Performing Spatial Interpolation Using ArcGIS 10
- Format: Web Course
- Duration: 1 module (3 hours)
- Price: $32 USD
- ArcGIS Version: 10.0
- Authored by Esri
For some applications, it is impossible to collect data for every point in an area of interest. Using ArcGIS Geostatistical Analyst tools and sample data, however, you can predict, or interpolate, values at every location across a surface. This course focuses on the kriging geostatistical interpolation method and teaches how to create a kriging model that is optimized for your sample data. Many factors impact the reliability of your interpolation results. You will learn how to use the kriging model to produce a statistically valid prediction surface, generate confidence in your analysis results, and improve decision making.
Who Should Attend
GIS analysts and specialists, students, and researchers and professionals working in industries such as public health, meteorology, precision agriculture, environmental management, mining, and energy production.
Learn How To
- Understand the data assumptions inherent to the kriging interpolation model and find out if your sample data matches those assumptions.
- Define an optimal semivariogram model for your data in preparation for kriging.
- Apply techniques to modify your sample dataset so that it meets kriging model criteria.
- Cross-validate a prediction surface to see how predicted values compare with known values for the location.
- Analyze cross-validation statistics to determine which kriging model is most suitable for your data and assess the accuracy of your prediction surface.
- Export a prediction surface generated by a kriging model to a raster dataset so it can be used for further visualization and analysis.
New Catalog Search
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