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Perform big data analysis using ArcGIS GeoAnalytics Server

In version 10.5 and later, you can perform feature analysis using distributed computing with the tools provided by ArcGIS GeoAnalytics Server. These tools can analyze patterns and aggregate data in the context of both space and time as well as help you answer questions such as the following:

  • Using millions of emergency calls accumulated over decades, which areas had the highest rates of emergency calls?
  • What are the most popular locations for taxi pickups in New York City, and how is this trend changing weekly?
  • What is the flight path of recorded GPS tracks, and how many of those paths occurred within 100 km of a no-fly zone in 2015?

Access the GeoAnalytics Tools

The feature analysis tools from ArcGIS GeoAnalytics Server can be used in Map Viewer, in ArcGIS Pro, the ArcGIS API for Python, and via the ArcGIS REST API. As a portal member, you can access the tools using the steps below.

For information on running the tools through the ArcGIS REST API, see the ArcGIS REST API documentation. To learn more about running the tools in ArcGIS Pro, see the ArcGIS Pro documentation.

Access the tools from Map Viewer

  1. Log in to the portal as a member with GeoAnalytics feature analysis privileges.
  2. Click Map to open Map Viewer.
  3. Click Analysis and choose GeoAnalytics Tools.
Note:

If you do not see the Analysis button or the GeoAnalytics Tools tab in Map Viewer, contact your portal administrator. Your portal may not be configured with ArcGIS GeoAnalytics Server, or you may not have privileges to run the tools. If you do not have the permissions required for the tools, they will not be visible.

Access the tools from the ArcGIS Python API

The ArcGIS Python API allows GIS analysts and data scientists to query, visualize, analyze, and transform their spatial data using the powerful GeoAnalytics Tools available in their organization. To learn more about the analysis capabilities of the API, see the documentation site.

The big data analysis tools can be accessed via the geoanalytics module.

Prepare your data for analysis

You can run the GeoAnalytics Tools on the following:

  • Feature layers (hosted, hosted feature layer views, and from feature services)
  • Feature collections
  • Big data file shares registered with ArcGIS GeoAnalytics Server

GeoAnalytics Tools output

The output from running GeoAnalytics Tools is hosted feature layers with data stored in the spatiotemporal big data store registered with the portal's hosting server.

Tool overview

An overview of each of the tools can be found below. The analysis tools are arranged in categories. These categories are logical groupings and do not affect how you access or use the tools in any way.

Summarize data

These tools calculate total counts, lengths, areas, and basic descriptive statistics of features and their attributes within areas or near other features.

ToolDescription

Aggregate Points

Aggregate Points

Using a layer of point features and either a layer of area features or a distance used to calculate bins, this tool determines which points fall within each area and calculates statistics about all the points within each area. You may optionally apply time slicing to this tool.

For example:

  • Given point locations of crime incidents, count the number of crimes per county or other administrative district.
  • Find the highest and lowest monthly revenues for franchise locations using 100 km bins.

Join Features

Join Features Tool

Using a layer of point, line or area features or a table and another of layer of point, line, area features or a table to join feature that exhibit a specified relationship. Spatial, temporal, and attribute relationships can be used to join features together, and optionally calculate summary statistics.

For example:

  • Given point locations of crime incidents with a time, join the crime data to itself, specifying a spatial relationship of crimes within 1 kilometers of each other, and that occurred within 1 hour of each other, to determine if there are a sequence of crimes close to each other in space and time.
  • Given a table of zip codes with demographic information and a area features representing residential building, join the demographic information to the residences, so that each residence now has the information.

Reconstruct Tracks

Reconstruct Tracks

Using either a layer of point features or polygon features that are time enabled, this tool determines which input features belong in a track, ordering the inputs sequentially in time. It then calculates statistics about all the input features within each track.

For example:

  • Given point locations and time of hurricane measurements, calculate the mean wind speed, and max wind pressure of the hurricane.

Summarize Attributes

Summarize Attributes

Using either feature or tabular data this tool summarizes statistics for field(s).

