People.BrandonU.Ca » Dr. Dion J. Wiseman » Dr. Dion J. Wiseman » 38/42:376 GIS II

38/42:376 GIS II

 Spatial Data Management and Analysis

Instructor: Lecture, Dr. Dion J. Wiseman
Office: Brodie Room 4-07
Office Hours: Monday, Wednesday, Friday; 9:00 – 10:00 AM; or by Appointment
Phone: 727-9774
Email: wiseman@brandonu.ca

Required Text: Introduction to Geographic Information Systems, 8th ed. 2015, Chang.

Optional Text: Cartography: Thematic Map Design, 6th ed. 2009, Dent, et al.

Notes: 1) Copies of both texts will be available on reserve in the main library. 2) An earlier edition of either text is acceptable.

Course Description

The objectives of this course are to provide students with a sound theoretical foundation in the fundamentals of geographic information science (experience without theory is ignorance) and practical experience in the development and application of geographic information systems (theory without experience is fantasy). The intent is to develop both an understanding of geographic information science and the applications of geographic information systems that transcends any particular software application.  The lecture component of the course will provide a software-independent foundation in GIS by addressing the topics outlined below and discussing real and hypothetical examples of GIS applications using generic GIS terminology.

The lab component of the course will provide practical experience with ArcGIS Desktop 10, including the ArcMap, ArcToolbox, and ArcCatalog applications, and various extensions that provide additional functionality such as Spatial Analyst and 3D Analyst. Students are encouraged to work collaboratively on laboratory assignments, however, your individual proficiency in the use of GIS techniques introduced in lab will be evaluated through a timed lab midterm and lab final exams.

The prerequisite for this course is GIS I (38/42:286). Additional readings and/or assignments may be required of those who have not completed the prerequisite; please see me at the end of the first lecture period if you are one of these individuals.

MODIFIED Grading Scheme

Midterm 20/30%* > 90% A+ 70-72% B-
Final 20/30%* 85-89% A 67-69% C+
Lab Assignments 20% 28-35%* 80-84% A- 63-66% C
Lab Midterm 15% 22-15%* 77-79% B+ 60-62% C-
Lab Final 15% CANCELLED 73-76% B 50-59% D
Bonus (optional) 5% < 50% F
Total 100% * variably weighted

Tentative Course Outline

(follow links below to access lecture notes and readings)

1. Spatial Data Representation, the Object-based Model and Geodatabases (Geodatabase Demo)

  • Review of Raster /Vector Models
  • Georelational vs. Object-based
  • The Geodatabase Model
  • Subtypes, Topology Rules, Attribute Domains
  • Raster Data Catalogues
  • Terrain Datasets
  • Relationship Classes, Network Classes
  • Topological Editing
  • Map Topologies

2. Managing Geospatial Databases (Tables Demo)

  • Functions of a DBMS
  • Tables and Data Relations
  • Types of Relations – Relate vs. Join
  • Attribute-based Operations

3. Exploratory Data Analysis

  • Descriptive Methods
  • Query by Attribute & Location
  • Relational Algebra
  • Boolean Logic
  • Querying Rasters

4. Vector Data Analysis (Simpson’s Vector Demo)

  • Buffers and Setbacks, Applications of
  • Map Overlay: Union vs. Intersection
  • Other Vector Tools

MIDTERM – Tentative Date: THURSDAY, FEBRUARY 13TH

Test Format

5. Raster Data Analysis (Raster Cougar Demo)

  • Basic Raster Operations
  • Environment Settings Local Operations
  • Local, Focal, Zonal Operations
  • Global Operations

6. Surface Representation & Analysis (Interpolation Demo)

  • TINS vs. DEMS
  • Spatial Interpolation
  • Global vs. Local, Exact vs. Inexact
  • Interpolation Algorithms
  • Kriging and Semivariograms
  • Surfaces and Isolines
  • Density Surfaces

7. Point Pattern Analysis (Narrated PowerPoint Presentation)

  • Descriptive Measures
  • Nearest Neighbour
  • Spatial Autocorrelation

8. Network Analysis (Narrated PowerPoint Presentation)

  • Components of a Network
  • Creating and Managing Networks
  • Types of Network Analysis

9. Spatial Data Quality (Narrated PowerPoint Presentation)

  • What is it and Why do we Care?
  • Measures of Data Quality
  • Metadata

10. GIS Implementation & Management (Narrated PowerPoint Presentation)

  • Implementation vs. Management
  • User Centered Approach
  • Implementation Strategies
  • Project Management

FINAL EXAM – APRIL 17th 9 AM

Tentative Laboratory Schedule

Labs are scheduled Monday & Tuesday afternoons (1:40 – 4:30 PM) in BB 3-44, the Geomatics Lab.

Date Lab Topic
Jan 6/7   (no lab this week)
Jan 13/14 #1 Building Geospatial Databases: Introduction to Geodatabase Model; Import & Construct a Geodatabase
Jan 20/21 #2 Building Geospatial Databases: Working with Geodatabase Domains & Subtypes in ArcGIS; Quality Control
Jan 27/28 #3 Building Geospatial Databases: Create & Edit Features; Topological Editing
Feb 3/4 #4 Working with Attribute Data: Join, Query & Spatial Join
Feb 10/11   TIMED LAB MIDTERM EXAM
Feb 17/18   NO LAB (Louis Riel Day & Reading Week)
Feb 24/25 #5 Vector-based Spatial Analysis: Geoprocessing
Mar 2/3 #6 Raster-based Spatial Analysis: Spatial Analyst
Mar 9/10 #7 3D – Creating & Analyzing Digital Elevation Models: 3D Analyst
Mar 16/17 #8 Getting Started with Network Analysis: Network Analyst  CANCELLED*
Mar 23/24 #9 ArcGIS Pro Basics CANCELLED*
Mar 30/31   TIMED LAB FINAL EXAM  CANCELLED*

*  Modified Year-End Lab Assignment – WINTER 2020