UA007 Data Formats and Transformations in Geographical Information Systems

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

Information

Code UA007
Name Data Formats and Transformations in Geographical Information Systems
Term 2024-2025 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 Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Öğr. Gör. MEHMET AKİF ERDOĞAN


Course Goal / Objective

The aim of this course is to define the data formats that will be needed within the scope of GIS, to transfer each data type from the correct source to the GIS environment with the correct techniques, to standardize the data in the GIS environment and to convert it into other formats, and also to demonstrate them through the applicable examples.

Course Content

The structure, properties, differences, advantages and disadvantages, usage content for different application areas, and also transformation to each other of data types used in GIS.

Course Precondition

None

Resources

Geographic Information Systems, Remote Sensing

Notes

Geographic Information Systems, Anadolu University Publishing


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Perception of GIS concept
LO02 Learning the basic principles of GIS
LO03 Adoption to spatial data modeling approach
LO04 Understanding the types and definitions of data
LO05 Learning point vector data
LO06 Learning line vector data
LO07 Learning polygon vector data
LO08 Understanding the raster data
LO09 Perception of data sources
LO10 Analyzing the data-source relationship
LO11 Learning transformation between vector data
LO12 Learning transformation between raster data
LO13 Learning transformation between vector and raster data
LO14 Discussing data transformation application examples


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 5
PLO02 Bilgi - Kuramsal, Olgusal The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data 4
PLO03 Bilgi - Kuramsal, Olgusal The students generate information using remotely sensed data and GIS together with database management skills. 5
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 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.
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 Introduction to GIS Literature reading Öğretim Yöntemleri:
Anlatım
2 Essental Principles of GIS Literature reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
3 Spatial Data Modelling Literature reading Öğretim Yöntemleri:
Anlatım, Tartışma
4 Data types and definations Literature reading Öğretim Yöntemleri:
Alıştırma ve Uygulama, Anlatım
5 Vector Data: Point Literature reading Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
6 Vector Data: Line Literature reading Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
7 Vector Data: Polygon Literature reading Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
8 Mid-Term Exam Preparing the exam Ölçme Yöntemleri:
Yazılı Sınav
9 Raster Data Literature reading Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
10 Data Sources Literature reading Öğretim Yöntemleri:
Anlatım
11 Association of Data and Source Literature reading Öğretim Yöntemleri:
Anlatım
12 Transformations between vactor data Literature reading Öğretim Yöntemleri:
Anlatım
13 Transformations between raster data Literature reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Transformations between vector and raster data Literature reading Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
15 Examples of data transformation applications Literature reading Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma, Beyin Fırtınası
16 Term Exams Preparing the exam Ölçme Yöntemleri:
Ödev
17 Term Exams Preparing the exam Ölçme Yöntemleri:
Yazılı 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: 23.09.2024 03:03