Special Topics in Geo-Business Data AnalysisSpecial Topics in Geo-Business Data Analysis

Week 3 Covering Topic 6Week 3 Covering Topic 6

Spatial InterpolationSpatial Interpolation

Point Density AnalysisPoint Density Analysis

(Berry)

Point Density analysis identifies the number of customers with Point Density analysis identifies the number of customers with a specified distance of each grid locationa specified distance of each grid location

Roving Window (count)

Identifying Unusually High DensityIdentifying Unusually High Density

(Berry)

Pockets of unusually high customer density are identified as more Pockets of unusually high customer density are identified as more than one standard deviation above the meanthan one standard deviation above the mean

Identifying Customer TerritoriesIdentifying Customer Territories

(Berry)

Clustering on the latitude and longitude coordinates of point locations Clustering on the latitude and longitude coordinates of point locations identify customer territoriesidentify customer territories

Map View vs. Data ViewMap View vs. Data View

(Berry)

Mapped data are characterized by their geographic distribution Mapped data are characterized by their geographic distribution (maps on the left) and their numeric distribution (maps on the left) and their numeric distribution (descriptive statistics and histogram on the right)(descriptive statistics and histogram on the right)

Geographic DistributionGeographic Distribution Numeric DistributionNumeric Distribution

Estimating the Geographic DistributionEstimating the Geographic Distribution

(Berry)

The spatial distribution implied by a set of discrete sample points The spatial distribution implied by a set of discrete sample points can be estimated by can be estimated by iterative smoothingiterative smoothing of the point values of the point values

Spatial Autocorrelation Spatial Autocorrelation (Variogram)(Variogram)

(Berry)

A variogram plot depicts the relationship A variogram plot depicts the relationship between distance and measurement similarity (spatial autocorrelation)between distance and measurement similarity (spatial autocorrelation)

“…“…nearby things are more alike than distant things”nearby things are more alike than distant things”

Spatial Interpolation MechanicsSpatial Interpolation Mechanics

(Berry)

Spatial interpolation involves fitting a continuous surface to sample pointsSpatial interpolation involves fitting a continuous surface to sample points

Roving Window (average)

Inverse Distance Weighted TechniqueInverse Distance Weighted Technique

(Berry)

Inverse distance weighted interpolation weight-averages sample Inverse distance weighted interpolation weight-averages sample values within a roving windowvalues within a roving window

Example Calculations Example Calculations (IDW)(IDW)

(Berry)

Example Calculations for Inverse Distance Squared InterpolationExample Calculations for Inverse Distance Squared Interpolation

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TitleTitle

(Berry)

A wizard interface guides a user through the necessary steps A wizard interface guides a user through the necessary steps for interpolating sample datafor interpolating sample data

MapCalc Spatial Interpolation WizardMapCalc Spatial Interpolation Wizard

Comparing Geographic Distributions Comparing Geographic Distributions (IDW vs. Avg)(IDW vs. Avg)

(Berry)

Spatial comparison of the project area average and the IDW interpolated surfaceSpatial comparison of the project area average and the IDW interpolated surface

Comparison Statistics Comparison Statistics (IDW vs. Avg)(IDW vs. Avg)

(Berry)

Statistics summarizing the difference between the IDW surface and the AverageStatistics summarizing the difference between the IDW surface and the Average

……big difference— more than 75 % of the big difference— more than 75 % of the project area is more than +/- 10 units differentproject area is more than +/- 10 units different

Comparing Geographic Distributions Comparing Geographic Distributions (IDW vs Krig)(IDW vs Krig)

(Berry)

Spatial comparison of IDW and Krig interpolated surfacesSpatial comparison of IDW and Krig interpolated surfaces

Evaluating Interpolation PerformanceEvaluating Interpolation Performance

(Berry)

A residual analysis table identifies the relative performance A residual analysis table identifies the relative performance of average, IDW and Krig estimatesof average, IDW and Krig estimates

Mapping Spatial DependencyMapping Spatial Dependency

(Berry)

Spatial dependency in continuously mapped data involves summarizing the Spatial dependency in continuously mapped data involves summarizing the data values within a “roving window” that is moved throughout a mapdata values within a “roving window” that is moved throughout a map

……compares the difference in values between the adjacent neighbors compares the difference in values between the adjacent neighbors (doughnut hole) and distant neighbors (doughnut), assigns the spatial (doughnut hole) and distant neighbors (doughnut), assigns the spatial

dependency index to the center cell location then moves to next locationdependency index to the center cell location then moves to next location