AGRI 226 Spatial Analysis with GIS*

This course provides an introduction to spatial analysis. The course will briefly review the principles of statistics and relate them to methods used in analysis of geographically referenced data. The course will introduce sampling strategies for data used in Geographic Information Systems (GIS) using raster and vector data structures. The fundamentals of conventional estimation techniques will be compared with geostatistical techniques. The course will present single and multi-layer statistical operations including classification, recode, interpolation, coordination, and modeling analysis using vectors, raster and TINs. Applications and problems in spatial correlation will be discussed including interpretation of results of spatial analysis and error propagation. ArcView GIS, Spatial Analysis, Network and 3D extension software will be used to demonstrate and practice basic principles of spatial analysis.

Credits

3 Credits

Prerequisite

AGRI 126 and AGRI 126L

Corequisite

AGRI 226L

AGRI 226Spatial Analysis with GIS*

Please note: This is not a course syllabus. A course syllabus is unique to a particular section of a course by instructor. This curriculum guide provides general information about a course.

I. General Information

Department

II. Course Specification

Credit Hours Narrative

3 Credits

Prerequisite Narrative

AGRI 126 and AGRI 126L

Corequisite Narrative

AGRI 226L

III. Catalog Course Description

This course provides an introduction to spatial analysis. The course will briefly review the principles of statistics and relate them to methods used in analysis of geographically referenced data. The course will introduce sampling strategies for data used in Geographic Information Systems (GIS) using raster and vector data structures. The fundamentals of conventional estimation techniques will be compared with geostatistical techniques. The course will present single and multi-layer statistical operations including classification, recode, interpolation, coordination, and modeling analysis using vectors, raster and TINs. Applications and problems in spatial correlation will be discussed including interpretation of results of spatial analysis and error propagation. ArcView GIS, Spatial Analysis, Network and 3D extension software will be used to demonstrate and practice basic principles of spatial analysis.

IV. Student Learning Outcomes

Upon completion of this course, a student will be able to:

V. Topical Outline (Course Content)

VI. Delivery Methodologies