Information Package / Course Catalogue
Lidar Applications For Landscape Architecture
Course Code: ZPM545
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

Analysis of Lidar data, mapping Lidar-based urban vegetation, individual tree segmentation algorithms, Lidar applications in landscape architecture

Course Content

Introduction of Lidar, introduction of programs that will be used in the analysis, associating Lidar-based analyzes with landscape architecture

Name of Lecturer(s)
Assoc. Prof. Derya GÜLÇİN
Learning Outcomes
1.Introduction of Lidar technology
2.Managing Lidar data (file reading with .las extension, parameter selection, point filtering, validation, three-dimensional visualization)
3.Classification of Lidar data
4.Creation of digital terrain model from Lidar data
5.Obtaining urban vegetation metrics
6.Comparison of Lidar algorithms
7.Associating Lidar applications with landscape architecture goals
Recommended or Required Reading
1.Murtha, T., Golden, C., Cyphers, A., Klippel, A., & Flohr, T. (2018). Beyond Inventory and Mapping: LIDAR, Landscape and Digital Landscape Architecture. Journal of Digital Landscape Architecture, 3, 249-259.
2.Roussel, J. R., Auty, D., Coops, N. C., Tompalski, P., Goodbody, T. R., Meador, A. S., ... & Achim, A. (2020). lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment, 251, 112061.
3.Farrell, S. L., Collier, B. A., Skow, K. L., Long, A. M., Campomizzi, A. J., Morrison, M. L., ... & Wilkins, R. N. (2013). Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere, 4(3), 1-18.
Weekly Detailed Course Contents
Week 1 - Theoretical
General introduction of the course
Week 2 - Theoretical
Information about R statistics software and introduction of the lidR package
Week 3 - Theoretical
Information about R statistics software and introduction of the lidR package Information about R statistics softwar
Week 4 - Theoretical
Reading, plotting, and querying Lidar metadata
Week 5 - Theoretical
Classification and validation of lidar metadata
Week 6 - Theoretical
Generation of digital terrain model
Week 7 - Theoretical
Height normalization
Week 8 - Theoretical
Generation of digital elevation model
Week 9 - Intermediate Exam
Midterm
Week 10 - Theoretical
Generation of canopy height model
Week 11 - Theoretical
Individual tree detection and segmentation
Week 12 - Theoretical
Calculation of tree metrics at tree level
Week 13 - Theoretical
Calculation of tree metrics at voxel level
Week 14 - Theoretical
Uses of Lidar in landscape architecture
Week 15 - Theoretical & Practice
Practice exam
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory14102168
Term Project1617
Midterm Examination110111
Final Examination113114
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
5
5
5
5
2
4
5
OÇ-2
4
4
4
3
2
3
4
OÇ-3
5
5
5
5
2
3
5
OÇ-4
4
4
4
3
2
4
4
OÇ-5
5
5
5
5
1
5
5
OÇ-6
5
4
4
4
1
4
5
OÇ-7
3
4
4
5
2
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026