UA0013

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code UA0013
Name
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator


Course Goal / Objective

Detailed learning of Remote Sensing techniques

Course Content

Remote Sensing, Modeling Techniques and Analysis

Course Precondition

None

Resources

Lecture Notes

Notes

Lecture Notes of ITU


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Recent Techniques Used in Remote Sensing
LO02 Models used in Remote Sensing Projects
LO03 Techniques of using different Satellite images
LO04 Usage techniques of projection systems
LO05 Using Remote Sensing in Different Studies
LO06 Digital Image Processing in Remote Sensing


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory. 3
PLO02 Bilgi - Kuramsal, Olgusal The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data. 3
PLO03 Bilgi - Kuramsal, Olgusal The students generate information using remotely sensed data and GIS together with database management skills. 3
PLO04 Bilgi - Kuramsal, Olgusal 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.
PLO05 Bilgi - Kuramsal, Olgusal The students gain knowledge to use current data and methods for multi-disciplinary research.
PLO06 Bilgi - Kuramsal, Olgusal The students gain technical competence and skills in using recent GIS and remote sensing software.
PLO07 Bilgi - Kuramsal, Olgusal 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
PLO08 Yetkinlikler - Öğrenme Yetkinliği Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data.
PLO09 Yetkinlikler - Öğrenme Yetkinliği Students can generate data for GIS projects using Remote Sensing techniques. 3
PLO10 Bilgi - Kuramsal, Olgusal Gains the ability to analyze and interpret geographic data with GIS techniques.
PLO11 Bilgi - Kuramsal, Olgusal Gains the ability of problem solving, solving, solution oriented application development.
PLO12 Yetkinlikler - Öğrenme Yetkinliği Acquires the ability to acquire, evaluate, record and apply information from satellite data. 4


Week Plan

Week Topic Preparation Methods
1 Getting Information about Different Satellite Images Used in Remote Sensing 1 Subject evaluation Öğretim Yöntemleri:
Anlatım
2 Getting Information about Different Satellite Images Used in Remote Sensing 2 Lecture and Application Öğretim Yöntemleri:
Anlatım
3 Elements to be considered in Remote Sensing Project Preparations and problem solving techniques 1 Lecture and Application Öğretim Yöntemleri:
Anlatım
4 Elements to be considered in Remote Sensing Project Preparations and problem solving techniques 2 Lecture and Application Öğretim Yöntemleri:
Anlatım
5 Techniques for using remote sensing in multi-disciplinary studies 1 Lecture and Application Öğretim Yöntemleri:
Anlatım
6 Techniques for using remote sensing in multi-disciplinary studies 2 Lecture and Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
7 Use of Modeling techniques in multi-disciplinary studies Lecture and Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
8 Mid-Term Exam Ölçme Yöntemleri:
Sözlü Sınav
9 Projection Methods Lecture and Application Öğretim Yöntemleri:
Anlatım
10 Georeference and Coordinate Systems Lecture and Application Öğretim Yöntemleri:
Anlatım
11 Topological correlation with satellite data 1 Lecture and Application Öğretim Yöntemleri:
Anlatım
12 Topological correlation with satellite data 2 Lecture and Application Öğretim Yöntemleri:
Anlatım
13 Elements to be considered in image interpretation 1 Lecture and Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
14 Elements to be considered in image interpretation 2 Lecture and Application Öğretim Yöntemleri:
Alıştırma ve Uygulama
15 An overview question and answer Öğretim Yöntemleri:
Soru-Cevap
16 Term Exams Ölçme Yöntemleri:
Sözlü Sınav
17 Term Exams Ölçme Yöntemleri:
Sözlü Sınav


Student Workload - ECTS

Works Number Time (Hour) 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 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 19.11.2022 10:03