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| Course Description |
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| Course Name |
: |
Remote Sensing and Agricultural Applications |
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| Course Code |
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UA-502 |
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| Course Type |
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Optional |
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| Level of Course |
: |
Second Cycle |
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| Year of Study |
: |
1 |
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| Course Semester |
: |
Spring (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Prof.Dr. AKIN OĞUZ DİNÇ
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| Learning Outcomes of the Course |
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Builds up knowledge on the basic principles of Remote Sensing
Understands satellite data types and performs geoographic and radiometric corrections
Gains the necessary skills to perform image enhancement and mathematical processes
Acquires knowledge on soil and vegetation reflectance characteristics
Becomes able to categorize soil and vegetation sources based on various classification techniques
Conducts field work to check and verify results
Interprets the results and performs accuracy assesment analysis
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| Mode of Delivery |
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Face-to-Face |
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| Prerequisites and Co-Prerequisites |
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None |
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| Recommended Optional Programme Components |
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None |
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| Aim(s) of Course |
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The aim of this course is to introduce the use of remote sensing for the mapping and monitoring of soils and vegetation, selection, processing and classification of satellite data and its interpretation. The course will also cover field work and accuracy analysis. |
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| Course Contents |
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The practice of Remote Sensing in agriculture with a specific focus on the methodologies and approaches to soil and crop mapping, monitoring and management. Spectral reflectance characteristics of soils, vegetation and water, and related histogram analysis. The use and interpretation of different satellite data. Supervised and unsupervised classification techniques. Detailed soil mapping using remote sensing methods and field work. Classification of vegetation acerage and yield estimation. Accuracy estimation, user and classification accuracy and kappa statistics. |
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| Language of Instruction |
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Turkish |
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| Work Place |
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Department of Soil Science and Plant Nutrition Remote Sensing and GIS Lab. |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
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1 |
Principles of Remote Sensing |
Preliminary reading |
Lecture and discussions |
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2 |
Satellites and their properties |
Preliminary reading |
Lecture and discussions |
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3 |
Geographic and Radiometric Correction |
Preliminary reading |
Lecture and discussions |
|
4 |
Image enhancement and mathematical calculations |
Preliminary reading |
Lecture and discussions |
|
5 |
Image processing/classification |
Preliminary reading |
Lecture and discussions |
|
6 |
Factors affecting reflections from soils |
Preliminary reading |
Lecture and discussions |
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7 |
Factors affecting reflections from vegetation |
Preliminary reading |
Lecture and discussions |
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8 |
Mid exam |
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|
|
9 |
Unsupervised and supervised classification of soils |
Preliminary reading |
Lecture and discussions |
|
10 |
Unsupervised and supervised classification of vegetation |
Preliminary reading |
Lecture and discussions |
|
11 |
Preparation of soil maps |
Preliminary reading |
Lecture and discussions |
|
12 |
Crop acerage and yield analysis |
Preliminary reading |
Lecture and discussions |
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13 |
Analysis of land use |
Preliminary reading |
Lecture and discussions |
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14 |
Field work and data collection methods |
Preliminary reading |
Lecture and discussions |
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15 |
Accuracy assesment and kappa statistical analysis |
Preliminary reading |
Lecture and discussions |
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16/17 |
Final exam |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Manual of remote sensing. Volume 2. Interpretation and applications. Colwell, R. N.;U¸laby, F. T.;Simonett, D. S.;Estes, J. E.;Thorley, G. A. 1983 pp. 2440pp. ISBN 0-937294-42-X
Remote sensing and image interpretation. 2004. Lillesand, T. M.; Kiefer, R. W.; Chipman, J W. + 763 pp
1-2001. Uzaktan Algılamanın Temel Esasları ve Bazı Uygulamaları. Dinç, U., İ. Yeğengil; V. Peştemalcı, A.O. Dinç, H.M. Kandırmaz. Tübitak Bilim Adamı Yetiştirme Grubu, Lisans Üstü Yaz Okulu. 18-23 Haziran Adana. (In Turkish)
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| Required Course Material(s) | |
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
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Mid-term Exams (Written, Oral, etc.) |
1 |
50 |
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Homeworks/Projects/Others |
2 |
50 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
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Final Assessments
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100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
The students acquire knowledge on potential practical fields of use of remotely sensed data, and use their theoretical and practical knowledge for problem solution in the related professional disciplines. |
5 |
|
2 |
The students identify, describe, formulate and solve problems in engineering, and for this purpose, they are able to select appropriate techniques and apply analytical methods and models. |
4 |
|
3 |
The students generate information using remotely sensed data and GIS together with database management skills. |
5 |
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4 |
The students gain knowledge to use current data and methods for multi-disciplinary research. |
4 |
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5 |
The students gain technical competence and skills in using recent GIS and remote sensing software. |
5 |
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6 |
The students have basic information about data collection, management, and analysis through integrating GIS and remote sensing, and are able to solve engineering problems using modern tools and technologies. |
4 |
|
7 |
The students develop an understanding of sustainable resource management and planning to meet human needs by taking ecological factors into consideration in light of the current research data. |
4 |
|
8 |
The students acquire the necessary knowledge and skills to understand a system, a system component or process for planning purposes, using modern techniques and methods. |
4 |
|
9 |
At the end of the programme, the students acquire advanced knowledge on remote sensing and GIS theory. |
5 |
|
10 |
The students gain knowledge on remote sensing technologies, sensors and platforms and remotely sensed data. |
5 |
|
11 |
The students gain knowledge on temporal, radiometrici, spatial and spectral characteristics of remotely sensed data, as well as optic and active remote sensing systems and their interpretation. |
5 |
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12 |
The students develop the necessary skills for selecting and using appropriate techniques and tools for engineering practices, using information technologies effectively, and collecting, analysing and interpreting data. |
4 |
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13 |
The students gain the necessary skills to access information, review the literature, use databases and other sources of information, as well as lifelong learning awareness and the skills to follow scientific and technological developments for personal improvement. |
5 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
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Class Time (Exam weeks are excluded) |
15 |
3 |
45 |
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Out of Class Study (Preliminary Work, Practice) |
10 |
3 |
30 |
| Assesment Related Works |
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Homeworks, Projects, Others |
2 |
35 |
70 |
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Mid-term Exams (Written, Oral, etc.) |
1 |
1 |
1 |
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Final Exam |
1 |
1 |
1 |
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Total Workload: | 147 |
| Total Workload / 25 (h): | 5.88 |
| ECTS Credit: | 6 |
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