Course Description
Geographic analytical methods and implementation. Theory and concepts of spatial analysis. Description, reduction, and comparison of point, line, area, and volumetric geographic data sets. Implementation and limitation of geographic information systems.
Additional Requirements for Graduate Students:
Additional readings, assignments, and questions on tests; research paper.
Athena Title
Adv Geospatial Spatial Stat
Undergraduate Prerequisite
[(STAT 2000 or STAT 2000E) and (GEOG 4370/6370-4370L/6370L or GEOG 4370E/6370E)] or permission of department
Graduate Prerequisite
[(STAT 2000 or STAT 2000E) and (GEOG 4370/6370-4370L/6370L or GEOG 4370E/6370E)] or permission of department
Semester Course Offered
Offered fallOffered spring
Grading System
A - F (Traditional)
Course Objectives
The objective is to provide the student with the ability to analyze GIS data of all sorts, and to understand the uses and limitations of GIS data. Emphasis is placed on both theoretical aspects of GIS data analysis and geo-computation, as well as hands-on familiarity with basic GIS software applications. This course meets the following General Education Abilities by accomplishing the specific learning objectives listed below: Communicate effectively through writing. This is met by a series of writing assignments associated with supplemental reading and data analysis. Communicate effectively through speech. This is met by oral presentations, discussion leading, and classroom participation. Computer Literacy is addressed through course administration, student-faculty electronic interaction, data analysis activities and assignments, and exposure to GIS technologies. Critical Thinking is central to the learning objectives of this class, and are developed through homework assignments, lecture, classroom discussion, and inquiry- based learning efforts.
Topical Outline
Quick Overview: Classical Statistics-hypothesis tester Intro to spatial data; what’s “special” about it? Exploring spatial data visually Point pattern descriptors Spatial autocorrelation; Point pattern analysis Spatial regression Local analysis (GWR) Geostatistical models - kriging Polygon pattern analysis (brief overview)
Syllabus