Remote sensing of environment-Applications
| Title | Περιβαλλοντική Τηλεπισκόπηση-Εφαρμογές / Remote sensing of environment-Applications |
| Code | 84Ε |
| Faculty | Agriculture, Forestry and Natural Environment |
| School | Forestry and Natural Environment |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Common | No |
| Status | Active |
| Course ID | 600019479 |
Programme of Study: PPS Tmīmatos Dasologías kai Fysikoý Perivállontos (2020-sīmera)
Registered students: 5
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Elective Courses | Elective Course belonging to the selected specialization (Elective Specialization Course) | 8 | 4 | 2 |
| Elective Courses | Elective Course belonging to the selected specialization (Elective Specialization Course) | 8 | 4 | 2 |
| Elective Courses | Elective Course belonging to the selected specialization (Elective Specialization Course) | 8 | 4 | 2 |
| Elective Courses | Compulsory Course belonging to the selected specialization (Compulsory Specialization Course) | 8 | 4 | 2 |
| Elective Courses | Elective Course belonging to the selected specialization (Elective Specialization Course) | 8 | 4 | 2 |
| Elective Courses | Elective Course belonging to the selected specialization (Elective Specialization Course) | 8 | 4 | 2 |
| Academic Year | 2023 – 2024 |
| Class Period | Spring |
| Faculty Instructors | |
| Class ID | 600232259
|
Class Schedule
| Building | Δασολογίας (Φοίνικας) - κτίριο β |
| Floor | Όροφος 1 |
| Hall | ΑΙΘΟΥΣΑ ΑΣΚΗΣΕΩΝ ΔΑΣΙΚΗΣ ΒΙΟΜΕΤΡΙΑΣ (505) |
| Calendar | Τρίτη 14:00 έως 16:00 |
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600232259
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=5185
Language of Instruction
- Greek (Instruction, Examination)
- ONLY IN GREEK
Learning Outcomes
Upon successful completion of the course, students will be able to:
● Search the internet for satellite imagery and other supporting information.
● Correct (preprocess) primary satellite data.
● Apply basic techniques for interpretation and analysis of satellite imagery.
● Produce thematic maps from the analysis of satellite images.
● Apply basic satellite image analysis processes using modern programming tools and specialized software.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
Course Content (Syllabus)
Introduction to Environmental Remote Sensing (definitions and introductory concepts of remote sensing science, historical background, multi-spectral and hyperspectral satellite earth observation systems, types of imagers). Digital image characteristics (spatial, temporal, spectral and radiometric resolution, pseudo-color imaging, spectral channel combinations for selected applications). Methods, techniques, systems and software for digital preprocessing and analysis of satellite data (introduction to Python programming language, open-source image processing software, basic techniques for processing and analysis of optical remote sensing data). Digital image classification (principles of satellite image interpretation, objects’ spectral signatures, supervised and unsupervised classification, introduction to the basic principles of machine learning and pattern recognition, clustering algorithms, the most important contemporary classifiers). Effect of the biological and physical characteristics of objects on digital analysis. Sampling and accuracy estimation (the concepts of precision and accuracy, sampling methods and design, the error matrix, and statistical measures of accuracy of the generated thematic map). Introduction to the basic principles of non-multispectral remote sensing systems (thermal, hyperspectral, active microwave and LiDAR systems). Applications of remote sensing in monitoring, management, protection and development of natural ecosystems and the environment (presentation of important applications of satellite remote sensing in natural resource monitoring and forestry, the European Copernicus Programme, current trends in the use of satellite data and products for long-term monitoring of the environment, applications using time series data, modern web-based tools). The practical training is carried out using specialized open-source software and modern programming languages.
Keywords
Remote sensing
Educational Material Types
- Notes
- Slide presentations
- Multimedia
- 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
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 12 | 0.4 | ✓ | ✓ | |
| Laboratory Work | 12 | 0.4 | ✓ | ✓ | |
| Reading Assigment | 9 | 0.3 | ✓ | ✓ | |
| Written assigments | 25.5 | 0.9 | ✓ | ✓ | |
| Exams | 1.5 | 0.1 | ✓ | ✓ | |
| Total | 60 | 2 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Labortatory Assignment (Summative)
Bibliography
Course Bibliography (Eudoxus)
Καρτάλης Κ. και Χ. Φείδας (2012). “Αρχές και εφαρμογές δορυφορικής τηλεπισκόπησης”. Εκδόσεις ΤΖΙΟΛΑ, Αθήνα, ISBN: 978-960-418-401-9, Κωδικός Βιβλίου στον Εύδοξο: 22767582.
Last Update
04-04-2024
