Information Package / Course Catalogue
Remote Sensing Based on Environmental Change Detection and Time Series
Course Code: ZPM619
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

Aims to present information about visual analysis methods by using the changes in the landscape image algebra, conversion, classification, GIS by using various algorithms, methods and approaches in terms of their use, advantages and disadvantages, and the need for landscape management.

Course Content

Pre-processing requirements for different change detection techniques. Introduction to digital image processing for change detection. Image algebra methods, Classification method: post-classification comparison, spectral and temporal mixture analysis, expectation maximization, unsupervised classification. Advantage and disadvantage of change detection procedure for a specific problem.

Name of Lecturer(s)
Learning Outcomes
1.Understands change detection based on digital image processing on the basic level
2.Decides the correct procedures about image processing prior to operations when necessary
3.Learns change detection methods based on digital image processing
4.Decides appropriate analysis approaches to produce digital data which is required to deal with the problem
5.Expresses change information through maps and statistics
Recommended or Required Reading
1.Süzen, M. L., & Ünlüsoy, D. (2018). Uzaktan Algılama ve Görüntü Yorumlama (Remote Sensing and Image Interpretation).
2.Frohn, R. C. (2018). Remote sensing for landscape ecology: new metric indicators for monitoring, modeling, and assessment of ecosystems. CRC Press.
3.Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
4.Wegmann, M., Leutner, B., & Dech, S. (Eds.). (2016). Remote sensing and GIS for ecologists: using open source software. Pelagic Publishing Ltd.
5.Rai, P. K., Mishra, V. N., & Singh, P. (Eds.). (2022). Geospatial technology for landscape and environmental management: sustainable assessment and planning. Singapore: Springer.
6.Lu, D., Mausel, P., Brondizio, E., Moran, E., 2003, Change Detection Techniques, International Journal of Remote Sensing, Vol. 25, No. 12, 2365- 407.
7.McCoy, R. M. (2005). Field methods in remote sensing. Guilford Press.
8.Adams, J. B., & Gillespie, A. R. (2018). Remote sensing of landscapes with spectral images: A physical modeling approach. Cambridge University Press.
9.Coops, N. C., & Tooke, T. R. (2017). Introduction to remote sensing. Learning Landscape Ecology: A Practical Guide to Concepts and Techniques, 3-19.
10.Sabins Jr, F. F., & Ellis, J. M. (2020). Remote sensing: Principles, interpretation, and applications. Waveland Press.
11.De Jong, S. M., & Van der Meer, F. D. (Eds.). (2007). Remote sensing image analysis: including the spatial domain (Vol. 5). Springer Science & Business Media.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to course: content, reason, importance, process method and needs.
Week 2 - Theoretical
Information about satellite images
Week 3 - Theoretical
Pre-processing techniques for change detection
Week 4 - Theoretical
Image differencing, image ratioing,image regression, and change vector analysis
Week 5 - Theoretical
Binary change detection and labeling change detection
Week 6 - Theoretical
Change detection using vegetation indices such as NDVI, SAVI, MSAVI
Week 7 - Theoretical
Transforming bi-temporal and multitemporal data
Week 8 - Theoretical
Classification method: pixel based unsupervised classification, post-classification comparison
Week 9 - Theoretical
Classification method: pixel based unsupervised classification, post-classification comparison
Week 10 - Theoretical
Classification method: object based unsupervised classification, post-classification comparison
Week 11 - Theoretical
Classification method: object based unsupervised classification, post-classification comparison
Week 12 - Theoretical
Advantage and disadvantage of different change detection techniques
Week 13 - Theoretical
Project presentations
Week 14 - Theoretical
Project presentations
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory1473140
Quiz116117
Midterm Examination142143
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
PÇ-8
PÇ-9
OÇ-1
3
4
OÇ-2
2
3
OÇ-3
4
5
OÇ-4
4
OÇ-5
5
Adnan Menderes University - Information Package / Course Catalogue
2026