Αcquisition, processing and management of environmental data
| Title | Απόκτηση, επεξεργασία και διαχείριση περιβαλλοντικών δεδομένων / Αcquisition, processing and management of environmental data |
| Code | ΠΠΒΑΑ04 |
| Faculty | Engineering |
| School | Civil Engineering |
| Cycle / Level | 2nd / Postgraduate, 3rd / Doctorate |
| Teaching Period | Winter |
| Common | Yes |
| Status | Inactive |
| Course ID | 600001533 |
| Academic Year | 2016 – 2017 |
| Class Period | Winter |
| Faculty Instructors | |
| Class ID | 600066301
|
| Section | Instructors |
|---|---|
| 1. ΠΠΒΑΑ04 | Maria Lazaridou, Margaritis Vafeiadis, Ioannis Yfantis |
Course Type 2016-2020
- Background
- General Knowledge
- Skills Development
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600066301
- Other: ppva.civil.auth.gr
Language of Instruction
- Greek (Instruction, Examination)
Learning Outcomes
After successfully attending the course the postgraduate student should be capable of:
collecting, inputting and processing data with G.I.S., based on geographic and time parameters.
extracting the desired pieces of information and presenting the outcome of the relevant studies,
evaluating the Photogrametry-Geoinformation Systems and Image Interpretation-Remote Sensing methods in order to implement them, depending on the problem in question, after having already analyzed its environmental components,
selecting the appropriate methods and equipment with the prospect to use them for the study of the subjects included in the course syllabus,
applying the proper statistical methods and techniques in the process of solving environmental problems,
successfully implementing special statistical software
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Work autonomously
- Work in teams
- Work in an international context
- Work in an interdisciplinary team
Course Content (Syllabus)
Introduction to GIS. Geographical data elements. Introduction of spatial and descriptive data in GIS. Database Management. Analysis of geographic information. Presentation and analysis of results.
Appropriate knowledge Photogrammetry - Geoinformation Systems and Photo-Interpretation - Sensing and implementation in information acquisition and processing issues for the environment, as the following: Catchment - river network. Coastal areas. Erosion - landslides, faults. Residential areas. Monuments and historical centers. Roads. Sustainable development.
Basic statistical distributions. Classical statistical methods. Non-parametric methods of analysis. Graphical data analysis. Simple and multiple regression. Introduction to statistical analysis of spatial variables. The kriging method. Using special statistics PC software
Keywords
measurements, data, data analysis, GIS
Educational Material Types
- Notes
- Slide presentations
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
Description
The course applications require the use of modern computer and software. These are used during lectures, the student workshops and the preparation of their individual work.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 153 | 6.1 | ✓ | ||
| Laboratory Work | 30 | 1.2 | ✓ | ||
| Reading Assigment | 9 | 0.4 | |||
| Written assigments | 30 | 1.2 | |||
| Exams | 3 | 0.1 | ✓ | ||
| Total | 225 | 9 |
Student Assessment
Description
Students are assessed on the basis of small individual tasks during the duration of the course, the major individual assignments and final exams
Student Assessment methods
- Written Exam with Multiple Choice Questions (Formative, Summative)
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Assignment (Formative)
- Performance / Staging (Formative)
- Written Exam with Problem Solving (Formative, Summative)
Last Update
19-12-2016
