GeoAnalytics distributes the analysis work across your ArcGIS GeoAnalytics Server. This allows you to analyze more data faster with multiple machines. The following tools are available:
GeoAnalytics focuses on analyzing large amounts of data with an emphasis on both spatial and temporal patterns.
The Summarize Data toolset contains tools that calculate total counts, lengths, areas, and basic descriptive statistics of features and their attributes within areas or near other features.
Aggregate Points |
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Using a layer of point features and either a layer of area features or bins defined by a specified distance, this tool determines which points fall within each area or bin and calculates statistics about all the points within each area or bin. You can optionally apply time slicing with this tool.
The following are examples:
Build Multi-Variable Grid |
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This tool generates a grid of square or hexagonal bins and calculates variables for each bin based on the proximity of one or more input layers.
The following are examples:
Describe Dataset |
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This tool summarizes input features with statistics, sample layers, and visualization. You can choose to output a sample layer or extent layer.
The following are examples:
Join Features |
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Using either feature layers or tabular data, you can join features and records based on specific relationships between the input layers or tables. Joins will be determined by spatial, temporal, and attribute relationships, and summary statistics can be optionally calculated.
The following are examples:
Reconstruct Tracks |
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Using a time-enabled layer of point or polygon features that represent an instant in time, this tool determines which input features belong in a track and will order the inputs sequentially in time. Statistics are optionally calculated for the input features within each track.
The following are examples:
Summarize Attributes |
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Using either feature or tabular data, this tool summarizes statistics for specified fields.
The following are examples:
Summarize Within |
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This tool finds areas (and portions of areas) that overlap between two layers and calculates statistics about the overlap.
The following are examples:
These tools are used to identify areas that meet a number of criteria you specify.
Detect Incidents |
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This tool works with a time-enabled layer of points, lines, areas, or tables that represents an instant in time. Using sequentially ordered features, called tracks, this tool determines which features are incidents of interest. Incidents are determined by conditions that you specify.
The following are examples:
Geocode Locations from Table |
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This tool converts addresses into coordinates. Use this tool on big data file share tables.
Find Dwell Locations |
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This tool works with track datasets; it is composed of a time-enabled layer of points to find where objects dwell within a specified distance and duration.
The following are examples:
Find Similar Locations |
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Based on criteria you specify, find similar locations by measuring the similarity of locations in your candidate search layer to one or more reference locations.
The following are examples:
These tools identify, quantify, and visualize spatial patterns in your data.
Calculate Density |
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This tool creates a density map from point features by spreading known quantities of some phenomenon (represented as attributes of the points) across the map. The result is a layer of areas representing the density.
The following are examples:
Find Point Clusters |
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This tool finds clusters of point features in surrounding noise based on their spatial distribution.
The following are examples:
Find Hot Spots |
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This tool will determine if there is any statistically significant clustering in the spatial pattern of your data.
Forest-Based Classification and Regression |
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This tool models and generates predictions using an adaptation of Leo Breiman's random forest algorithm, which is a supervised machine learning method.
The following are examples:
Generalized Linear Regression |
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This tool generates predictions or models a dependent variable in terms of its relationship to a set of explanatory variables. This tool can be used to fit continuous (OLS), binary (logistic), and count (Poisson) models.
The following are examples:
Geographically Weighted Regression |
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This tool performs Geographically Weighted Regression (GWR), which is a local form of linear regression used to model spatially varying relationships.
The following are examples:
These tools help answer one of the most common questions posed in spatial analysis: What is near what?
Create Buffers |
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A buffer is an area that covers a given distance from a point, line, or polygon feature.
The following are examples:
Trace Proximity Events |
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This tool analyzes time-enabled point features representing moving entities. The task will follow entities of interest in space (location) and time to see which other entities the entities of interest have interacted with. The trace will continue from entity to entity to a configurable value of maximum degrees of separation from the original entity of interest.
The following are examples:
These tools are used for the day-to-day management of geographic and tabular data.
Append Data |
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This tool appends features to an existing hosted layer in your contents in ArcGIS Enterprise.
The following are examples:
Calculate Field |
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This tool calculates values for a new or existing field and creates a layer in your contents in ArcGIS Enterprise.
The following are examples:
Clip Layer |
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This tool clips input features from defined areas of interest. The output result will be a subset of input features.
The following are examples:
Copy to Data Store |
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This tool copies an input feature layer or table to an ArcGIS Data Store and creates a layer in your contents in ArcGIS Enterprise.
The following are examples:
.csv
files in a big data file share to the spatiotemporal data store for visualization.
Dissolve Boundaries |
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This tool merges area features that intersect or share a common field value to create contiguous or multipart features.
The following are examples:
Merge Layers |
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This tool combines two feature layers to create a single result layer. All fields from the merge layer will be included by default, or you can specify custom merge rules to define the resulting schema.
The following are examples:
Overlay Layers |
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This tool combines two or more layers into one layer. Overlay is used to answer one of the most basic questions of geography: What is on top of what?
The following are examples:
These tools help you explore the character of areas.
Calculate Motion Statistics |
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This tool calculates groups of motion statistics and measurements for time-enabled points that represent tracks.
The following are examples:
Enrich From Multi-Variable Grid |
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This tool efficiently joins attributes from a multivariable grid to a point layer, allowing you to quickly add a large and diverse collection of information to point data for use in further spatial analysis.
The following is an example: