TÜRKÇE
ENGLISH
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 | ||