| Course Description |
|
| Course Name |
: |
Applied Geostatistics |
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| Course Code |
: |
TS-552 |
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| Course Type |
: |
Optional |
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| Level of Course |
: |
Second Cycle |
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| Year of Study |
: |
1 |
|
| Course Semester |
: |
Spring (16 Weeks) |
|
| ECTS |
: |
6 |
|
| Name of Lecturer(s) |
: |
Prof.Dr. MAHMUT ÇETİN
|
|
| Learning Outcomes of the Course |
: |
1. Learns spatial variability concept.
2. Models spatial structure of a regionalized variable; Gains skills on interpretation of findings by defining model parameters.
3. Esimates the likely values for the unsamples locations (Kriging, BLUE), and makes interpratation on the results.
4. Generates kriging and kriging error maps.
5. Examines throughly the maps generated, and optimizes sampling pattern.
|
|
| Mode of Delivery |
: |
Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
The aim of this course is mainly to teach the principles of regionalized variables theory and its applications to hydrology and natural resources. The aim is also extended aquire skills on developing kriging and kriging error maps, and on interpretting the generated maps. |
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| Course Contents |
: |
Nomenclature, regionalized variable theory and stationarity assumptions. Spatial correlation structure analysis: Semivariogram analysis; Matheron model types, parameter estimation, and cross validation techniques. Best Linear Unbiased Estimation (BLUE) at unsampled locations: point kriging, block kriging. Spatial mapping: Kriging estimation and kriging error maps. Interpretations of results. Applications to the up-to-date and real data of hydrology and natural resources. |
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| Language of Instruction |
: |
Turkish |
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| Work Place |
: |
Class |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Nomenclature, regionalized variable theory and stationarity assumptions. |
Books and other study materials |
Self-study plus lecturing |
|
2 |
Nomenclature, regionalized variable theory and stationarity assumptions (CONT.) |
Books and other study materials |
Self-study plus lecturing |
|
3 |
Stationarity and its assumptions |
Books and other study materials |
Self-study plus lecturing |
|
4 |
Spatial correlation structure and modelling |
Books and other study materials |
Self-study plus lecturing |
|
5 |
Theoretical and experimental semivariogram analysis |
Books and other study materials |
Self-study plus lecturing |
|
6 |
Theoretical and experimental semivariogram analysis (CONT.) |
Books and other study materials |
Self-study plus lecturing |
|
7 |
Matheron model types, parameter estimation, and cross validation techniques. |
Books and other study materials |
Self-study plus lecturing |
|
8 |
Matheron model types, parameter estimation, and cross validation techniques (CONT.) |
Books and other study materials |
Self-study plus lecturing |
|
9 |
Best Linear Unbiased Estimation (BLUE) at unsampled locations |
Books and other study materials |
Self-study plus lecturing |
|
10 |
Mid-term exam |
Books and other study materials |
Take-home exam |
|
11 |
Best Linear Unbiased Estimation (BLUE) at unsampled locations (CONT.) |
Books and other study materials |
Self-study plus lecturing |
|
12 |
Point kriging |
Books and other study materials |
Self-study plus lecturing |
|
13 |
Block kriging |
Books and other study materials |
Self-study plus lecturing |
|
14 |
Spatial mapping: Kriging estimation and kriging error maps |
Books and other study materials |
Self-study plus lecturing |
|
15 |
Interpretations of results. Applications to the up-to-date and real data of hydrology and natural resources |
Books and other study materials |
Self-study plus lecturing |
|
16/17 |
Final exam |
Books and other study materials |
Take-home exam |
|
|
|
Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Clark, I. and Harper, W. V., 2000. Practical Geostatistics 2000. Geostokos (Ecosse) Limited, Scotland.
Chiles, J.-P. and Delfiner, P., 1999. Geostatistics: Modeling Spatial Uncertainty. Wiley Series in Probability and Statistics, John Wiley & ons, Inc., Canada, 695 pp.
|
| |
| Required Course Material(s) |
Other text books, and published papers in the esteemed national and international journals
|
|
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Has the ability to develop and deepen the level of expertise degree qualifications based on the knowledge acquired in the field of agriculture and irrigation structures |
3 |
|
2 |
Has the ability to understand the interaction between irrigation and agricultural structures and related disciplines |
3 |
|
3 |
Qualified in devising projects in agricultural structures and irrigation systems. |
4 |
|
4 |
Conducts land applications,supervises them and assures of development |
2 |
|
5 |
Has the ability to apply theoretical and practical knowledge in the field of agricultural structures and irrigation department |
4 |
|
6 |
Has the ability to support his specilist knowledge with qualitative and quantitative data. Can work in different disciplines. |
5 |
|
7 |
Solves problems by establishing cause and effect relationship |
5 |
|
8 |
Able to carry out a study independently on a subject. |
3 |
|
9 |
Has the ability to design and apply analytical, modelling and experimental researches, to analyze and interpret complex issues occuring in these processes.
|
4 |
|
10 |
Can access resources on his speciality, makes good use of them and updates his knowledge constantly. |
5 |
|
11 |
Has the ability to use computer software in agricultural structures and irrigation; can use informatics and communications technology at an advanced level.
|
3 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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