| ||Searching Current Courses For Fall 2017|
||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.
||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.
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
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||Front Range Community College