Types of feature analysis

You can perform many different types of feature analyses with the spatial analysis service.

The operations are categorized into the following:

  1. Find data
  2. Combine data
  3. Summarize data
  4. Analyze patterns
  5. Calcuate geometries

Click on the links below to learn how to execute each operation programmatically with ArcGIS APIs and the ArcGIS REST API.

Find data

Find data operations allow you to find feature data with a SQL or spatial query or to export feature data to create new feature data.

OperationDescription
Input data
Output data
Example
Find existing locationsSelects features that satisfy one or more SQL and/or spatial expressions and returns new feature data.Point, polyline, or polygon feature dataPoint, polyline, or polygon feature data find existing locations
Derive new locationsSelects and can modify features to satisfy one or more SQL and/or spatial expressions and returns new feature data.Point, polyline, or polygon feature dataPoint, polyline, or polygon feature data derrive new locations
Extract featuresSelects and exports features that satisfy a SQL and/or spatial expression and creates new feature data stored as a file in a new item. Feature data can be converted to CSV, KML, file geodatabase, or shapefile format.Point, polyline, or polygon feature dataPoint, line, or polygon feature data in a file in a item extract data

Combine data

Combine data operations allow you to merge, overlay, and join multiple sources of feature data to create new feature data.

OperationDescription
Input data
Output data
Example
Merge layersCombines two feature datasets and returns a new a feature dataset. The input feature data must contain the same type of geometry (point, polyline, or polygon). Attributes can be added, removed, renamed, or matched.Point, polyline, or polygon feature dataPoint, polyline, or polygon feature data merge layers
Overlay layersCombines two or more feature datasets using intersect, union, or erase and returns a new feature dataset. All of the feature attributes are persisted in the output feature data.Point, polyline, or polygon feature dataPoint, polyline, or polygon feature data overlay layers
Join featuresCombines the attributes from one feature dataset to another based on spatial and/or attribute relationships and returns new feature data. The type of attribute and spatial relationship join operations can be specified. Feature geometry and attribute summary statistics can also be generated.Point, polyline, polygon, or table feature dataPoint, polyline, polygon, or table feature data join features
Dissolve boundariesCombines polygons from feature datasets that overlap or share a common boundary and returns new feature data. Feature geometry and attribute summary statistics can also be generated.Polygon feature dataPolygon feature data dissolve boundaries

Summarize data

Summarize data operations allow you to calculate spatial and attribute statistics on feature data to create new feature data.

OperationDescription
Input data
Output data
Example
Aggregate pointsFinds which points fall inside polygons using a point-in-polygon spatial relationship and returns new feature data. Feature geometry and attribute statistics are also generated for the number of points in each polygon.Point or polygon feature dataPolygon feature data aggregate points
Summarize nearbyFinds features within a specified distance of other feature data and returns new feature data. The distance measure can be a straight line or defined by travel mode (e.g. drive time or distance). Feature geometry and attribute statistics are also generated.Point, polyline, or polygon feature dataPoint, polyline, or polygon feature data summarize nearby
Summarize withinFinds areas (and portions of areas) that overlap between two feature datasets, calculates statistics about the overlap, and returns new feature data. Additional feature geometry and attribute statistics are also generated.Polygon features
Point, polyline, or polygon feature data
Point, polyline, or polygon feature data summarize within
Summarize center and dispersionFinds central features and directional distribution in feature data and returns new feature data. It calculates the central, mean center, median center, or ellipse of features to determine the distribution.Point, line, or polygon feature dataPolygon feature data summarize center and dispersion

Analyze patterns

Analyze patterns operations allow you to perform complex geometry, attribute, and statistic calculations to identify spatial patterns and relationships in feature data. All operations result in new feature data.

OperationDescription
Input data
Output data
Example
Find hot spotsFinds spatially and statistically significant clusters of features with high values (red hot spots) and low values (blue cold spots) and returns new feature data. Calculations can be performed on geometries or geometries and attributes.Point or polygon feature dataPoint or polygon feature data find hot spots
Find outliersFinds spatial and statistical anomalies in clusters of feature data and returns new feature data. Features are assigned colors from red, blue, to beige (significantly high outlier to significantly low outlier).Point or polygon feature dataPoint or polygon feature data find outliers
Find point clustersFinds clusters of point features at a specified distance and using unsupervised machine learning clustering algorithms and returns new feature data.Point feature dataPoint feature data find point clusters
Calculate densityFinds areas in feature data that are the most and least dense and returns new feature data. It spreads known quantities of some phenomenon (represented as attributes of the points or lines) to create polygon features.Point or line feature dataPolygon feature data calculate density
Interpolate pointsFinds and predicts new features and attribute values in point feature data and returns new feature data. Parameters can be used to control the speed and accuracy of the analysis.Point feature dataPolygon feature data interpolate points

Calculate geometries

Calculate geometries operations allow you to perform different types of geometric calculations on feature data and to create new feature data such as grids, tessellations, and bins.

OperationDescription
Input data
Output data
Example
Create buffersCreates areas at a distance around a point, line, or polygon feature and returns new feature data.Point, polyline, or polygon feature dataPolygon feature data create buffers
Find centroidsFinds the representative center (centroid) of each multipoint, polyline, or polygon feature and returns new feature data.Multipoint, point, polyline, or polygon feature dataMultipoint, point, polyline, or polygon feature data find centroids
Generate tessellationsCreates equally sized square, hexagon, triangle, or diamond geometry bins for an area or extent and returns new feature data.Not requiredPolygon feature data generate tessellations

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Spatial analysis service

Process spatial datasets to discover relationships and patterns.

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