Remote Sensing I

Course Information
TitleΤηλεπισκόπηση Ι / Remote Sensing I
Code04YB024
FacultyEngineering
SchoolRural and Surveying Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
CoordinatorGeorgios Mallinis
CommonNo
StatusActive
Course ID600025733

Programme of Study: PPS Tmīmatos Agronómōn kai Topográfōn Mīchanikṓn (2025-sīmera)

Registered students: 100
OrientationAttendance TypeSemesterYearECTS
Core CoursesCore Courses425
Class Information
Academic Year2025 – 2026
Class PeriodSpring
Faculty Instructors
Instructors from Other Categories
Weekly Hours5
Class ID
600267799
Course Type 2021
Specific Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
Basic theoretical and applied knowledge related to remote sensing science. Knowledge and understanding of remote sensing sensors and platforms characteristics. Understanding essential optical RS image processing workflows.
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 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
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
History and general principles of Remote Sensing. Electromagnetic radiation and generally sensing systems. Photographic systems - Photointerpretation. Sensors and Sensing Platform. Digital processing of remotely sensed images. Radiometric errors - corrections. Geometric distortion - geometric transformations. Spectral and spatial image enhancement through radiometric transformations, filters, indices, Principal Component Analyis, Patern Recognition and Classification of digital images. Hyperspectral sensors - hyperspectral images.
Keywords
Satellite imary, Earth observation satellites, Earth observation data, Multispectral imagery
Educational Material Types
  • Notes
  • Slide presentations
  • 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
  • Use of ICT in Student Assessment
Description
The teaching of the course is performed through lectures and slide presentetions using PC and projector in the classroom. Students receive in electronic form their projects' subject and the material for the implementation of the laboratory exercise. In the PC labs there are installed licenses of specialized digital image processing software for the preparation of the students' project.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39✓
Laboratory Work26✓✓
Reading Assigment26✓
Project31✓
Exams3✓
Total125
Student Assessment
Description
Written examination in the theory lectures, writing in the form of a technical booklet of all exercises.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Assignment (Summative)
Bibliography
Course Bibliography (Eudoxus)
1. Αρχές και Εφαρμογές Δορυφορικής Τηλεπισκόπησης, Καρτάλης Κων/νος-Φείδας Χαράλαμπος
Additional bibliography for study
1.ΤΗΛΕΠΙΣΚΟΠΗΣΗ, 2016, Πανεπιστημιακές Παραδόσεις, Τσακίρη-Στρατή Μ., ΑΠΘ, σε ψηφιακή μορφή. 2. Παρουσιάσεις των διαλέξεων , οι οποίες αναπροσαρμόζονται κάθε χρόνο, παρουσιάσεις των ασκήσεων, Γιώργος Μαλλίνης, Χαράλαμπος Γεωργιάδης, Ναταλία Βερδέ, Τσακίρη-Στρατή Μ., ΑΠΘ, σε ψηφιακή μορφή
Last Update
24-02-2025