Environmental Remote Sensing and Digital Image Analysis

Course Information
TitleΠΕΡΙΒΑΛΛΟΝΤΙΚΗ ΤΗΛΕΠΙΣΚΟΠΗΣΗ & ΨΗΦΙΑΚΗ ΑΝΑΛΥΣΗ ΕΙΚΟΝΑΣ / Environmental Remote Sensing and Digital Image Analysis
Code0309Ε
FacultyAgriculture, Forestry and Natural Environment
SchoolForestry and Natural Environment
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CommonYes
StatusActive
Course ID420000462

Class Information
Academic Year2017 – 2018
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600101143
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
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)
  • English (Instruction, Examination)
Learning Outcomes
- to seek satellite images and other ancillary data on the internet. - to correct (pre-process) raw satellite data. - to implement basic and advanced techniques of interpretation and analysis of satellite images. - to produce thematic maps from satellite image analysis. - to estimate the accuracy of the produced maps. - to employ change detection analysis methods.
General Competences
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work autonomously
Course Content (Syllabus)
Characteristics of the electromagnetic spectrum (electromagnetic radiation models, radiation path, atmospheric effects, interaction with the objects of the earth's surface). Historical development of Remote Sensing (aerial photography, satellite imagery, sensor types). Image display (hardware, formats, software, spatial-temporal-spectral-radiometric resolution, metadata). Image correction (systematic errors, geometric - atmospheric - topographic corrections). Image enhancement (filters, texture analysis) and mosaicking. Image analysis and thematic information extraction (creation of thematic maps). Transformations (vegetation indices, tasselled cap, principal components analysis). Image classification (supervised, non-supervised) and thematic map accuracy assessment. The practical work is done using the ERDAS Imagine software. Transformations (tasselled cap, principal components analysis). Change detection methods (land cover / use changes, monitoring of forest ecosystems, forest fire mapping, monitoring post-fire vegetation recovery). Advanced image classification techniques (object-oriented classification , SVM).
Keywords
Remote sensing
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
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
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures501.8
Seminars100.4
Laboratory Work802.9
Project281
Total1686
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 (2006). Αρχές και εφαρμογές δορυφορικής τηλεπισκόπησης. Β. Γκιούδας Εκδοτική, Αθήνα. Μερτίκας Σ. (1999) Τηλεπισκόπηση και Ψηφιακή Ανάλυση Εικόνας. Εκδοτικός Όμιλος Ίων, Αθήνα ISBN 960-405-949-1
Last Update
10-04-2017