LEARNING OUTCOMES
The aim of the course is to understand specialized applications of remote sensing in:
- Urban environment
- Agricultural crops
- Monitoring of natural disasters
- Water management
- Marine environment
- Monitoring of targets and environmental pollution
- Infrastructure and energy projects
- Specialized methods of Artificial Intelligence and analysis of large amounts of satellite data
General Competencies
- Search, analysis and synthesis of data and information, using the necessary technologies
- Decision-making
- Autonomous work
- Project planning and management
COURSE CONTENT
- Spatial Changes in urban environment and atmospheric quality
- Flood monitoring
- Monitoring earthquakes, micro-movements and erosion
- Fire monitoring and mapping
- Estimation of rainfall and snowfall
- Classification of agricultural crops
- Mapping of inaccessible coastal areas and wetlands
- Water quality techniques and river sediment calculation techniques
- Extraction of bathymetry from satellite data
- Archaeological depictions and excavations
- Specialized machine learning methods in satellite image classification
- Time series and techniques for large volume of satellite data mining (Big dada and Datamining).
- Identifying and tracking goals
- Use of Remote Sensing in infrastructure and energy projects
- Special applications of remote sensing software (ENVI, eCognition)
STUDENT EVALUATION
- Multiple-choice final written exam and development questions(60%)
- Semester theme(4 0%)
Language of the examination: Greek (English if needed, e.g., Erasmus+students)
RECOMMENDED BIBLIOGRAPHY
Greek:
1. Skianis Eim. G., Nikolakopoulos G. K., Vaiopoulos A. D. 2012. “Remote Sensing” ION Publications 336sel.
2. Kartalis K., C., 2007, Fidas, “Principles & Applications of Satellite Remote Sensing”, V. Gkiourdas Ekdotiki, Athens.
3. Mertikas S.P., 2006, “Remote Sensing and Digital Image Analysis”, ION Publications
English:
1. Campbell J.B., 2006. Introduction to Remote Sensing, The Guilford Press, New York.
2. Cracknell A.P., L. Hayes, 2007. Introduction to Remote Sensing, CRC Press.
3. Jensen J.R., 2005. Introductory Digital Image Processing: A Remote Sensing Perspective. Prentice Hall.
4. Lillesand S. M.,R.W. Kiefer, J.W. Chipman, 2007. Remote Sensing and Image Interpretation. Wiley.
5. Mather P., 2004. Computer Processing of Remotely Sensed Images: An Introduction. Wiley.
6. Sabins F.F., 1997. Remote Sensing: Principles and Interpretation, W. H. Freeman & Co., New York.
7. Schowengerdt R.A., 2006. Remote Sensing: Models and Methods for Image Processing, Academic Press.