Advanced Remote Sensing

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Course Examiner Professor Yifang Ban,


Yifang Ban

Alexander Jacob

Helén Rost, BLOM

Torbjörn Rost, Metria

Teaching Assistant Osama A Rhaman Yousif
Literature Jensen, J.R., 2005. Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd edition, Prentice Hall, Upper Saddle River, New Jersey. 526 pp.
Prerequisites AG1321, Remote Sensing Technology, 7.5c or equivalent

Course Description 

This course aims to provide every student with a working knowledge of sophisticated methods and techniques for collecting, processing and analysing remotely sensed data; as well as the theory and practice of undertaking remote sensing projects. Throughout the course, emphasis will be placed on image processing, image analysis, image classification, remote sensing and GIS data integration, and applications of remote sensing in geographical analysis and environmental monitoring. 

The course is composed of lectures, laboratory exercises and student presentations.

Laboratory Sessions 
During laboratory sessions, you will have the opportunity to improve your skills on digital image processing and analysis, as well as to conduct a remote sensing project. All meetings of the lab groups are held weekly in the GEO-Lab using PCI Geomatica image processing and analysis software. Students who work two in a group should submit one group report for each lab/project. 

Student Presentations 
One of the requirements for this course is to present a remote sensing project to the class. More details will be published soon. 

Exam grading: A-F (3 ECTS)

Lab grading: Pass or redo (3 ECTS)

Project grading: Pass or redo (1.5 ECTS)

Please note: 
1. All labs have a deadline. If not specified differently in the lab instructions, the due date is always one week after the lab session. Labs are to be uploaded to the Bilda system before the deadline to not forfeit the chance for bonus points. 6 bonus points (1 for each lab) towards the the final grade will be given to students who submit their lab reports and project reports on time.
2. Please observe KTH’s guidelines on academic honesty.


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