Course descriptions and websites

GEOG 3561/5561. Principles of Geographic Information Science: Introduction to the study of geographic information systems (GIS) for geography and non-geography students. GIS powers popular applications ranging from online mapping to video games. Topics considered in the course include basics of maps and map reading, computer software and data models, where to find geographic data, methods for spatial analysis, visualization techniques, and the societal ramifications of GIS. The course combines lectures and hands-on experience with GIS software. Class time: 65% lecture, 35% lab. Credits: 4.

GEOG 5563. Advanced Geographic Information Science: This class starts where GEOG 5561 left off. It continues the exploration of key topics in GISc, including map projection, data models, error/uncertainty, change analysis, GIS and society, advanced raster processing, advanced vector methods, and spatial analysis. Class time: 30% Lecture, 20% Discussion, 50% Laboratory. Credits: 3. [Example syllabus of the course as offered by Dr. Manson]

GEOG 5564. Urban geographic Information Science: Core concepts in urban geographic information science including sources for urban geographical and attribute data (including census data), urban data structures, urban spatial analyses (including location-allocation models), geodemographic analysis, network analysis, and the display of urban data. Class time: 30% Lecture, 20% Discussion, 50% Laboratory. Credits: 3.

GEOG 5565. Geographical Analysis of Human-Environment Systems: This course expands on aspects of GISc and statistics covered by previous courses. It is designed to introduce ways in which GIS can be used to explore human-environment systems by gaining hands-on experience with advanced methods in spatial analysis and modeling. Class time: 30% Lecture, 20% Discussion, 50% Laboratory. Credits: 3. [Example syllabus of the course as offered by Dr. Manson]

GEOG 8292. Seminar in Spatial Analysis & Modeling: Explores different ways of analyzing and modeling human-environment interaction from a spatial analysis and modeling perspective. Class time: 100% seminar. Credits: 3. [Example syllabus of the course as offered by Dr. Manson]

GIS 5555. Basic Spatial Analysis: Analyses of data with spatial (locational) information. Exploratory data analysis. Descriptive statistics of point data. Descriptive statistics for line data. Descriptive statistics for polygon data. Spatial autocorrelation. Inferential statistical analysis of point data/polygons. Descriptive analysis of patches/landscapes. Spatial pattern recognition using empirical orthogonal functions and cluster analysis. Regression methods for spatially autocorrelated variables. Class time: 30% Lecture, 20% Discussion, 50% Laboratory. Credits: 3. [Example syllabus of the course as offered by Dr. Manson]