GEOG 620        Fall 2009

Geographical Information Systems

Class Hours:                 Monday & Wednesday 13:10 -14:50                                 

Location:                      HSS 290 (the Geographic Teaching Lab)

Course Materials:          P:\courses\G620\Fall2008 

 

Instructor:                     XiaoHang Liu (xhliu@sfsu.edu)

Office Location:            HSS 269, 415-338-7509

Office hours:                 M & W 10:30 – 11:30 & 15:30-16:00

 

Teaching Assistant:       Seth Hiatt, HSS 290 (shiatt @sfsu.edu)

Text:

1. B = Bolstad, P. GIS Fundamentals. Eider Press.

2. Z = Zeiler, M., 1999. Modeling our world: the ESRI Guide to Geodatabase Design. ESRI Press, p.195.

Software:

Student license of ArcView 9.3 available to enrolled students. Note this license does not support Geodatabase.

Course Description:

This course is an advanced GIS course with emphasis on vector GIS. The first halve is on advanced spatial analysis which includes data model, data acquisition, and model builder. The second halve introduces the ESRI geodatabase model and its functions such as domain, relationship, topology, and network analysis. Direct experience in the use of GIS tools (particularly ArcGIS desktop 9) is emphasized.

Prerequisites: Familiarity with ArcGIS 9. Geog. 603 or equivalent is required, Geog. 621 is recommended.

 

Course Objectives:

Materials: A USB thumb drive is recommended for backup purpose.  

Methods of Instruction: Lecture, demonstration, laboratory, and discussion. For most assignments, student should plan on working two to three extra hours in addition to the assigned lab time.

Grading and Exams: There will be 7 lab exercises, 1 project, and 2 exams. All lab exercises, project, and exams are required to pass this class. All assignments and exams must be submitted by the specified deadline. No late homework will be accepted!

Grading will be on a percentage basis: 100-90% A, 89-80% B, 79-70% C, 69-60% D. Plus/minus grades will be assigned for points near the margins.

The course grade will be based on the following allocations: 40% labs, 40% exams, 20% project.

Housekeeping:

 Statement on Cheating and Plagiarism: Cheating is the actual or attempted practice of fraudulent of deceptive acts for the purpose of improving one’s grade or obtaining course credit; such acts also include assisting another to do so. Typically, such acts occur in relation to examinations. However, it is the intent of this definition that the term “cheating” not be limited to examination situations only, but that it includes any and all actions by a student that are intended to gain an unearned academic advantage by fraudulent or deceptive means. Plagiarism is a specific form of cheating which consists of the misuse of the published and/or unpublished works of the others by misrepresenting the material (i.e. their intellectual property) so used as one’s own work. Penalties for cheating and plagiarism range from a 0 to F on a particular assignment, through an F for the course, to expulsion from the University. For more information on the University’s policy regarding cheating and plagiarism, refer to University Catalog (Policies and Regulations).

 American with Disabilities Act (ADA) Accommodation: The University is committed to providing academic accommodation to students with disabilities. The Disabilities Resource Center provides support services and specialized assistance to students with disabilities. Individuals with physical, perceptual, or learning disabilities as addressed by the American with Disabilities Act should contact the Disabilities Resources Center for information regarding accommodations. Please notify your instructor so that reasonable efforts can be made to accommodate you. If you expect accommodation through the Act, you must make a formal request through the Disabilities Resources Center in Student Services Building 110, Telephone: 415-338-2472.

 Statement on Disruptive Classroom Behavior: The classroom is a special environment in which students and faculty come together to promote learning and growth. It is essential to this learning environment that respect for the rights of others seeking to learn, respect for the professionalism of the instructor, and the general goals of academic freedom are maintained. Differences of viewpoint or concerns should be expressed in terms which students and faculty may learn to reason with clarity and compassion, to share of themselves without losing their identities, and to develop an understanding of the community in which they live. Student conduct that disrupts the learning process shall not be tolerated and may lead to disciplinary action and/or removal from class. Some specific examples include talking during lecture, cellular phones, and pagers.

Syllabus and schedule are subject to change in the event of extenuating circumstances.

Week

Dates

Lecture

Lab

Reading

1

8/26

Overview, diagnostic exam

 

2

8/31, 9/2

Spatial Data 

Lab1

B. Ch. 7

3

9/9

Vector Data Analysis   

Lab 2

B. Ch. 9

4

9/14,  9/16

Model Builder

Lab 3

 

5

9/21,  9/23

Exam I

 

6

9/28,  9/30

Geodatabase I

Lab 4

B. Ch. 2

7

10/5,  10/7

Geodatabase II

Lab 5

Z. Ch. 1&5

8

10/12, 10/14

Relationship and Topology

Lab 6

Z. Ch. 6

9

10/19, 10/21

Network Analysis I

Lab 7

Z. Ch. 8

10

10/28

Network Analysis II

11

11/2, 11/4

Geodatabase Design

Exam II

 

12

11/9

Exam II 

Handout

13

11/16, 11/18

Individual  Project

Individual Project

 

14

11/23, 11/25

Fall recess, No class.

15

11/30, 12/2

Individual Project

Individual Project

 

16

12/7, 12/9

Project Presentation

Project Presentation

 

17

12/14, 12/16

Project Report Due