |
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7 | Lesson 7: Case Study: Urban Sprawl Impacts in Atlanta, GA |
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8 | Lesson 8: Case Study: Climate Change |
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9 | Final Project |
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10 | Final Project |
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