Teaching

 

University of Iowa

 

GEOG 1050 - Foundations of GIS (Spring 2017)

The global geospatial industry brings in $270 billion in annual revenue, and companies in the sector pay more than $90 billion in wages each year.  Geospatial technologies are used to design sustainable cities, better understand environmental drivers of health, support business, and allow Google to get you to your destination. Geospatial technologies are and will play an ever-increasing role in our daily lives, ranging from mobile devices to data used by a wide range of government agencies and private businesses. This course introduces students to the technology and science behind digital mapping and geographic data analysis, and provides hands-on experience with modern geographic information system (GIS) software. Specific topics covered include geographic visualization, spatial problem solving, and geostreaming of real-time geographic data (e.g., geotagged tweets, images). We show how geographic patterns and processes can be better observed and understood through GIS, and how these systems allow us to explore large data, and areas, in ways not previously possible.

Course link: https://isis.uiowa.edu/isis2/courses/details.page?_ticket=3jriVfY6RZ4oRqxYjdjBfPatWyzz1sCZ&id=791214&ci=151694 

 

GEOG 3540 - Introduction to Geographic Visualization (Spring 2017)

From ancient maps of Babylon, to an interactive map of the planet Mars, people have used maps as analytic tools to navigate and explore geographic phenomena. Drawing from the fields of cartography, information visualization, and human-computer interaction, this course introduces the basic concepts and techniques that underlie cartographic representation and the broader field of geographic visualization. Selected topics include cartographic principles (e.g., color and symbolization; scale and generalization), animation, interactive cartography, user interface design, and geovisual analytics. Weekly lab assignments are designed to familiarize students with cartographic principles using powerful and easy-to-use visualization software and basic programming skills to implement effective and cross-platform (desktop, web and mobile) open-source visualizations using JavaScript, and visualization/mapping libraries such as D3 and Leaflet.

Course link: https://isis.uiowa.edu/isis2/courses/details.page?_ticket=pjtPNWq_tQ0iYaW663WDFbmTRnc9o6_1&id=792945&ci=158578

 

GEOG 4580 - Introduction to Geographic Databases (Fall 2017)

This introductory course focuses on the design and implementation of geographic information systems databases. Students will learn about the basic building blocks of spatial database design, spatial data models, structures, relationships, queries (SQL), and indexing. Several discussions will introduce students to concepts of Big Data, and NoSQL databases. Lab assignments introduce students to techniques for collecting, maintaining and querying geographic data from various sources such as utility networks, cadasters, social media, public health, environmental sciences, and businesses. Students will gain hands-on programming experience in writing spatial SQL queries, and Python Scripting to support spatial querying and automating repetitive geographic data handling tasks. The labs utilize both open-source (PostgreSQL/PostGIS) and commercial (ESRI) solutions for spatial database management. Students will also gain experience in hosting databases in the cloud using Amazon Web Services (AWS). 

Course link: https://isis.uiowa.edu/isis2/courses/details.page?_ticket=Bop8V1kH-jcvSotjmDm4m0JwrGDmSZOY&id=779940&ci=153900

 

GEOG 6500 - Graduate Seminar in Spatial Analysis and Modeling (Fall 2018)

This seminar is designed to improve students’ theoretical foundation in GIScience and research skills in GIScience related projects. While the particular focus in on the theory and methodologies for analyzing geographic phenomena represented by spatial, temporal, and multivariate data; practical applications of GIScience in geography, such as social sciences, public health, digital humanities, environmental and sustainability sciences are also covered.  

The discussions will cover a broad range of topics including but not limited to:

  1. Spatial Statistical Approaches (e.g., local spatial statistics, geographically weighted regression, point pattern analysis, and space-time scan statics)
  2. Exploratory Approaches: Spatial Data Mining (i.e., spatial association rule mining, clustering, and classification), and Geovisual Analytics
  3. Machine Learning (e.g., supervised classification such as decision trees and support vector machines)
  4. Themes in GIScience (e.g., time geography, spatial interactions, complex networks, and agent-based modeling), and related work in various application domains

This seminar is methodology oriented. Students are encouraged to choose datasets that are relevant for her/his research interest. The objectives of this seminar are to (1) help students learn a variety of analysis approaches and apply them in topical areas; and (2) facilitate students in making progress towards their theses and dissertations. To examine each topic, the seminar will use a mix of approaches, including lectures, readings, discussions, project assignment, writing and peer-review.

Learning Outcomes

  • Students will acquire an overall understanding of the GIScience body of knowledge, and acquaint themselves with the latest research topics and innovations within the GIScience community.
  • Students will be able to understand the challenges in GIScience, and link their thesis or dissertation research to address fundamental issues in GIScience.
  • Students will work on their research projects throughout the semester, and present them in the seminar.
  • Throughout the semester, students will get familiar with peer-review process and receive feedback both from each other and the instructor.
  • Student will be able to apply learned statistical, computational and visual methods to analyze spatial data in his/her chosen application domain. 
  • Each student will obtain training in basic research skills, such as writing, data collection, preprocessing, analysis and visualization, interpretation, and result communication;
  • Students will obtain foundation knowledge necessary for further learning and research related to GIScience.

 

University of South Carolina

[USC Geography Courses Link]

GEOG 363 - Introduction to Geographic Information Systems (GIS)

Instructor (Summer 2012, Spring 2013)

The class introduces student principles and methods of Geographic Information Systems with emphasis on spatial data collection, storage, querying, manipulation, analysis, and applications. Practical experience with GIS is also provided through hands-on computer exercises

[Syllabus]

 

GEOG 563 - Advanced Geographic Information Systems (GIS)

Lab Instructor (Spring 2012, Fall 2012)

Designed and taught labs that introduce graduate students with GIS applications from a variety of perspectives such as environmental protection, crime analysis, real estate, spatial and temporal analysis of social networks, and etc.

[Syllabus]