Αcquisition, processing and management of environmental data
| Title | Απόκτηση, επεξεργασία και διαχείριση περιβαλλοντικών δεδομένων / Αcquisition, processing and management of environmental data |
| Code | ΠΠΒΑΑ04-2018 |
| Faculty | Engineering |
| School | Civil Engineering |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter |
| Common | Yes |
| Status | Active |
| Course ID | 600016655 |
Programme of Study: PMS PPVA 2018-2023
Registered students: 13
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 9 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors | |
| Class ID | 600287125
|
EPIChallenges
- Sustainable Transformation
- European Values
- Global Health
Type Of Offer
- Disciplinary Course
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600287125
- At the Website of the School:
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
- English (Instruction, Examination)
Learning Outcomes
Upon successful completion of the course, students will have understood:
• The full potential of Geographic Information Systems and the value of producing thematic maps
• the distinction between spatial and descriptive data
• the importance of personal data management
• the legal framework that governs them and they will have acquired the skill of distinguishing sensitive data (personal, social, environmental).
Also they will have:
• Appropriate knowledge of Photogrammetry – Geoinformation Systems and Photointerpretation – Remote Sensing and their application in matters of obtaining and processing information about the environment, as follows: Watershed - hydrographic network. Coastal areas. Erosion phenomena – landslides, cracks. Residential areas. Monuments and historical centers. Road network. Sustainable development.
They will also have knowledge of:
• Basic statistical distributions.
• Classical methods of statistical analysis.
• Non-parametric analysis methods.
• Graphical analysis of data.
• Simple and multiple regression.
• Introduction to the statistical analysis of spatial variables. The kriging method.
• Use of special statistics packages for PC.
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
- Work in teams
- Work in an international context
- Work in an interdisciplinary team
- Design and manage projects
- Appreciate diversity and multiculturality
- Respect natural environment
- Demonstrate social, professional and ethical commitment and sensitivity to gender issues
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to GIS. Geographic Data Elements Import spatial and descriptive data into GIS. Database management. Analysis of geographic information. Presentation of analysis and results.
Introduction to the legal regime of personal, social and environmental data management.
Appropriate knowledge of Photogrammetry - Geoinformation Systems and Photointerpretation - Remote Sensing and their application in matters of obtaining and processing information about the environment, as follows:
Watershed - hydrographic network. Coastal areas. Erosion phenomena – landslides, cracks. Residential areas. Monuments and historical centers. Road network. Sustainable development.
Introduction to measurements and measuring instruments. Organization and avoidance of measurement errors.
Data management in general and digital data in particular.
Introduction to Data Analysis and Statistics.
Basic statistical distributions. Classical methods of statistical analysis. Non-parametric methods of analysis.
Graphical data analysis. Correlation, simple and multiple regression.
Time series analysis.
Introduction to spatial variable analysis. Geostatistical methods.
Use of PC data analysis software.
Educational Material Types
- Notes
- Slide presentations
- Video lectures
- Multimedia
- Book
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 120 | 4.8 | ✓ | ✓ | |
| Reading Assigment | 50 | 2 | ✓ | ✓ | |
| Written assigments | 50 | 2 | ✓ | ✓ | |
| Exams | 6 | 0.2 | ✓ | ✓ | |
| Total | 226 | 9.0 |
Student Assessment
Description
Individual or group assignments during the semester
Written or oral exams (οραλ where necessary or required)
Student Assessment methods
- Written Exam with Multiple Choice Questions (Formative, Summative)
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
- Oral Exams (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Additional bibliography for study
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Last Update
31-12-2023
