Geostatistics
| Title | Γεωστατιστική / Geostatistics |
| Code | 03YA018 |
| Faculty | Engineering |
| School | Rural and Surveying Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Christoforos Kotsakis |
| Common | No |
| Status | Active |
| Course ID | 600025730 |
Programme of Study: PPS Tmīmatos Agronómōn kai Topográfōn Mīchanikṓn (2025-sīmera)
Registered students: 58
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Core Courses | Core Courses | 3 | 2 | 5 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors | |
| Weekly Hours | 4 |
| Class ID | 600267780
|
Course Type 2021
Specific Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600267780
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
No prerequisite courses are required to attend the course. However, it is beneficial for students to have knowledge of Statistics and Probability Theory.
Learning Outcomes
The aim of the course is to introduce students to the basic principles of spatial analysis and geostatistics. Random fields (definition, properties), Basic spatial dependence functions (autocovariance, crosscovariance, autocorrelation, variogram), Concepts of stationarity, ergodicity and anisotropy, Dependent random variables, Multidimensional trend models, Introduction to simulation, Estimation of variogram from scattered spatial data, Spatial estimation with deterministic methods (Voronoi polygons, nearest and natural neighbor, inverse distance weights, minimum curvature), Spatial interpolation (optimal estimation) with stochastic methods (kriging), Uncertainty analysis, Practical applications in the science of Agronomy and Surveying.
Upon successful completion of the course, the student will be able to:
• Recognize at a satisfactory level concepts of the theory of random fields
• Analyze the concept of spatial continuity and related functions
• Develop the concept of spatial interpolation and its implementation methods
• Evaluate the basic stages of geostatistical analysis
• Use computational tools of geostatistical analysis with ease
• Estimate and evaluate basic spatial variables and parameters with geostatistical methods
General Competences
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work in teams
- Work in an interdisciplinary team
- Design and manage projects
- Respect natural environment
- Advance free, creative and causative thinking
Course Content (Syllabus)
The course includes: Basic principles of spatial analysis and geostatistics. Random fields (definition, properties). Basic spatial dependence functions (autocovariance, heterocovariance, autocorrelation, variogram). Concepts of stationarity, ergodicity and anisotropy. Dependent random variables. Multidimensional trend models. Introduction to simulation. Estimation of variogram from scattered spatial data. Spatial estimation with deterministic methods (Voronoi polygons, nearest and natural neighbor, inverse distance weights, minimum curvature). Spatial interpolation (optimal estimation) with stochastic methods (kriging). Uncertainty analysis. Practical applications in the science of Agricultural and Surveying Engineering.
Keywords
geostatistics, Kriging, stationarity, ergodicity, variogram, random fields, dispersion, variance, covariance
Educational Material Types
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
The Information Technologies are used in the course teaching (educational material, video, presentations, etc), in laboratory exercises and in the communication of teachers with the students.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ||||
| Laboratory Work | 13 | ||||
| Reading Assigment | 25 | ||||
| Project | 20 | ||||
| Exams | 3 | ||||
| Total | 100 |
Student Assessment
Description
Language of Assessment
Greek
Assessment Methods
The course lectures are combined with corresponding laboratory exercises and applications. At the same time, a semester group project is prepared and a corresponding technical report is written. Students are assessed by:
60% Written exams with theory questions and problem solving
40% Semester group project: Semester group project on a topic of interest to an Agronomist and Surveyor Engineer. Mandatory writing of a technical report and submission of the topic.
Student Assessment methods
- Written Exam with Multiple Choice Questions (Formative, Summative)
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Exam with Extended Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Καπαγερίδης, Ι.Κ. «Εφαρμοσμένη Γεωστατιστική». Μαρία Παρίκου και Σια Ε.Π.Ε., 2006, σελ. 240. ISBN: 9789604115518, [Κωδικός Βιβλίου στον Εύδοξο: 122079976]
Μόδης, Κ., Βαλάκας, Γ. και Σιδέρη, Δ. «Γεωστατιστική και Υπολογισμός Μεταλλευτικών Αποθεμάτων», ΚΑΛΛΙΠΟΣ Ανοικτές Ακαδημαϊκές Εκδόσεις, 2023, σελ. 330. ISBN 9786185726775, [Κωδικός Βιβλίου στον Εύδοξο: 121051719]
Additional bibliography for study
1) Σημειώσεις διδασκόντων
2) Journel, A. G. Huijbregts, C. Mining geostatistics Academic Press 1978 0123910501
3) Kitanidis, P. K. (1997), Introduction to geostatistics, Cambridge University Press, Cambridge.
4) Christakos, G. (2000), Modern Spatiotemporal Geostatistics, Oxford University Press, New York.Τερζίδης, Γ., Καραμούζης, Δ., «Υδραυλική Υπόγειων Νερών», Ζήτη, 2001, ISBN: 960-431-653-2, Κωδικός Βιβλίου στον Εύδοξο: 11389
Last Update
21-05-2025
