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Choose semester and course offering
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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
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Literature and preparations
Specific prerequisites
AG1321 Remote Sensing Technology or equivalent
AG2413 Digital Image Processing and Application or equivalent
Recommended prerequisites
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Equipment
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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
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Opportunity to raise an approved grade via renewed examination
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Examiner
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 FAG3106Offered by
Main field of study
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Education cycle
Third cycle
Add-on studies
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Contact
Yifang Ban yifang@kth.se
Supplementary information
The course replaces the previous course F1N5510: Knowledge-based Remote Sensing 7,5 credits.