Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Faculty of Architecture and Design
  • Department of Architecture
  • Course Structure Diagram with Credits
  • Remote Sensing
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title MİM3503 - Remote Sensing
Course Type Area Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 2+1
ECTS 4.0
Course Instructor(s) ARAŞTIRMA GÖREVLİSİ DOKTOR EMRE MUSTAFA BEKTÖRE
Mode of Delivery This course is only offered in face-to-face format.
Prerequisites There are no prerequisites or co-requisites for this course.
Courses Recomended No recommended programme component.
Required or Recommended Resources https://www.youtube.com/@middleburyremotesensing3639https://step.esa.int/main/doc/tutorials/https://www.youtube.com/watch?v=IqqH4UEVGmY
Recommended Reading List Uzaktan Algılama (Anadolu Üniv. Yayınları)Dijital Görüntü İşleme (Anadolu Üniv. Yayınları)Uzaktan Algılama Uygulamaları II (Anadolu Üniv. Yayınları)Uzaktan Algılama Ve Görüntü Yorumlama (Palme Yayınevi)
Assessment methods and criteria 1 midterm exam, 1 final exam.
Work Placement There is no internship in this course.
Sustainability Development Goals

Content

Weeks Topics
Week - 1 EN: What is remote sensing? Usage areas of Remote Sensing
Week - 2 Electromagnetic energy, Electromagnetic spectrum, Interaction of electromagnetic radiation with atmosphere, Interaction of electromagnetic radiation with earth objects. Spectral properties of vegetation, soil and water
Week - 3 EN: Basic conceps and historical development of remote sensing
Week - 4 EN: Remote sensing types and sensing systems
Week - 5 Thermal Remote Sensing
Week - 6 Microwave Remote Sensing
Week - 7 Image types and characteristics, Hisogram, Statistical Parameters
Week - 8 Image types and characteristics; Spatial Resolution, Spectral Resolution, Radiometric Resolution, Temporal Resolution
Week - 9 Pre-processing; Radiometric correction, Geometric correction
Week - 10 Image enhancement
Week - 11 Indices
Week - 12 Supervised classification
Week - 13 Unsupervised classification
Week - 14 Remote sensing application examples in the scope of urban and regional planning and architecture.

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Case Study
  • Problem Solving
  • Brain Storming
  • Report Preparation and/or Presentation
  • Competences
  • Rational
  • Questoning
  • Creative
  • Follow ethical and moral rules
  • Effective use of a foreign language
  • Work in teams
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Information Management
  • Elementary computing skills
  • Decision making
  • To work in interdisciplinary projects

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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