Welcome to CPSC 695 !
 | Contact information |
| Textbook and recommended reading |
| Course information |
| Course outline |
| Course evaluation |
| Project |
| Useful links |
1. Spatial
Databases: With Application to GIS
Philippe Rigaux, Michel O. Scholl, Morgan Kaufmann
Publishers, 2001
2.
Principles of Geographical Information Systems
P. Burough R. McDonnell 1998 Oxford University
Press
3.
Fundamentals of Geographical Information Systems
M.N.
DeMers, et al; John Wiley & Sons, 2nd
edition, 1999
4. Data Visualization in the GeoSciences
James Carr
Prentice Hall 2002
5. Statistical Analysis of Geographic Information
with Arcview GIS and ArcGIS
David Wong and Jay Lee, Wiley, 2005
Advanced geometric algorithms for
representation, analysis and visualization of GIS and other applied models Data
structures such as progressive mesh, ROAM, multidimensional Delaunay
triangulation, quadtree, trapezoidalization, and convex partitioning. Basic
techniques such as incremental, divide-and-conquer, sweep-plane, and dimension
reduction. Algorithms for surface simplification, culling, quality measurement
and error metrics.
Computational problems of
computing an overlay of two subdivisions, triangulating a polygon, computing
line segment intersection, and geometric database querying will be discussed. The impact of GIS characteristics on the
computability of these problems will be addressed. Selected techniques for
parallel algorithm implementation will also be discussed. Applications to other
areas, such as modeling of complex dynamic systems, optimization and
visualization will be covered.
The course is strongly recommended for graduate students who perform research in computer graphics, visualization, GIS, algorithms, modeling and computational geometry areas.
The objective
in offering this course is to study advanced algorithms in the area of applied
sciences, computer graphics and GIS. The course introduces geometric
data structures used for efficient representation and analysis of terrain
models. Algorithms for surface simplification, culling, quality measurement and
error metrics are discussed in details. The course
also reviews some known techniques for algorithm development, and includes
a discussion of some parallel algorithms.
The methods and techniques learned in the course find a variety of
applications in the areas of computer graphics, modeling, and spatial databases.
Some applications to simulation
of complex dynamic systems, optimization and visualization will also be
discussed. The assignment component of the course will involve an in-depth
analysis of a selected method, writing a research paper, and making a
presentation on a subject.
Ideally, on successful completion of this course, a student will be
familiar with a variety of methods in representation, optimization and
visualization in a variety of applications, will have a working knowledge of
advanced data structures and techniques, and be prepared to apply this knowledge
in related disciplines.
The course is suitable for graduate
student enrolled in M. Sc or Ph. D program in CPSC Department, as well as
students enrolled in graduate degree granting programs in other departments,
including MGIS students. It exposes students to a variety of issues related to
both theoretical foundations of GIS and a variety of industrial applications.
|
Meet and Greet. Course Outline. |
|
Algorithmic foundations of GIS. Text 1: Ch 2.
|
|
Data models and representation in GIS. Text 1: Ch 2; Text 2; Text
3: Ch 2-3 |
|
Advanced
geometric data structures (progressive mesh, ROAM, Voronoi diagram, multidimensional
Delaunay triangulation, quadtree)
Text 1: Ch 5, Text 2: Ch. 9,10,11. |
|
GIS Open Data Source Introduction This lecture focuses on very useful and accessible Open GIS data sources In addition, Open Earthquake Data also being briefly introduced. Introduction of Google Map and Google Earth The basics of the Google Maps interface, the fundamentals of the Google Maps API, and how to organize and translate existing information into a format that can successfully be used within Google Maps and Google Earth applications. |
Invited lecture
|
Algorithm
design techniques (incremental, divide-and-conquer, sweep-plane,
dimension reduction) Text 1: Ch5, Text 2: Ch 9,10,11. |
|
Algorithm
design techniques. |
| Algorithmic
techniques for dealing with large data sets. Text book Ch 5, Ch 7. |
| Lectures on data quality and errors. |
| QUIZ |
| Statistical Analysis in GIS. Text 6. Lectures on Statistical Analysis in GIS. |
| Lecture on statistical analysis 1 |
| Lecture on statistical analysis 2 |
| Clustering, statistical analysis and autocorrelation in GIS Lecture on statistical analysis and autocorrelation |
| http://www.math.yorku.ca/SCS/Gallery/ |
| Variance demo |
Week 10 Nov 15-22
| GIS hardware. Lecture on GIS Visualization Software and Hardware |
| Lecture on Multiresolution and rendering |
| Lecture on Data mining |
| Lecture on databases, interpolation and networks. |
| Future directions |
| Final project presentations |
Three components are included in the determination of the course grade.
| Component | Component Weight |
| Project | 40% |
| Assignments/Quiz(es) | 40% |
| Presentations | 20% |
Assignments/Quizzes can be in the form of a written test, a research paper analysis, a presentation on the subject, or a problem to solve over some period of time. There are two presentations in this course (each weighted 10%). First one includes a 45 min presentation on an assigned subject, a 30 min presentation at the end of the term is related to the project.
Assignment 1 - Term paper (10%) and Presentation (10%)
Due: Sept 27, 2016, 9:00 am
Assignment 1 can be downloaded here.
List of topics:
-GIS software/GIS hardware
-GIS databases
-Geometric data structures in GIS
-Algorithms in GIS
-GIS visualization
-Web-based GIS
-Sensor-based GIS
-Remote sensing and GIS
-GIS for Virtual Reality
-GIS and biometrics
-Security in data representation
Note: a 30 minute presentation on the chosen subject will be scheduled in October
Quiz (20%)
Assignment 3 - Practical Assignment (10%)
Due: November 21th, Monday, 9:00 am by e-mail to your instructor
Excel data file can be downloaded.
Useful GIS Software links:
TIBCO software: http://spotfire.tibco.com/en/demos.aspx
GrassGIS is an open source project: http://grass.itc.it/download/index.php
A trial version (60 days) of ArcGIS is available at : http://www.esri.com/software/arcgis/arcview/eval/evaluate.html
For data analysis software, Acastat (and others) can be found at http://www.newfreedownloads.com/find/data-analysis.html
S-plus trial version statistical analysis software S-PLUS Trial Edition 6.2 Download
As a course policy, Assignments received after the due date will not be accepted. However, due to extenuating circumstances, the assignment can be accepted up to 3 days late with a deduction of 10% for each late day.
Collaboration
Students are
encouraged to discuss the assignments and methods of solution with other
students. All work that is handed in as a solution to the assignment must be
original work of the student. Any student found copying all or part of an
assignment from another student or another source without proper acknowledgement
of the copyright will face consequences outlined in
Plagiarism/Cheating/Other Academic Misconduct sections of the University
calendar.
Quizzes are essential part of this course and intended to help students to develop valuable research skills, such as ability to solve problems using knowledge obtained from the course, ability to critically analyze methods and techniques, ability to compare and contrast different solutions, ability to write a critique on a paper or a scientific article, and ability to compare different approaches to the same problem.
Individual research project is an essential component of this course. Students are expected to select a topic of research project from the course outline, which can include theoretical research in the area or applied studies (including a programming component in OpenGL, ArcView, Geo/SQL and Visual_Data).
Project requirements can be found here.
This page was last updated on 01/06/06
Department of Computer Science
University of Calgary
2500 University Dr. N.W.
Calgary, AB, T2N1N4
Office: MS 269
Phone: (403) 220-5105
Fax: (403) 284-4707
