SPATIAL ANALYSIS AND AGRO-GEOINFORMATICS
| Title | ΧΩΡΙΚΗ ΑΝΑΛΥΣΗ ΚΑΙ ΑΓΡΟ-ΓΕΩΠΛΗΡΟΦΟΡΙΚΗ / SPATIAL ANALYSIS AND AGRO-GEOINFORMATICS |
| Code | AKA816 |
| Faculty | Agriculture, Forestry and Natural Environment |
| School | Agriculture |
| Cycle / Level | 2nd / Postgraduate, 3rd / Doctorate |
| Teaching Period | Spring |
| Coordinator | Georgios Menexes |
| Common | Yes |
| Status | Active |
| Course ID | 600017451 |
Programme of Study: Prógramma metaptychiakṓn Spoudṓn Aeiforiká Geōrgiká Systīmata Paragōgīs kai Klimatikī Allagī
Registered students: 9
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses | 2 | 1 | 8 |
| Academic Year | 2022 – 2023 |
| Class Period | Spring |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 5 |
| Total Hours | 65 |
| Class ID | 600228008
|
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600228008
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Respect natural environment
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Content:
1. Introduction to Spatial Analysis and geospatial field data management. Spatial Analysis for big data analysis in agriculture, geospatial data analyses, and data mining. The concept of spatial dependence and the significance of spatial information in agriculture. Types of spatial distribution - random spatial process. Spatial analysis in Geographic Information Systems (GIS). Geoinformatics applications in agriculture and examples.
2. Geospatial analysis in Geographic Information Systems (GIS). Basic concepts of geographic analysis, including spatial data types and attributes. Types of spatial analysis and their applications in agriculture. The spatial analysis methods within the GIS environment including overlay analysis, distance or proximity analysis, and surface analysis.
3. Databases in GIS - Creation of queries, primary and secondary data for GIS, spatial data models, advantages and disadvantages of bivariate and binary data, data sources and file types, GIS-based field data entry, data management in GIS, and organization of information layers. Geographic databases and digital databases online. Tools to calculate descriptive statistics for spatial data and how to create and execute queries in the GIS database.
4. Thematic mapping in GPS. Thematic Map Basics, thematic levels of information, different types of thematic maps such as suitability and risk maps. Map examples. A map construction exercise in GIS.
5. Spatial Autocorrelation - Methods of Exploratory spatial data analysis (ESDA), spatial autocorrelation metrics and weight calculations (Moran's I, Geary's c, Getis G*). Creating cluster maps of spatial patterns (LISA cluster maps). Applications of spatial autocorrelation in Agriculture. Spatial Autocorrelation exercise (with GeoDa software) and cluster map construction in GIS (QGIS).
6. Multiple Regression on Spatial Data. Multiple Regression exercise (GeoDA).
7. Point Spatial Analysis - Construction of data density maps (via CAST and QGIS), applications, and examples.
8. Spatial interpolation methods. Introduction to Geostatistical approaches. Objectives of spatial interpolation. Spatial correlation of measurements. Selection of the appropriate spatial interpolation method. Validation and comparison of Spatial Interpolation results. Spatial Interpolation of field geospatial data. Spatial Interpolation exercise using soil data (QGIS plugins).
Keywords
Geoinformatics, Geospatial technologies, Analysis of spatial data
Educational Material Types
- Notes
- Slide presentations
- Multimedia
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
Use of Web, Internet, Powerpoint, video, Excel, special software (GeoDa), email.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | ✓ | ✓ | |||
| Seminars | ✓ | ✓ | |||
| Laboratory Work | ✓ | ✓ | ✓ | ||
| Reading Assigment | ✓ | ✓ | |||
| Tutorial | ✓ | ✓ | ✓ | ||
| Project | ✓ | ✓ | ✓ | ||
| Written assigments | ✓ | ✓ | ✓ | ||
| Exams | ✓ | ✓ | ✓ | ||
| Total |
Student Assessment
Description
Projects (written) and oral presentations.
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)
- Oral Exams (Formative, Summative)
- Performance / Staging (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
- Report (Formative, Summative)
Last Update
08-03-2023
