Information
Code | UA0030 |
Name | Using Software in Remote Sensing |
Term | 2023-2024 Academic Year |
Term | Spring |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 6 ECTS |
National Credit | 3 National Credit |
Teaching Language | Türkçe |
Level | Yüksek Lisans Dersi |
Type | Normal |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | |
Course Instructor |
1 |
Course Goal / Objective
Teaching the IDRISI software used in the Remote Sensing field
Course Content
Opening, preprocessing, exporting, image enhancement, spectral enhancement, classification of remote sensing images in IDRISI program
Course Precondition
none
Resources
Remote sensing with Terr-SET/IDRISI, Timoty A.Warner. Geocartao int.LTD.
Notes
lecture notes
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | he/she can use IDRISI |
LO02 | Understands the processing of satellite data |
LO03 | Classifies with IDRISI software |
LO04 | Applies remote sensing techniques to satellite data with IDRISI software |
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 | |
PLO02 | Bilgi - Kuramsal, Olgusal | The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data | |
PLO03 | Bilgi - Kuramsal, Olgusal | The students generate information using remotely sensed data and GIS together with database management skills. | |
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 | 5 |
PLO06 | Bilgi - Kuramsal, Olgusal | The students gain technical competence and skills in using recent GIS and remote sensing software | 5 |
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. | 5 |
PLO08 | Yetkinlikler - Öğrenme Yetkinliği | Students will be able to calculate and interpret physical and atmospheric variables by processing the satellite data. | 4 |
PLO09 | Yetkinlikler - Öğrenme Yetkinliği | Students can generate data for GIS projects using Remote Sensing techniques. | |
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 | 4 |
PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Acquires the ability to acquire, evaluate, record and apply information from satellite data | 5 |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Overview of remote sensing software | no preparation | Öğretim Yöntemleri: Tartışma |
2 | Integration with GIS software and remote sensing | no preperation | Öğretim Yöntemleri: Tartışma |
3 | What can IDRISI do. Installing the software | no preperation | Öğretim Yöntemleri: Gösteri |
4 | introduction of software and explorer window | Studying the relevant part from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
5 | Displaying Remotely Sensed Data | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
6 | Importing, Pre-Processing and Exporting | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
7 | Enhancing Images Spatially | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
8 | Mid-Term Exam | topic repetition | Ölçme Yöntemleri: Ödev |
9 | Spectral Enhancement Techniques | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
10 | Image Ratios | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
11 | Introduction to Classifying Multispectral Images | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
12 | Introduction to Classifying | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
13 | Supervised Classification | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
14 | Soft Classification | study of the relevant section from the book | Öğretim Yöntemleri: Gösterip Yaptırma |
15 | An overview | no need any preperation | Öğretim Yöntemleri: Tartışma |
16 | Term Exams | general repetition | Ölçme Yöntemleri: Ödev |
17 | Term Exams | general repetition | Ölçme Yöntemleri: Ödev |
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 |