Advanced GIS (CP 6521)

Instructor: Dr. Clio Andris
See Canvas for official syllabus.


This class is a natural next step for those who have had a GIS class and are interested in learning more about Geographic Information Systems and Geographic Information Science. This class will go over advanced topics such as point pattern analysis, compactness and characterizing geometries, distance decay functions, location/allocation functions, routing, basic non-planar network metrics, geographically-weighted parameterization, and geovisualization. It will have a project component.

Class meets Tuesdays and Thursdays 12:30 pm – 1:45 pm. It will be taught remotely through webex. There are no expectations for meeting in person. There will be lecture days and lab days as well as guest lectures and practical assignments. Lectures will be taught synchronously. Attendance on lab days (dates to be announced with the syllabus) is encouraged but lab days will be recorded and the recordings can be watched later.

Introduction to GIS, or a prior GIS class. Students will have a skills assessment on the first week to ensure that they have the prerequisite skills for the class.

Students are expected to attend all lectures, read readings, and complete all assignments. There will be no official final exam. Late submissions will be graded down by 10% for each day of delay past the due time starting at 12:30 pm. All assignments should be handed in on Canvas.

ContentNumber of AssignmentsTotal Points
GIS labs5 45
Practical assignments4* (R review counts for 2 pts)15
Contribution to discussion and professionalism10

 Course Objectives

  1. Learn about polygon encapsulation and description methods
  2. Create GIS analyses that measure environmental exposure and vulnerability for different demographic groups
  3. Download and use GIS data sources from the web
  4. Compare different methods of computing distance between points
  5. Quantitatively demonstrate issues with edge effects
  6. Use an API through the R statistical computing environment
  7. Find locations for facilities and evaluate disparities in emergency response times
  8. Quantify point pattern distributions and distance decay
  9. Demonstrate use of geographically-weighted regression models
  10. Understand principles of geovisualization and interaction with data

Tentative Schedule (subject to change)

Check Canvas for Official Deadlines

Th 1/14Introduction to Course, GIS and R DemoNone
Tu 1/19On your own: GIS and R Review (help available)None
Lecture 1: Capturing Polygonal Geometries
Breakout activity: finding irregular polygons
GIS Review due (1/21)
PolygonsTu 1/26Lab 1: Compactness | Gerrymandering PPI: 343-353
R Review due (1/26)
PolygonsTh 1/28Lecture 2: Social Vulnerability and Social Capital Indexes
Breakout activity: exploring indices
PolygonsTu 2/2Lab 2: Environmental Justice and Social Vulnerability: Does Unit MatterNone/TBD Lab 1 due (2/2)
PolygonsTh 2/4Guest Speaker: Dr. Jayajit Chakraborty (University of Texas-El Paso)None/TBD
NetworksTu 2/9Lecture 3: Networks 1: Road Networks, Location/AllocationNetworks Lab 2 due (2/9)
NetworksTh 2/11Guest Speaker-PractitionerOpt[Berke]
NetworksTu 2/16Lab 3.1: Network AnalysisNone/TBDPolygon quiz (2/16)
NetworksTh 2/18Lecture 4: Networks 2: More on Travel Time, Travel Cost, Data Sources
Breakout activity: your route (hypotheses)
NetworksTu 2/23Lab 3.2: Network Analysis: Response AnalysisBoscoe
Th 2/25Guest Speaker: Sarah Williams (Massachusetts Institute of Technology)None/TBD
NetworksTu 3/2Practical 1: APIs for Travel Time, Travel Cost, Euclidean Distance in R.None/TBDLab 3 due (3/2)
Th 3/4Practical 2: Fieldwork on Data/LandscapePaper 4Practical 1 due (3/4)
PointsTu 3/9Lecture 5: Point Patterns 1: Capturing Distributions
Point Patterns
PointsTh 3/11Lecture 6: Point Patterns 2: Point Patterns: Capturing Distributions and Geographically-Weighted Regression
Breakout activity: Patterns in interactive visualizations
Th 3/18Project Introduction
Data Search and Project Workshop
Andris (Sports)
Networks quiz (3/18)
PointsTu 3/23Lab 4: Part 1 University Sports Teams: Calculating Distributions None/TBDPractical 2 due (3/23)
PointsTh 3/25Lab 4: Part 2 Restaurant Analysis: Predictive FactorsNone/TBD
GeovisTu 3/30Lecture 7: Principles of Good Maps and Elements of DesignNone/TBD
GeovisTh 4/1Practical 3: Pair Activity: Practical Assessment: COVID 19 Visualization Tools (Same day: in-class assignment). Cartography TopicsPractical 3 due (4/1)
GeovisTu 4/6Lecture 8: Symbology and Gestalt PsychologyNone/TBDPoints quiz (4/6)
GeovisTh 4/8Lab 5: Small Multiples in R (tiny lab)–map your project data. None/TBDLab 4 due (4/8)
GeovisTu 4/13Lecture 9: Geovisualization Interaction, Tasks and HCI PrinciplesNone/TBD
ProjectTh 4/15Quiz. Project Help (at school or virtual) None/TBDLab 5 due GeoVis quiz (4/15).
ProjectTu 4/20Project Help (at school or virtual) None/TBD
ProjectTh 4/22Project Presentations None/TBD
ProjectTu 4/27Project Presentations None/TBD
Date on Canvas