Office hours: 1:00 to 3:00 PM on Mondays and Wednesdays, and by appointment.

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1 USP 531 Geographic Data Analysis and Display Winter credit hours Mondays, 4:00 6:30 PM Cramer Hall, room 250 Course description The goal of the course is to introduce students to principles and methods of analysis and visualization of geographic information. The course explores sources and types of geographic data used in urban and regional studies and planning with an emphasis on Census data, and discusses data quality and compatibility. Students learn about Geographic Information Systems (GIS) as a primary tool of spatial (geographic) analysis. Principles of graphic design and spatial data visualization are discussed, as well as GIS uses and limitations. Attention is given to practical applications of GIS in urban and regional planning and to developing essential skills in desktop mapping and spreadsheet software. The course consists of lectures and exercises to be completed through an independent work in the computer laboratory. The latter includes completing exercises from Getting to Know ArcGIS Desktop manual and three assignments developed to help students build skills in retrieving, manipulation, analysis and effective presentation of geographic information. In addition to the lectures and labs, the course utilizes WebCT, an online educational tool, to support the instruction (URL Instructor: Irina V. Sharkova, Ph.D. Population Research Center & School of Urban Studies and Planning Urban Center, Rm. 570M sharkovai@pdx.edu Office hours: 1:00 to 3:00 PM on Mondays and Wednesdays, and by appointment. Required reading Course pack Geographic Data Analysis and Display at PSU Bookstore Chrisman, Nicholas. Exploring Geographic Information Systems, 2 nd Ed., John Wiley & Sons, Inc.: New York NY Ormsby, Tim, et. al. Getting to Know ArcGIS Desktop, ESRI: Redlands CA Online and other digital sources as assigned Evaluation Method Final grades will be established on the basis of: Assignments (3) 60% (20% each) Exercises from Getting to Know ArcGIS Desktop 8% Presentation (1) 7% Participation (daily) 7% Leading a discussion 3% Final exam 15% Special needs

2 If you have a disability and are in need of academic accommodations, please notify the instructor immediately to arrange needed supports. Topical Outline and Weekly Agenda Week 1. Course introduction. Geographic data and its users. 1. Course introduction. WebCT introduction. 2. Data and information. Types of data. 3. Primary and secondary data. Geographic (spatial) and categorical data. 4. Sources of geographic and categorical data. Data on the Web. 5. Using geographic data, maps and GIS in planning and other disciplines. Reading materials for Week 2 Jacek Malczewski (1999). GIS and Multicriteria Decision Analysis. Ch. 1, pp Dowell Myers (1992). Analysis with Local Census Data. Chs 3, 4: pp , & pp Edward Tafte (1997). Visual and Statistical Thinking (Part 1). Board on Earth Sciences and Resources, NAS (2002). Community and Quality of Life: Data Needs for Informed Decision Making. Appendix A, pp Week 2. US decennial Census and other governmental data sources. Analysis with local Census data. 1. US Decennial Census: concepts & definitions and 2000 Census data. Data comparability. 3. American Community Survey and other data sources. 4. Geographic hierarchy of Census data. 5. Data available for local area analysis. 6. Summary files. PUMAs and PUMSs. Population estimates and projections. Reading materials for Week 4 Grieco, E. (2002) An Evaluation of Bridging Methods Using Race Data from Census Population Research and Policy Review 21: Edward R. Tafte (1997). Visual and Statistical Thinking: Display of Evidence for Making Decisions (Part 2). Graphics Press: Cheshire, CT, pp Dowell Myers (1992). Analysis with Local Census Data. Ch. 5, Strategies of Presentation, pp Week 3. Martin Luther King, Jr. Day University closed Week 4. Derived variables and descriptive statistics. Principles of data visualization. Designing tables and charts in Excel. 1. Derived variables and descriptive statistics. 2. Comparing areas: index of dissimilarity; normalization of numerical data. 3. General principles of presentation. Visual variables. 4. Presenting tabular data. 2

3 5. Creating effective charts and graphs. 6. Formulas and charts in Excel. Reading materials for Week 5 Chrisman, N. Exploring Geographic Information Systems, Introduction; Chapters 1 and 2. Kenneth E. Foote and Margaret Lynch. Geographic Information Systems as an Integrating Technology: Context, Concepts, and Definitions. The Geographer's Craft Project, Department of Geography, The University of Colorado at Boulder. Online, Swasti Shah. Neighborhood GIS: A Tool for Community Participation in Planning. Online, Barbara M. Parmenter. Visualizing Urban History Using GIS. Online, Week 5. GIS: concepts, principles, components. 1. Geographic (spatial) phenomena; their types and characteristics. 2. GIS database concepts. Vector and raster GIS data models. 3. Vectors data models: topology. 4. Geographic data development: digitizing, remote sensing. 5. TIGER/Line files: a major source of geographic data. Reading materials for Week 6 Chrisman, N. Exploring Geographic Information Systems, Ch. 3. Mark Monmonier. How to Lie with Maps. Chs. 6 and 10; Kent, Robert, and Richard Klosterman. GIS and Mapping: Pitfalls for Planners. JAPA (2000), Vol. 66, No. 2, pp Week 6. Geographic data visualization. Thematic Mapping. Classification Types 1. Map as a model of geographic data. Map goals, users and types. 2. Thematic maps: portraying distribution, count, magnitude. 3. Joining tabular and geographic data. 4. Methods of data classification for choropleth maps. 5. Other methods of geographic data visualization. Reading materials for Week 7 Chrisman, N. Exploring Geographic Information Systems, Ch. 4. Angela Goodwin Cort Daniel. Maximizing Use of Census 2000 Data in Local Government. Online, L. Denise Pinnel, Matthew Dockrey, A.J. Bernheim Brush, and Alan Borning. Design of Visualizations for Urban Modeling. Online, Week 7. Map elements. Controls on map design. 1. Map elements, informative titles, creative labeling. 3

