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 Searching Current Courses For Fall 2017

  Course: GIS 211
  Title:Spatial Modeling & Analysis
  Long Title:Spatial Data Modeling and Analysis for GIS
  Course Description:Examine techniques for modeling and analyzing spatial data in a GIS. Topics include defining object models and geodatabases as they are used to access geographic data and build data models, creating new information from existing data through data classification, geoprocessing, presentation, and display and using raster analysis to display and analyze spatial data.
  Min Credit:4
  Max Credit:

  Origin Notes: FRCC
  Notes:vised-ttl,dscrptn,cmptncs,outln 5/10/12 LK

 1. Identify the characteristics and the importance of statistical relationships in spatial data.
 2. Identify techniques for exploratory spatial data analysis.
 3. Create new information from existing data through geoprocessing and spatial data model operations.
 4. Relate GIS centric models to linked or model centric analysis.
 5. Analyze spatial analysis and modeling capabilities.
 6. Perform vector data processing
 7. Execute raster analysis.
 8. Perform surface visualization and analysis.
 9. Demonstrate the use of networks in data modeling and analysis.
 10. Perform point density analysis.
 11. Explore spatial autocorrelation.
 12. Distinguish geostatistics including spatial sampling, and  semi-variogram modeling.
 13. Discuss object models and topology using geodatabases.
 14. Model physical processes in terms of spatial relationships.
 15. Identify criteria for selection of static and dynamic models.
 16. Distinguish data models from  process models.
 17. Evaluate application criteria for selection of models.

 I. Introduction
 II. Geospatial modeling
 III. Geoprocessing & spatial statistics
 IV. Spatial analysis
 V. Network analysis
 VI. Link Models
 VII. Urban  models
 VIII. Transportation models
 IX. Business location models
 X. Epidemiology models
 XI. Land use models
 XII. Hydrology models

 Course Offered At:

  Front Range Community College FRCC
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Release: 8.5.3