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Humboldt State University

Guide to Student Success (from Jeff Dunk)

The content of the material below have been provided by a large number of individuals who are listed at the bottom of this web page.

Below are links to the materials for classes I'm teaching at HSU:

GSP 270: Introduction to Geographic Information Science (GIS)

This is a second class in Geospatial Science and requires the completion of GSP 101 or the equivalent. Students should already have experience with: spatial reference systems (datums and projections), the nature of spatial data (points, polylines, polygons, and rasters), and some experience with using ArcGIS for creating simple maps.

This class will provide students with the opportunity to learn how to: acquire spatial data from a wide variety of sources, prepare data for use in a GIS, digitize features to create new spatial data, perform basic spatial analysis, and create reports and maps that include maps and analysis results. We'll we'll also look at the standard methods for using spatial data in ArcGIS and tricks to get work done more quickly and to avoid common pit-falls.

GSP 318: Geospatial Programming

Programming is becoming critical to many spatial science tasks. This class will teach you the basics of the Python programming language, how to create powerful tools for ArcGIS, and how to use Open Source libraries as well.

GSP 470: Advanced Geographic Information Science (GIS)

Students taking this class will learn to use the advanced features of ArcGIS and OpenSource spatial software. We'll look at how to manage large data sets, automate analysis, and provide results through websites and web services. Students will learn to use ArcGIS and R together to complete more complex processes. While not required, programming experience will make this class easier for most students.

In this class, we will also create more complex projects that tackle some of the most challenging spatial analysis and data problems.

GSP 570: Geospatial Modeling

This class will teach students to use formal spatial modeling approaches to model current and potential future spatial phenomenon.

This is a graduate courses but advanced undergraduates are also welcome to take the course if they have completed a course in GIS at the intermediate level. Programming is not required but will help and broaden the approaches available the students.

R Web Site:Learn to use R for Spatial Statistics

This web site contains material that I access from other classes.

Faculty Short-Course

Firefox for Science A, Room 364

Note: I have removed links to the other class materials from my previous institutions as the content has been moved and updated in the courses above. Please contact me if you have questions.


The material contained herein come from a large number of individuals that have influenced me and contributed ideas to its creation. They include:

Colorado State University, Oregon State University, and Humboldt State University have provided resources for the development of these materials. There are also too many students to list who have patiently given feedback on the creation of the materials.