Main Page     Information on the Institution     Degree Programs     General Information for Students     Türkçe  

 DEGREE PROGRAMS


 Associate's Degree (Short Cycle)


 Bachelor’s Degree (First Cycle)


 Master’s Degree (Second Cycle)

  Course Description
Course Name : Remote Sensing and Gıs in Urban Planning

Course Code : UA-514

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Prof.Dr. SÜHA BERBEROĞLU

Learning Outcomes of the Course : At the end of the course, the students acquire general knowledge and skills on remote sensing and GIS techniques for monitoring urban development.
acquire general knowledge and skills on remote sensing and GIS techniques for modelling urban development.

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : Application of optical and radar remote sensing, advanced remote sensing techniques for monitoring and modelling urban development to determine unplanned urbanisation. Additionally, analysis of high spatial remotely sensed data for urban and regional applications and urban information systems.

Course Contents : Remote sensing and geographical information systems techniques for monitoring and modelling urban development.

Language of Instruction : Turkish

Work Place : Lecture hall and laboratory


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Remote sensing patforms and sensors for monitoring urban development not required Lecture, discussion and demonstration
2 Urban change detection and time-series analysis Preliminary Reading Lecture, discussion and demonstration
3 Change detection and accuracy analysis Preliminary Reading Lecture, discussion and demonstration
4 Urban development modelling Preliminary Reading Lecture, discussion and demonstration
5 Cellular automata concept in modelling Preliminary Reading Lecture, discussion and demonstration
6 Cellular automata concept in modelling Preliminary Reading Lecture, discussion and demonstration
7 Urban heat islands and thermal remote sensing Preliminary Reading Lecture, discussion and demonstration
8 Urban information systems Preliminary Reading Lecture, discussion and demonstration
9 Change detection practice Preliminary Reading Lecture, discussion and demonstration
10 Mid-term exam
11 New applications in urban studies including Lidar, UAV etc. Preliminary Reading Lecture, discussion and demonstration
12 Urban 3D modelling studies Preliminary Reading Lecture, discussion and demonstration
13 Urban development plans and regulations Preliminary Reading Lecture, discussion and demonstration
14 Global case studies Readings Lecture, discussion and demonstration
15 Project presentations Project Assignement Group Presentations
16/17 Final exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Lecture notes, handouts and refereed journal papers
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 50
    Homeworks/Projects/Others 1 50
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 The students acquire knowledge on potential practical fields of use of remotely sensed data, and use their theoretical and practical knowledge for problem solution in the related professional disciplines. 3
2 The students identify, describe, formulate and solve problems in engineering, and for this purpose, they are able to select appropriate techniques and apply analytical methods and models. 0
3 The students generate information using remotely sensed data and GIS together with database management skills. 3
4 The students gain knowledge to use current data and methods for multi-disciplinary research. 4
5 The students gain technical competence and skills in using recent GIS and remote sensing software. 4
6 The students have basic information about data collection, management, and analysis through integrating GIS and remote sensing, and are able to solve engineering problems using modern tools and technologies. 5
7 The students develop an understanding of sustainable resource management and planning to meet human needs by taking ecological factors into consideration in light of the current research data. 4
8 The students acquire the necessary knowledge and skills to understand a system, a system component or process for planning purposes, using modern techniques and methods. 2
9 At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory. 3
10 The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data. 0
11 The students gain knowledge on temporal, radiometrici, spatial and spectral characteristics of remotely sensed data, as well as optic and active remote sensing systems and their interpretation. 2
12 The students develop the necessary skills for selecting and using appropriate techniques and tools for engineering practices, using information technologies effectively, and collecting, analysing and interpreting data. 2
13 The students gain the necessary skills to access information, review the literature, use databases and other sources of information, as well as lifelong learning awareness and the skills to follow scientific and technological developments for personal improvement. 3
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
    Homeworks, Projects, Others 1 14 14
    Mid-term Exams (Written, Oral, etc.) 1 6 6
    Final Exam 1 6 6
Total Workload: 138
Total Workload / 25 (h): 5.52
ECTS Credit: 6