GEOG5533

What happens north, south, east, or west is very likely to be dependent on what is happening here. The uniqueness of geospatial information coming from both physical and human geography requires specialized theories and methods to tackle. Spatial analysis provides ways to approach complex spatial effects and to support geographic knowledge discovery. In this course, we will dive into several major topics in the field of quantitative spatial analysis, ranging from spatial statistics, point patterns, clustering, and spatial interpolation, to spatial regression analysis. Through in-person modules (lectures, reading activities, and labs) and a case study project, students will develop an in-depth understanding of spatial principles such as autocorrelation, scale, distance, and spatial associations. This is an advanced course for spatial analysis and geospatial data science that makes use of specialized linear algebra, statistical modeling, and computational skills.

Students need a basic background in statistics to succeed in the course. If you have this background but have not taken one of the listed prerequisite courses, please contact the instructor for a permission number.

OPT - Student Option

EPSY 3264 or ESPM 3012 or Geog 3531 or Pol 3085 or Soc 3811 or Stat 1001 or Stat 3011 or Stat 3022 (or instr consent)

No

Every Spring