Course Outline
GEOG 145 - LiDAR Data Processing and GIS Integration
Fall Semester 2020
Basic Course Information
Courses numbered 1 - 49 are remedial or college preparatory courses which do not apply toward an A. A. Degree and are not intended for transfer. Courses numbered 50-99 apply toward an AA Degree, but are not intended for transfer. Courses numbered 100 and higher apply toward an AA Degree and/or are intended for transfer to a four-year college or university.
D - Credit - Degree Applicable
GEOG
LiDAR Data Processing and GIS Integration
Units and Hours
1
0
Grade/Pass/No Pass
Hour Type
Units
Weekly Hours
Semester Hours x 16 Weeks
Semester Hours x 18 Weeks
Lecture Category -
1.00
1.00
x 16 Weeks - 16.00
x 18 Weeks - 18.00
Lab Category -
0.00
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Subtotal -
1.00
x 16 Weeks - 16.00
x 18 Weeks - 18.00
Out of Class Hour -
2.00
x 16 Weeks - 32.00
x 18 Weeks - 36.00
Totals -
3.00
x 16 Weeks - 48.00
x 18 Weeks - 54.00
Hour Type
Units
Weekly Hours
Semester Hours x 16 Weeks
Semester Hours x 18 Weeks
Lecture Category -
0.00
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Lab Category -
0.00
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Subtotal -
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Out of Class Hour -
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Totals -
0.00
x 16 Weeks - 0.00
x 18 Weeks - 0.00
Catalog Description
This course will introduce students to basic concepts in Light Detection and Ranging (LiDAR). Students will also learn to process LiDAR data collected by unmanned aircraft systems (UAS), and analysis these data using Geographic Information Systems (GIS).
Student Learning Outcomes
Outcome
Describe the functions of the major components of a UAS LiDAR system.
Explain laser return and point density, and their implication for LiDAR data analysis.
Specific Course Objectives
Objective
Upon successful completion of the course, the student will be able to:
- Evaluate the difference between point cloud data from photogrammetry versus LiDAR.
- Analyze the different applications of LiDAR in the UAS industry.
- Compare the advantages and disadvantages of manual versus automated point cloud classification techniques.
- Implement the workflow needed to process and analyze LiDAR data.
Methods of Instruction
Methods of Instruction may include, but are not limited to, the following:
Discussion
Group Projects/Activities
Learning Modules
Lecture
Content in Terms of Specific Body of Knowledge
- Introduction to LiDAR
- Principles
- Point density
- Laser returns
- Intensity values
- Hardware Components
- LiDAR sensors
- Inertial measurement unit
- GPS
- Onboard computer and storage
- Principles
- Data Processing
- Manual classification
- Data requirements
- Advantages
- Disadvantages
- Automated classification
- Data requirements
- Advantages
- Disadvantages
- Manual classification
- Data Analysis
- Feature extraction
- Industry use cases
- 3-D modeling
- Industry use cases
- Volumetric analysis
- Industry use cases
- Feature extraction
Textbooks/Resources
Textbook
Pinliang Dong, Qi Chen
LiDAR remote sensing and applications
1st
Boca Raton
CRC Press
2018
Assignments
Students will review textbooks and journal articles to learn about the principles of photogrammetry and LiDAR. They will also review trade publications to learn how LiDAR is applied in the UAS industry.
Students will be require to write up the results from their learning modules and also summarize different industry applications of LiDAR.
Students will be required to reflect on the development of LiDAR hardware and data analysis techniques. They will also need to identify the advantages and disadvantages of various analytical methods introduced in the course.
Students will need to reserach novel applications of LiDAR in the UAS industry.
Methods of Assessment
Evaluation Method
- Oral Presentation
- Class Participation
- Class Work
- Homework
- Standardized instrument objectively measuring student knowledge
Open Entry/Open Exit
- Not Open Entry/Open Exit
Repeatability
No
Contact Person
Cheung, Wing H.