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Course module: 2IMA20
2IMA20
Algorithms for geographic data
Course info
Course module2IMA20
Credits (ECTS)5
Category-
Course typeGraduate School
Language of instructionEnglish
Offered byEindhoven University of Technology; Mathematics and Computer Science; Computer Science;
Is part of
Computer Science and Engineering
Contact persondr. K.A. Buchin
Telephone5927
E-mailk.a.buchin@tue.nl
Lecturer(s)
Contactperson for the course
dr. K.A. Buchin
Other course modules lecturer
Responsible lecturer
dr. K.A. Buchin
Feedback and reachability
Other course modules lecturer
Co-lecturer
dr. W. Meulemans
Other course modules lecturer
Academic year2016
Period
3  (06/02/2017 to 23/04/2017)
Starting block
3
TimeslotE: E - Mo 9-10, Tu 5-8, Th 1-4
Course mode
Fulltime
RemarksCourse is replaced by 2IMG15.
Registration openfrom 15/06/2016 up to and including 15/01/2017
Application procedureYou apply via OSIRIS Student
Explanation-
Registration using OSIRISYes
Registration open for students from other department(s)Yes
Pre-registrationNo
Waiting listNo
Number of insufficient tests-
Number of groups of preference1
Learning objectives
At the end of this course students should be able to

• describe algorithms and data structures to solve fundamental computational challenges on geographic data

• decide which algorithmic technique or data structure to use in order to solve a given basic analysis task on geographic data,

• analyze problems on geographic data, and design efficient solutions using concepts and techniques from the course.
Content
A significant part of today's data is geographic, has a geographic component (is geo-referenced), or benefits from geographic interpretation. To analyze these data requires advanced algorithmic tools. This course takes a data-driven perspective on algorithm design for geographic data. The course has three parts:

• fundamentals: fundamental geographic concepts, geographic data models (raster, vector) and data representation, data structures for geographic data like R-trees, algorithms for terrain data

• analysis of movement data: Advances in tracking technology (like GPS) give rise to increasing amounts of location data of moving entities. In this part we will cover algorithms for fundamental analysis tasks like similarity, clustering, simplification, movement patterns and segmentation

• automated cartography: To visualize the results of a geographic analysis, automated cartography techniques are needed. In this course we will cover techniques for tasks like map labeling, map generalization and simplification, generating schematic and thematic maps, and algorithms for specific types of maps like cartograms
Entrance requirements
Entrance requirements tests
-
Assumed previous knowledge
2IL50 Data structures
Previous knowledge can be gained by
-
Resources for self study
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Bachelor College or Graduate School
Graduate School
URL study guide
http://www.win.tue.nl/~kbuchin/teaching/2IMA20/
URL study guide
http://www.win.tue.nl/~kbuchin/teaching/2IMA20/
Required materials
-
Recommended materials
The material for the course consists of original papers, survey papers and lecture notes.
Instructional modes
Lecture

General
-

Remark
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Lecture with notebook / PC

General
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Remark
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Tutorial

General
-

Remark
-
Tests
Assignment(s)
Test weight100
Minimum grade6
Test typeAssignment(s)
Number of opportunities1
OpportunitiesBlock 3
Test duration in minutes-

Assessment
-

Remark
-

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