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Week
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Topics
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Study Metarials
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1
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Overview of the main features of RS platforms and sensors
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Reading Unit 1 and 2 in R3
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2
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Introduction of MATLAB interface and basic operations
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Reading Unit 1 and 2 in R1 and R2
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3
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Introduction of MATLAB interface and basic operations
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Reading Unit 1 and 2 in R1 and R2
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4
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Introduction of MATLAB interface and basic operations
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Reading Unit 1 and 2 in R1 and R2
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5
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Geometric correction and image registration with MATLAB
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Reading Unit 6 and 8 in R2 and Unit 4 in R3
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6
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Geometric correction and image registration with MATLAB
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Reading Unit 6 and 8 in R2 and Unit 4 in R3
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7
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Radiometric correction with MATLAB
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Reading Unit 5 in R3
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8
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Radiometric correction with MATLAB
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Reading Unit 5 in R3
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9
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Image conversion and filtering with MATLAB
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Reading Units 6 and 7 in R3
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10
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Image conversion and filtering with MATLAB
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Reading Units 6 and 7 in R3
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11
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Image conversion and filtering with MATLAB
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Reading Units 6 and 7 in R3
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12
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Basic image classification operations with MATLAB
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Reading Unit 8 in R3
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13
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Basic image classification operations with MATLAB
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Reading Unit 8 in R3
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14
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Basic image classification operations with MATLAB
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Reading Unit 8 in R3
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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Dr. Semih Kuter
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Instructors
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-
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Assistants
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Dr. Semih Kuter
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Resources
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R1. Brian, R., Hunt, R., Lipsman, L., & Rosenberg, J. (2001). A guide to MATLAB for beginners and experienced users: Cambridge University Press.
R2. Gebbers, R., Marwan, N., & Trauth, M. H. (2006). MATLAB Recipes for Earth Sciences: Springer.
R3. Mather, P. M. (2004). Computer Processing of Remotely-Sensed Images An Introduction (3rd ed.). England: John Wiley & Sons Ltd.
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Supplementary Book
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YK1. Liu, J. G., & Mason, P. (2009). Essential image processing and GIS for remote sensing: John Wiley & Sons.
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Goals
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The aim of this course is to teach basic image processing techniques in the field of RS by using MATLAB software on images obtained by remote sensing (RS) and at the same time, to gain basic coding skills in MATLAB environment.
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Content
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Introducing MATLAB interface, basic data types used in MATLAB and basic operations on this data, basic information about RS, basic filtering and classification methods on RS images.
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Program Learning Outcomes |
Level of Contribution |
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1
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Must learn the methods of both improving the basic sciences and engineering knowledge and obtaining new knowledges at a level of expertise
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4
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2
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Must be able to design, develop, and apply methods and experiments at advanced level to solve forestry problems, and analyses and interpret their results
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4
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3
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Must be able to provide solutions for the country?s forestry and environmental problems by considering global, public and ecosystem conditions
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-
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4
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Must be able to setup interdisciplinary approach to reach an advanced solution for forestry problems
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4
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5
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Must be able to act in an advanced level of professional ethics and responsibility during the identification and resolution of problems encountered in forestry
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-
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6
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Must be able to do the task in a single or multi-disciplinary working groups, and be able to show effective communication
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4
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7
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Must have the ability to effective use of both information technologies and a foreign language at an advanced level
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4
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8
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Must be able to describe, foresee and solve the current problems in the fields of forestry and other related problems at advanced level brought by current global developments
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-
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9
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Must be able to use the tools and techniques required for forestry applications at an advanced level
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4
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10
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Must be able to think, interpret, analyse and synthesize forestry practices at an advanced level by using a three dimensional perspective
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3
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11
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Must be able to research and survey any kinds of natural resources and event, and write advanced reliable reports by using the achieved findings
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3
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12
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Must be able to understand the necessity of life-long learning at an advanced level, and to be able to use the methods that keeps obtained knowledge up date
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3
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