COURSE UNIT TITLE

: REMOTE SENSING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ELECTIVE

Offered By

City and Regional Planning

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR HAYAT ZENGIN ÇELIK

Offered to

City and Regional Planning
Architecture

Course Objective

Remote sensing provides the opportunity to detect, classify, monitor and map objects and events on earth by using the methods of analyzing data collected by sensors. With the developing technologies, remote sensing techniques are also changing and
developing in parallel. The aim of this course is to teach students the principles of remote sensing, data collection techniques, image processing and analysis methods, data interpretation and inference techniques. At the same time, it aims to introduce and teach remote sensing techniques that will be effective in the development of high-scale plan decisions within the framework of city and regional planning discipline.

Learning Outcomes of the Course Unit

1   To have knowledge about the subject and techniques of remote sensing
2   Gain the ability to process data through programs
3   Having the ability to classify and analyze data
4   To have knowledge about the application of remote sensing techniques in the field of city planning
5   To be able to apply in related programs at the entry level and to have knowledge of data validation

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to remote sensing and application areas
2 Promotion of satellite imagery and transfer of organizations offering online resources
3 Introduction of remote sensing techniques and related programs
4 Image processing and classification techniques
5 Examination of urban development with remote sensing techniques with ArcGIS program
6 Investigation of land cover change with remote sensing techniques with ArcGIS program
7 Midterm
8 Machine learning and deep learning techniques in remote sensing
9 Monitoring land use and land cover change with remote sensing techniques in IDRISI/TerrSet program
10 Performing trend analysis with remote sensing techniques in the IDRISI/TerrSet program
11 Introducing the Google Earth Engine interface and coding
12 Monitoring of land cover change using the Google Earth Engine program
13 Examination of remote sensing techniques with QGIS program
14 Monitoring of land cover change with the QGIS program
15 Final exams
16 Final exams

Recomended or Required Reading

References:
- Introduction to Remote Sensing, 2011, James B. Campbell and Randolph H. Wynne
- GNSS Remote Sensing: Theory, Methods and Applications, 2014, Jin Shuangge,
- Remote Sensing and Geographical Information System, 2011, Chandra, A. M.,
- Articles and papers on remote sensing.

Planned Learning Activities and Teaching Methods

The course will be learned and taught through readings, lectures and classroom discussions. Case studies and brainstorming methods will be used in class discussions to support student-centered education. Homework-based learning method will be applied and students will be asked to prepare and present an assignment on tactical urbanization examples.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FINS FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.30 + FINS * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes of defining concepts and describing them with examples will be evaluated in the midterm exam. Relating the subjects, criticizing the examples and proposing alternative solutions will be evaluated in the assignment and the final exam.

Language of Instruction

Turkish

Course Policies and Rules

-

Contact Details for the Lecturer(s)

hayat.zengin@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Student Presentations 1 2 2
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 9 9
Preparation for final exam 1 12 12
Individual homework preperation (CBIKO Talent Gate) 1 12 12
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 75

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.11
LO.2
LO.3
LO.4
LO.5

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

HOME / ABOUT US / DEGREE PROGRAMMES / GENERAL INFORMATION FOR STUDENTS / INTERNATIONAL RELATIONS