Akademik Dersler - Tanıtım

Course Introduction Information


Code - Course Title	UCS1002 - Remote Sensing and GIS Studio II -Data Processing and Analy.
Course Type	Required Courses
Language of Instruction	Türkçe
Laboratory + Practice	2+6
ECTS	8.0
Course Instructor(s)	ÖĞRETİM GÖREVLİSİ DOKTOR GÖKBEN ADANA KARAAĞAÇ
Mode of Delivery	Face to Face
Prerequisites	Successful completion of UCS1001 – Remote Sensing and GIS Studio I - Fundamental Applications.
Courses Recomended	-
Required or Recommended Resources	Çabuk, A., & Uyguçgil, H. (Ed.). (2019). Coğrafi Bilgi Sistemleri. Anadolu Üniversitesi Yayınları, Açıköğretim Fakültesi Yayını No: 2057, Eskişehir.
Recommended Reading List	- https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/what-is-raster-data.htm- https://pro.arcgis.com/en/pro-app/3.4/tool-reference/spatial-analyst/how-weighted-overlay-works.htm- https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/an-overview-of-the-surface-tools.htm- https://desktop.arcgis.com/en/arcmap/latest/analyze/commonly-used-tools/surface-creation-and-analysis.htm- https://pro.arcgis.com/en/pro-app/latest/help/mapping/navigation/sql-reference-for-elements-used-in-query-expressions.htm
Assessment methods and criteria	1 Midterm Exam, 1 Final Exam and 1 Assignment
Work Placement	- The program includes compulsory internship training.- Practical applications are carried out in the computer laboratory using various GIS software.
Sustainability Development Goals	Quality Education , Industry, Innovation and Infrastructure , Responsible Production and Consumption , Climate Action , Terrestrial Life

Content

Weeks	Topics
Week - 1	Spatial data, data model, transformation, comparison, evolution,
Week - 2	EN: Geodatabase theory, models, components
Week - 3	Vector data; spatial objects and geometry, spatial reference, spatial object tables and relationships between tables
Week - 4	Spatial object types (point, line, polygon, label, measurement, multiple point, multiple surface)
Week - 5	Raster data properties; usage areas, management strategies, data organization
Week - 6	Attribute and location based query applications
Week - 7	Spatial data processing; buffer, truncation, truncation, merging, merging, integration
Week - 8	Three-dimensional surface generation; digital surface model, digital terrain model, regular triangle mesh, digital elevation model
Week - 9	Surface analysis; slope, aspect, relief, field of view, elevation curve, watershed calculations
Week - 10	Data transformations, reclassification
Week - 11	Overlap analysis
Week - 12	Multi-criteria decision making methods
Week - 13	Multi-criteria decision making methods
Week - 14	EN: Multi-criteria decision making methods and weighted overlay analysis applications II

Learning Activities and Teaching Methods

Teaching Methods
Lecture
Demonstration
Drill - Practise
Competences
Productive
Questoning
Work in teams
Problem solving
Applying theoretical knowledge into practice
Information Management

Assessment Methods

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	30
Homework	1	20
Final Exam	1	50
Toplam (%)		100