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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of FOREST ENGINEERING
Doctorate
Course Catalog
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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of FOREST ENGINEERING / Doctorate
Katalog Ana Sayfa
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ORMI7420Using Sattellite Images in Forest Ecosystems3+0+0ECTS:7.5
Year / SemesterFall Semester
Level of CourseThird Cycle
Status Elective
DepartmentDEPARTMENT of FOREST ENGINEERING
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 3 hours of lectures per week
LecturerDoç. Dr. Uzay KARAHALİL
Co-LecturerProf. Mehmet MISIR
Language of instruction
Professional practise ( internship ) None
 
The aim of the course:
Understanding the satellite images, an important source of data, increasingly used in forest resources management in recent years. Furthermore, teaching usage and performing case studies in other forestry activities generally.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : Students will be able to learn different types and characteristics of satellite images. 2,3,101
PO - 2 : Students will be able to be well grounded in different types of image processing programs 2,3,101
PO - 3 : Students will be able to open, cut, coordinate and enrich of different satellite images.2,3,103,4
PO - 4 : Students will be able to compose and use programs used in forestry.2,3,103,4
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
This course aims to provide the usage of satellite images in forestry, to introduce different types and characteristics of satellite images especially LANDSAT and IKONOS. Rectifying and processing of images using ERDAS Imagine program. Supervised and unsupervised classification.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Introduction, content of the course, sources be followed
 Week 2Sattelites, history of the satellites
 Week 3Natural resource satellites
 Week 4IKONOS and Landsat Satellites
 Week 5Resolution and bands in sattelites
 Week 6Opening and combining the bands of images
 Week 7Cutting and mosaic the images.
 Week 8Rectification of the images.
 Week 9Mid term
 Week 10İmage enhancement methods
 Week 11Supervised classification in images
 Week 12Unsupervised classification
 Week 13Assignement
 Week 14Processing lidar data
 Week 15An overview of the course and explanation of understood the issues.
 Week 16Final exam
 
Textbook / Material
1Lillesand, T. M., Kiefer, R. W.,1987. Remote Sensing And Image Interpretation. Second edition. John Wiley-Sons Ltd. Canada.
2Lillesand, T. M., Kiefer, R. W.,1987. Remote Sensing And Image Interpretation. Second edition. John Wiley-Sons Ltd. Canada.
 
Recommended Reading
1Mather, P. M., 1999. Computer Processing of Remotely- Sensed Images. Second edition. John Wiley-Sons Ltd. England.
2Mather, P. M., 1999. Computer Processing of Remotely- Sensed Images. Second edition. John Wiley-Sons Ltd. England.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Homework/Assignment/Term-paper 9
13
16/11/2021
13/12/2021
4
4
50
End-of-term exam 16 10/01/2022 4 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 13 39
Sınıf dışı çalışma 3 5 15
Uygulama 3 5 15
Klinik Uygulama 0 0 0
Ödev 10 2 20
Proje 0 0 0
Dönem sonu sınavı için hazırlık 5 2 10
Dönem sonu sınavı 5 1 5
Diğer 1 0 0 0
Diğer 2 0 0 0
Total work load104