For example:

  • Given locations of grocery stores with a field COMPANY_NAME, summarize the stores by the company name to determine statistics for each company.
  • Given a table of grocery stores with a field COMPANY_NAME and COUNTY, summarize the stores by the company name and county to determine statistics for each company in each county.

Summarize Within

Summarize Within

Finds areas (and portions of areas) that overlap between two layers and calculates statistics about the overlap.

For example:

  • Given a layer of watershed areas and a layer of land-use areas by land-use type, calculate total acreage of land-use type for each watershed.
  • Given a layer of parcels in a county and a layer of city boundaries, summarize the average value of vacant parcels within each city.

Find locations

These tools find features that pass any number of criteria that you specify. They are typically used for site selection, where the objective is to find places that satisfy multiple criteria.

ToolDescription

Detect Incidents

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.

For example:

  • Given a layer of GPS measurements of hurricanes every 10 minutes. Each GPS measurement records the hurricane's name, location, time of recording, and wind speed. Using these fields, create an incident where any measurement with a wind speed greater than 208 km/h is an incident titled Catastrophic
  • Given a layer of sensor measurements, create an incident whenever values exceed the mean of the 3 previous values.

Find Similar Locations

Find Similar Locations

Based on criteria you specify, the Find Similar Locations tool measures the similarity of locations in your candidate search layer to one or more reference locations.

For example:

  • Find the ten most similar stores by examining the number of employees and the annual sales.
  • Find the 100 most similar cities by examining the relationship between population, annual growth, and tax revenue.

Geocode Locations from Table

Geocode Locations from Table

Converts addresses into coordinates. Use this tool on big data file share tables.

Analyze patterns

These tools help you identify, quantify, and visualize spatial patterns in your data.

ToolDescription

Calculate Density

Calculate Density

The Calculate Density 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.

For example:

  • Calculating densities of hospitals within a county. The result layer will show areas with high and low accessibility to hospitals, and this information can be used to decide where new hospitals should be built.
  • Identifying areas that are at high risk of forest fires based on historical locations of forest fires.
  • Locating communities that are far from major highways in order to plan where new roads should be constructed.

Find Hot Spots

Find Hot Spots

The Find Hot Spots tool will determine if there is any statistically significant clustering in the spatial pattern of your data.

  • Are your points (crime incidents, trees, traffic accidents) really clustered? How can you be sure?
  • Have you truly discovered a statistically significant hot spot (for spending, infant mortality, consistently high test scores) or would your map tell a different story if you changed the way it was symbolized?
The Find Hot Spots tool will help you answer these questions with confidence.

Create Space Time Cube

Create Space Time Cube

This tool summarizes a set of time enabled points into a netCDF structure by aggregating them into space time bins.

For example:

  • Aggregate all crimes in a city into 1 km bins by month.
  • Aggregate all 911 calls that occurred in a county over the last 50 years into 100 km bins, with annual temporal bins.

Use proximity

These tools help you answer one of the most common questions posed in spatial analysis: "What is near what?"

ToolDescription

Create Buffers

Create Buffers

A buffer is an area that covers a given distance from a point, line, or polygon feature.

For example:

  • Using linear river features, buffer each river by 50 times the width of the river to determine a proposed riparian boundary.
  • Given areas representing countries, buffer each country by 200 nautical miles to determine the maritime boundary.

Manage data

These tools are used for the day-to-day management of geographic and tabular data.

ToolDescription

Calculate Field

Calculate Field

Calculates values for a new or existing field and creates a layer in your contents on ArcGIS Enterprise.

For example

  • Modify an existing field named total to be the sum of revenue from fields total_2016, total_2017, and total_2018.
  • Create a new field to categorize hazard levels based on field values such as windspeed and pollutant.

Copy to Data Store

Copy to Data Store

Copies an input feature layer or table to an ArcGIS Data Store and creates a layer in your Web GIS.

For example:

  • Copy a collection of csv files in a big data file share to the spatiotemporal data store for visualization.
  • Copy the features in the current map extent that are stored in the spatiotemporal data store to the relational data store.