2-credit hybrid course (with scheduled meetings) taught from weeks 1 to 5

GEOG 577 can be used toward the GIS certificate.

Course Webpage: https://sites.google.com/pdx.edu/geog-geoffreyduh/home/photogrammetry-and-lidar

(Or go to http://web.pdx.edu/~jduh/ and select "Courses-> GEOG 4/577 (F24)")

Instructor: Geoffrey Duh (jduh@pdx.edu)

Lecture hours: Lecture: Weeks 1 to 5, Tue 12:00 - 1:50 pm at VSC B108 or optionally on Zoom (see Canvas for additional Zoom attendance information).

Online lab Q&A hours: Schedule an appointment with the instructor or use the course Slack workspace to post questions. 

Number of Credits: 2. This is a 2 credits course taught in a compressed 5-week schedule. You should treat the course as if it's a 4 credits course and put between 6 to 8 hours per week during the 5 week period; 2 hours for lectures and discussions; 4 to 6 hours for lab exercises, readings, writing lab reports, and working on the final project.

Course Objectives

This course focuses on the theory and methods of the generation and compilation of digital elevation data using photogrammetry and LiDAR technologies. Specific topics include UAS, digital photogrammetry, structure from motion, and LiDAR data processing. The course includes computer exercises using GIS and image processing software packages including ArcGIS Pro.

Text and Readings

There is no required textbook. Journal articles are available in pdf format and can be found on Canvas course page. See the Readings section for a list of weekly readings.

Software documents: There are online software documents that will be used for both the theoretical and practical components of the course. The instructor will provide access instructions on Canvas.

Grading

The instructor will grade graduate and undergraduate students based on separate distribution curves. The components of a student's grade are:

Class Participation (20%)

The course is an online course with scheduled meetings and is taught in a studio format, meaning there will be fewer in-classroom lectures and more hands-on computer exercises. There are some course activities that students can perform asynchronously every week. Attendance to the Tuesday lecture sessions is mandatory. If you miss more than one class period then you will be penalized five percent of your final grade per absence. You are expected to take part in the discussions and collaborative activities and if you are not in class then you cannot. If you are repeatedly late you will be given an absence. There are also online learning modules that require you to complete. These online learning activities complement the hands-on exercises and are counted toward your class participation grade.

Graduate (GEOG 577) students are required to select a topic from a list provided by the instructor (see the "Student Discussion Topics" table below) and prepare 3 discussion/quiz questions and their answers based on the assigned readings. Students who are responsible for the week's topics must post the questions (without the answers) to the Canvas discussions and send the questions and their answers to the instructor by 5 pm the day before the class (i.e., on Monday).

All students (both graduate and undergraduate) are expected to answer a total of at least 3 of these student-posted questions this term by replying to the questions post on Canvas discussion. Please try not to answer questions that have been answered by other students, unless all posted questions have been answered. The instructor will use the Canvas Discussion statistics as part of the Class Participation scores. 

Exam (0%)

There is no exam in this class, but the labs have their associated quizzes (see the lab assignments section below). 

Lab Assignments (Undergraduate students 60%, graduate students 45%)

The practical lab exercises provide a way to acquire skills using GIS software packages and to apply the course concepts to real data. All lab exercises require a significant amount of time to finish. Make sure you pace your lab exercises appropriately to prevent from turning them in late. Students usually have one or two weeks to work on the labs. The labs are due by Monday midnight. See the course schedule for the exact due dates. Please complete the Canvas lab quizzes and submit your lab reports on Canvas. You are required to work on the lab assignments at a time that is convenient for you outside classroom. All lab instructions can be found on Canvas. Please use Slack class channels to ask lab-related questions. The instructor will respond to questions posted to Slack. All students are encouraged to answer questions posted on Slack. 

Final Project (Undergraduate students 20%, graduate students 35%)

A term project is required for all students. Students work individually on a project that is based on one of the lab or ESRI online course exercises. Undergraduate students only need to replace the lab data with their own data. Graduate students are required to form a coherent research question based on one (or several) exercises and additional spatial analysis to find the answer to their question using their own data. The deliverable includes a digital copy of Powerpoint slide deck. Graduate students also need to submit a 250 words project abstract that provides a comprehensive description of the project. See this wiki page or any journal articles we read this term for examples of how to write an effective abstract. There are two stages to the project:

*  Submit a project proposal by Tuesday in Week 4: Each student will submit a one page project proposal. It should include a project title, the main objective of the project (or a research question), and the data to be used. Please make appointments with the instructor to discuss your proposal if you have questions.

*  Submit your Powerpoint slide deck (or a link to your Story Map) by Friday in Week 6: The slide deck should Includes the essential information described in the proposal, data sets used, the analyses performed, and display the maps and tabular output derived from the analyses. Graduate students need to put their project's 250 words abstract on the first page of the slide deck. The abstract also includes a title, author and their affiliation, contact information, and 4 to 6 keywords.

Course Evaluation

The university will process course evaluations on online. Students will be notified via PSU email at the beginning of week 10 (or week 5 depending on the departmental request submitted to PSU). Those who do not respond receive reminder emails the following week and again the day before the evaluations close. Students must check their PSU email accounts to receive the link to online course evaluation.

See the "Title IX & Academic Guidelines" page for information on the requests for academic accommodation, the policy on academic honesty, and the statement for Title IX Reporting Obligations.

Readings:

The readings PDF files can be found on Canvas or from the internet (when the URLs are provided).

Week 1:

• ESRI online course: Introduction to 3D Data (https://www.esri.com/training/catalog/5e42f6f9a333e81cae770275/introduction-to-3d-data/)

Week 2:

• Gatziolis, D. and Andersen, H-E. 2008. Guide to LIDAR Data Acquisition and Processing for the Forests of the Pacific Northwest. United States Department of Agriculture Forest Service Pacific Northwest Research Station General Technical Report PNW-GTR-768.

Week 3:

• USGS. 2018. U.S. Geological Survey National Geospatial Program Lidar Base Specification Version 1.3. https://pubs.usgs.gov/tm/11b4/pdf/tm11-B4.pdf

• ESRI ARCGIS LAB: Working with the ArcGIS Solution for 3D Buildings (https://www.esri.com/training/catalog/6410bcb84d750615175af71d/working-with-the-arcgis-solution-for-3d-buildings/)

Week 4:

• Lillesand, T., Kiefer, R. W., and Chipman, J. 2008. Remote Sensing and Image Interpretation. 6th Edition. New York: John Wiley and Sons, 123-181.

• ERDAS 2010. Photogrammetric Concepts. ERDAS Field Guide. 595-633.

Week 5:

• ArcGIS Pro Online Help Ortho Mapping (https://pro.arcgis.com/en/pro-app/latest/help/data/imagery/introduction-to-ortho-mapping.htm), read all topics in the Ortho Mapping container.

• Unmanned aerial vehicle on Wikipedia, https://en.wikipedia.org/wiki/Unmanned_aerial_vehicle