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* Retrieved from Course syllabus FAG3106 (Autumn 2018–)

Content and learning outcomes

Course contents

1)  Earth Observation Big Data

2)  Image Pre-processing

3)  Advanced Image Analysis

4)  Advanced Image Classification

5)  Digital Change Detection

6)  Earth Observation Big Data Analytics

7)  Remote Sensing Applications

Intended learning outcomes

This course intends to provide a comprehensive overview of sophisticated techniques for acquiring remotely sensed data, state-of-the-art algorithms for image processing and analysis, and real-world applications of remote sensing in various fields such as urban planning, environmental monitoring and natural resource management.

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites

AG1321 Remote Sensing Technology or equivalent

AG2413 Digital Image Processing and Application or equivalent

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

Introductory Digital Image Processing: A Remote Sensing Perspective (4th Edition)

Multitemporal Remote Sensing: Methods and Applications

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F

Examination

  • LAB1 - Laboratory exercises, 3,0 hp, betygsskala: P, F
  • PRO1 - Project work, 4,5 hp, betygsskala: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

LAB1 - Laboratory Work, 3.0 credits, grade scale: P, F

PRO1 - Project, 4.5 credits, grade scale: P, F

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Yifang Ban

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web FAG3106

Offered by

ABE/Urban Planning and Environment

Main field of study

No information inserted

Education cycle

Third cycle

Add-on studies

No information inserted

Contact

Yifang Ban yifang@kth.se

Supplementary information

The course replaces the previous course F1N5510: Knowledge-based Remote Sensing 7,5 credits.

Postgraduate course

Postgraduate courses at ABE/Urban Planning and Environment