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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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Carbon and its importance in forestry
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R1-Introduction section
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2
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Components of carbon
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R2-Material and method section
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3
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Calculation of single tree and stand carbon by ground measurements
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R1-Method section and R2-Method section
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4
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Remote sensing concept
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R3-Introduction section
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5
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Importance of remote sensing in forestry
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R4-Introduction section, R5-Introduction section and R6-Introduction section
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6
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Integration of carbon and remote sensing data
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R1-Method section, R2-Method section, R4-Method section, R5-Method section and R6-Method section
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7
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Modeling of the relationship between reflectance values obtained from different passive images and carbon values obtained from ground measurements
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R2-Material, Method and Results section, R4-Material, Method and Results section, R5-Material, Method and Results section, and R6-Material, Method and Results section
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8
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Modeling of the relationship between vegetation indices obtained from different passive images and carbon values obtained from ground measurements
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R2-Material, Method and Results section, R4-Material, Method and Results section, R5-Material, Method and Results section, and R6-Material, Method and Results section
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9
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Modeling of the relationship between textural values obtained from different passive images and carbon values obtained from ground measurements
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R2-Material, Method and Results section, R4-Material, Method and Results section, R5-Material, Method and Results section, and R6-Material, Method and Results section
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10
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Modeling the relationships between the backscattering values obtained from different active satellite images and the carbon values obtained from ground measurements
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R1-Material, Method and Results section
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11
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Modeling the relationships between the textural values obtained from different active satellite images and the carbon values obtained from ground measurements
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R1-Material, Method and Results section
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12
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Modeling the relationship between carbon values obtained from ground measurements and both active and passive satellite images
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R1-Material, Method and Results section, and R5-Material, Method and Results section
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13
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Sample application-I
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R1-Material, Method and Results section, R2-Material, Method and Results section, R4-Material, Method and Results section, R5-Material, Method and Results section and R6-Material, Method and Results section
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14
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Sample application-II
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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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Professor. Alkan GÜNLÜ
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Instructors
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1-)Profesör Dr. Alkan Günlü
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Assistants
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-
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Resources
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1. Lillesand, T.M., Kiefer, R.W., ve Chipman, J.W., 2004. Remote Sensing and Image Interpretation. 5th ed. New York: John Wiley & Sons, Inc.
2. Günlü, A., Ercanlı İ., Başkent, E.Z., ve Çakır G., 2014. Estimating Aboveground Biomass using Landsat TM Imagery: A Case Study of Anatolian Crimean Pine Forests in Turkey. Ann. For. Res. 57(2): 289-298.
3. Günlü, A., ve Ercanlı, İ., 2020. Artificial Neural Network Models by Alos Palsar Data for Aboveground Stand Carbon Predictions of Pure Beech Stands: A Case Study From Northern of Turkey. https://doi.org/10.1080/10106049.2018.1499817.
5. Günlü, A., Ercanlı İ., Şenyurt, M., ve Keleş, S. 2020. Estimation of Some Stand Parameters from textural features from WorldView-2 Satellite Image using the Artificial Neural Network and Multiple Regression Methods: A Case Study from Turkey. https://doi.org/10.1080/10106049.2019.1629644
5. Lucas, R.M., Mitchell, A.L., ve Armston, J., 2015. Measurement of Forest Above-Ground Biomass using Activeand Passive Remote Sensing at Large (Subnational to Global)Scales. Curr Forestry Rep (2015) 1:162?177.
6. Sakıcı, O.E., ve Günlü, A. 2018. Artificial Intelligence Applications for Predicting Some Stand Attributes using Landsat 8 OLI Satellite Data: A Case Study from Turkey. Applıed Ecology and Envıronmental Research 16(4):5269-5285.
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Supplementary Book
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Goals
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Learning the development of models for determining carbon storage capacities of forests using different remote sensing data
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Content
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Modeling the relationships between carbon quantities obtained by ground measurements and different remote sensing data
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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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3
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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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-
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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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4
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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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-
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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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3
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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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-
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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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4
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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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-
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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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