Information Package / Course Catalogue
Spatial Analysis Techniques of Landscapes
Course Code: ZPM542
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

This course aims to explain the theory and different practical skills for the analysis of the spatial structure and organization of the landscape that can be used in landscape planning studies.

Course Content

Demonstration of some of the basic analysis that can be used in landscape planning by explaining the content of spatial analysis techniques and how to perform various spatial analysis.

Name of Lecturer(s)
Learning Outcomes
1.To develop a deeper understanding of spatial data and principles of spatial analysis,
2.To develop a proficiency in the analysis and evaluation of spatial data,
3.To develop technical skills to structure spatial data analysis and modeling in planning,
4.To develop and improve spatial problem solving abilities through the application of GIS knowledge and spatial thinking skills.
5.To be able to produce landscape planning projects with spatial analysis techniques.
Recommended or Required Reading
1.Jensen J.R. and Jensen R.R. (2013) Introductory Geographic Information Systems, Upper Saddle River, New Jersey: Prentice Hall.
2.Heywood, I, Cornelius, S. and Carver, S. (2011) An Introduction to Geographical Information Systems, 4th Ed, Upper Saddle River, New Jersey: Prentice Hall.
3.Longley, P.A., Goodchild, M.F, Maguire, D.J. and Rhind, D.W. (2015) Geographic Information Systems and Science, 4rd ed., Chichester: Wiley.
4.Lo, C.P. and Yeung, A.K.W. (2007) Concepts and Techniques of Geographic Information Systems, 2nd ed., Upper Saddle River, New Jersey: Prentice-Hall.
5.Chang, K.T. (2015) Introduction to Geographic Information Systems, 8th ed., Boston: McGraw-Hill.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to course: content, reason, importance, process method and needs
Week 2 - Theoretical
Introduction to spatial analysis: Deriving information from data, Identifying spatial relationships
Week 3 - Theoretical
Spatial analysis tools
Week 4 - Theoretical
Distance analysis
Week 5 - Theoretical
Density analysis
Week 6 - Theoretical
Surface Analysis
Week 7 - Theoretical
Conversion functions / Reclassify
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
Spatial statistics
Week 10 - Theoretical
Project based learning
Week 11 - Theoretical
Project based learning
Week 12 - Theoretical
Project based learning
Week 13 - Theoretical
Project based learning
Week 14 - Theoretical
Project based learning
Week 15 - Theoretical
Project based learning
Week 16 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%40
Assignment2%30
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory144284
Lecture - Practice144284
Assignment24110
Midterm Examination110111
Final Examination110111
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
OÇ-1
5
4
5
5
1
OÇ-2
5
4
5
5
1
OÇ-3
5
4
5
5
1
OÇ-4
5
4
5
5
1
OÇ-5
5
4
5
5
1
Adnan Menderes University - Information Package / Course Catalogue