Course Details

Course Information Package

Course Unit TitleREMOTE SENSING AND GIS
Course Unit CodeCET450
Course Unit Details
Number of ECTS credits allocated5
Learning Outcomes of the course unitBy the end of the course, the students should be able to:
  1. Understand the basic concepts and definition of remote sensing, energy sources, radiation principles and the Global Positioning System.
  2. Identify remote sensing platforms and sensors and describe the characteristics of sensors related to their spatial, spectral and temporal resolution.
  3. Describe and apply geometric correction, radiometric correction and atmospheric correction algorithms on satellite imagery using ERDAS Imagine software.
  4. Apply Unsupervised Classification method using different algorithms.
  5. Identify training sites and apply supervised classification using algorithms: parallelepiped classifier, centroid k means, maximum likelihood
  6. Describe vegetation Indices and their use in satellite remote sensing.
  7. Describe Geographical Information Systems, explain its importance and describe applications.
  8. Analyse and apply different types of layer (point, line, polygon) and different type of data.
Mode of DeliveryFace-to-face
PrerequisitesCET108Co-requisitesNONE
Recommended optional program componentsNONE
Course Contents

Introduction: Use basic concepts of remote sensing. Identify Energy Sources and Radiation Principles. Use the Global Positioning System.

Satellite Remote Sensing: Identify remote sensing platforms and sensors (spatial, spectral, temporal resolution). Describe different types of sensors for different applications, advantages and disadvantages. Define Electronic and Multiband Imaging.

Image Pre-Processing: Define geometric correction, radiometric correction. Apply corrections for missing scan lines, de-stripping, terrain effects and sensor calibration. Describe and apply atmospheric correction methods. Create Image Rectification and Restoration.

Digital Image Processing: Explain the Fundamentals of Visual Image Interpretation. Apply Unsupervised Classification method. Identify training sites. Apply classification algorithms: parallelepiped classifier, centroid k means, maximum likelihood. Describe vegetation Indices and their use in satellite remote sensing. Evaluate image classification results.

Geographical Information Systems: Describe Geographical Information Systems, explain its importance and describe applications. Describe spatial analysis and separation of map features as different layers for the representation and display of the results. Analyse and apply different types of layer (point, line, polygon) and different type of data.
Recommended and/or required reading:
Textbooks
  • “Computer Processing of Remotely-Sensed Images’’, Mather, P., Wiley, 2004.
References
  • “Introductory digital image processing”, Jensen, J.R., Prentice Hall, 2004.
  • “Introduction to Remote Sensing”, Campell, J.B., Guilford Press, 2002.
Planned learning activities and teaching methodsThe course will be presented through theoretical lectures in class and computer labs. The lectures will present to the student the course content and allow for questions. Part of the material will be presented using visual aids. The aim is to familiarize the student with the different and faster pace of presentation and also allow the instructor to present related material (photographs, videos etc) that would otherwise be very difficult to do. The learning process will be enhanced with the use of ERDAS Imagine software (remote sensing and GIS package) where practical exercises will be carried out weekly. Exercises will also be given as homework (final project) which will be part of their assessment. Besides from the notes taken by students in class, all of the course material will be made available through the class website and also through MOODLE. Finally the instructor will be available to students during office hours or by appointment in order to provide any necessary tutoring.
Assessment methods and criteria
Assignments20%
Tests20%
Final Exam60%
Language of instructionEnglish
Work placement(s)NO

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