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.
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
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:
- Gain a mastery of fundamental GIS skills: data organization, management, geoprocessing, queries, and layout design. Identify, compare, and contrast the basic properties of raster and vector spatial data.
- Understand and implement the basic components of spatial analysis: density, patterns, spatial changes, mean centers, interpolation, and categorization.
- Perform basic vector routines, including data creation, collection, coordination, and projection.
- Utilize ESRI tools for raster analysis.
- Collect vector and raster data using a variety of tools and georeferenced the data to the Earth.
- Identify and utilize online vector and raster data.
V. Topical Outline (Course Content)
VI. Delivery Methodologies