Photogrammetry and Remote Sensing

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Course responsible: Yifang Ban
Course examinor: Yifang Ban
Lecturer: Yifang Ban (YB)
Andrea Nascetti
Teaching Assistant:

Sebastian Hafner

Textbook: Lillesand, T. M. and R. W. Kiefer. 2015. Remote Sensing and Image Interpretation, 7th edition, John Wiley and Sons, Inc., New York.

Course Description 

This course will provide an overview of photogrammetry and remote sensing theory, the ways in which remote sensing systems are used to acquire data, how these data may be analyzed digitally, and how the information is used in various real-world applications such as urban planning, disaster damage assessment, environmental change monitoring, among others.

At the end of the course, students should have a good knowledge on how to acquire different types of remote sensing imagery and the basic algorithms to process and analyze remotely sensed images. Students should also be capable of undertaking basic digital image analysis, developing photogrammetry for production of spatial data, planning aerial photogrammetric spatial data production, and analysing the quality of the results.




Lectures
See schedule.

Laboratory Sessions
Laboratory sessions involve understanding and interpretation of remote sensing data and application of digital image processing techniques to remote sensing data. Most meetings of the lab groups are held digitally in Fall, 2020. Students will work with Google Earth Engine, ENVI and/or PCI Geomatica processing and analysis software.

Grading and Examination
There will be a written examination at the end of the course. 
Exam grading: A-F  (3.5c)
Lab grading: Pass or Fail (4.0c)
Project: Pass or Fail (1.5c)

The final grade is combined from the results on the exam, project and the bonus points.

Please note:
1.  Deadline for all labs is usually one week after the lab (see schedule or bilda assignments). Eight (or less, out of 100) bonus points towards the FINAL marks will be given to students who submit their lab reports on time.

2.  Please observe KTH's guidelines on academic honesty (i.e., no cheating or copying).

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