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102-0617-01L  Methodologies for Image Processing of Remote Sensing Data

SemesterSpring Semester 2016
LecturersI. Hajnsek, O. Frey, M. A. Siddique
Periodicityyearly recurring course
Language of instructionEnglish


AbstractThe aim of this course is to get an overview of several methodologies/algorithms for analysis of different sensor specific information products. It is focused at students that like to deepen their knowledge and understanding of remote sensing for environmental applications.
ObjectiveThe course is divided into two main parts, starting with the brief introduction to remote sensing imaging (4 lectures) and is followed by the introduction into different methodologies (9 lectures) for the quantitative estimation of bio-/geo-physical parameters. The main idea is to deepen the knowledge in remote sensing tools in order to be able to understand the information products, with respect to quality and accuracy.
ContentEach lecture will be composed of two parts:
Theory: During the first hour, we go trough the main concepts needed to understand the specific algorithm.
Practice: During the second hour, the student will test/develop the actual algorithm over some real datasets using Matlab. The student will not be asked to write all the code from scratch (especially during the first lectures), but we will provide some script with missing parts or pseudo-code. However, in the latest lectures the student is supposed to build up some working libraries.
Lecture notesHandouts for each topic will be provided.
LiteratureSuggested readings:
T. M. Lillesand, R.W. Kiefer, J.W. Chipman, Remote Sensing and Image Interpretation, John Wiley & Sons Verlag, 2008
J. R. Jensen, Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall Series in Geograpic Information Science, 2000