4 2. Map design process and controls. 3. Scale and projections. 4. Generalization. 5. Dasymetric mapping and its uses. Reading materials for Week 8 Chrisman, N. Exploring Geographic Information Systems, Chs. 5 & 6. Steven R Holloway, James Schumacher, and Roland L Redmond. People & Place: Dasymetric Mapping Using Arc/Info. In press: Cartographic Design Using ArcView and ARC/INFO. High Mountain Press, NM, Online, Week 8. Spatial Analysis in GIS (Part1) 1. Locating and identifying spatial objects. 2. Defining spatial characteristics. 3. Simple queries; reclassification. 4. Measuring length, perimeter, area, distance. 5. Spatial overlay and buffers. Reading materials for Week 9 Chrisman, N. Exploring Geographic Information Systems, Chs. 7, 8, and 9. Drummond, William. Address Matching: GIS Technology for Mapping Human Activity Patterns. JAPA (1995), Vol. 61, No. 2, pp Marc Schlossberg. Visualizing Accessibility with GIS. Online, Emily Talen. GIS Helps Evaluate Living Patterns. Online, Week 9. Spatial Analysis in GIS (Part 2) 1. Statistical surfaces. 2. Analysis with raster GIS: neighborhood operations. 3. Map algebra. 4. Geocoding. 5. Political redistricting. Reading materials for Week 10 Chrisman, N. Exploring Geographic Information Systems, Chs. 10 and 11. Daniel Howard. Geographic Information Technologies and Community Planning: Spatial Empowerment and Public Participation. Online, Peter A. Kwaku Kyem. Examining the Community Empowerment Process in Public Participation GIS Applications. Online, Week 10. Social and cultural context of GIS. Public Participation GIS. 4

5 1. Using GIS: geographic data quality. 2. Error, accuracy and precision. 3. GIS and community. Public Participation GIS. 4. GIS and society: legal and other issues. Week 11. Final exam. 5

6 Week/ Date Week 1 1/6 Week 2 1/13 Week 3 1/20 Week 4 1/27 Week 5 2/3 Week 6 2/10 Week 7 2/17 Week 8 2/24 Week 9 3/3 Week 10 3/10 Week 11 3/17 TOPICS (see corresponding REQUIRED READING in WebCT) EXERCISES & Due dates ASSIGNMENTS Course introduction. Geographic and categorical data, its types and uses. Sources of geographic and categorical data. US decennial Census and 2000 Census data. Summary files. Analysis with local Census data. Geographic hierarchy of Census data. Martin Luther King, Jr. Day University closed Derived variables; descriptive statistics; index of dissimilarity; normalizing numerical data. Principles of data visualization. Designing tables and charts. GIS: concepts, principles, components. GIS data models. Data development. GIS data sources. TIGER. Geographic data visualization. Thematic mapping. Linking tabular and geographic data. Classification methods for mapping. Controls on map design. Scale and projections. Dasymetric mapping. Spatial analysis in GIS (Part1): simple queries; reclassification; overlays; distance & buffers. Spatial analysis in GIS (Part 2): surfaces, advanced analysis, geocoding. Geographic data quality, accuracy and precision. Social and cultural context of GIS. Public participation GIS. See Week 1 in WebCT (Weekly course materials) by Monday, 1/13, 4:00 PM Submit your research proposal via WebCT (see Week 2) by Friday, 1/17, 4:00 PM GTKAGD: Ch. 1, 2, 3, 4 by Wednesday, 2/5, 4 PM GTKAGD: Ch. 5, 6, 7, 9 by Wednesday, 2/12, 4 PM GTKAGD: Ch. 13, 18, 19 by Wednesday, 2/19, 4 PM GTKAGD: Ch. 8, 10, 11, 12 by Wednesday, 2/26, 4 PM GTKAGD: Ch. 14, 15, 16, 17 by Wednesday, 3/5, 4 PM Take-home final exam is given in class Final exam turned in; Student presentations (5) 15:30-17:20, room CH 250, Monday, March 17 th n/a Assignment 1 due Friday, January 31, by 4:00 PM in URBN 570M Assignment 2 due Friday, February 21, by 4:00 PM in URBN 570M Assignment 3 due Wednesday, March 12, by 4:00 PM in URBN 570M