Class Summary |
AverageNearestNeighbor |
Calculates a nearest neighbor index based on the average distance from each feature to its nearest neighboring feature. |
CalculateAreas |
Calculates area values for each feature in a polygon feature class. |
CalculateDistanceBand |
Returns the minimum, the maximum, and the average distance to the specified Nth nearest neighbor (N is an input parameter) for a set of features. |
CentralFeature |
Identifies the most centrally located feature in a point, line, or polygon feature class. |
ClustersOutliers |
Given a set of weighted features, identifies statistically significant hot spots, cold spots, and spatial outliers using the Anselin Local Moran's I statistic. |
ClustersOutliersRendered |
Given a set of weighted features, identifies hot spots, cold spots, and spatial outliers using the Anselin Local Moran's I statistic. |
CollectEvents |
Converts event data, such as crime or disease incidents, to weighted point data. |
CollectEventsRendered |
Converts event data to weighted point data and then applies a graduated circle rendering to the resultant count field. |
ConvertSpatialWeightsMatrixtoTable |
Converts a binary spatial weights matrix file (.swm) to a table. |
CountRenderer |
Applies graduated circle rendering to a numeric field in a feature class. |
DirectionalDistribution |
Creates standard deviational ellipses to summarize the spatial characteristics of geographic features: central tendency, dispersion, and directional trends. |
DirectionalMean |
Identifies the mean direction, length, and geographic center for a set of lines. |
ExportXYv |
Exports feature class coordinates and attribute values to a space, comma, or semi-colon delimited ASCII text file. |
GenerateNetworkSpatialWeights |
Constructs a spatial weights matrix file (.swm) using a Network dataset, defining feature spatial relationships in terms of the underlying network structure. |
GenerateSpatialWeightsMatrix |
Constructs a spatial weights matrix (.swm) file to represent the spatial relationships among features in a dataset. |
GeographicallyWeightedRegression |
Performs Geographically Weighted Regression (GWR), a local form of linear regression used to model spatially varying relationships. |
HighLowClustering |
Measures the degree of clustering for either high values or low values using the Getis-Ord General G statistic. |
HotSpots |
The Hot Spot Analysis (Getis-Ord Gi*) tool is contained in the Spatial Statistics Tools tool box. |
HotSpotsRendered |
Calculates the Getis-Ord Gi* statistic for hot spot analysis and then applies a cold-to-hot type of rendering to the output z-scores. |
MeanCenter |
Identifies the geographic center (or the center of concentration) for a set of features. |
MedianCenter |
Identifies the location that minimizes overall Euclidean distance to the features in a dataset. |
MultiDistanceSpatialClustering |
Determines whether features, or the values associated with features, exhibit statistically significant clustering or dispersion over a range of distances. |
OrdinaryLeastSquares |
Performs global Ordinary Least Squares (OLS) linear regression to generate predictions or to model a dependent variable in terms of its relationships to a set of explanatory variables. |
SpatialAutocorrelation |
Measures spatial autocorrelation based on feature locations and attribute values using the Global Moran's I statistic. |
StandardDistance |
Measures the degree to which features are concentrated or dispersed around the geometric mean center. |
ZRenderer |
Applies a cold (blue) to hot (red) color rendering scheme for a field of z-scores. |