The Crime Analysis solution delivers a set of capabilities to help you manage and query incident data, conduct tactical, strategic, and investigative analysis, and share web-based and hard-copy information products with decision makers.
In this topic, you’ll learn how to use the Crime Analysis solution by exploring Crime Analysis tools, navigating the Crime Analysis Add-In, and reviewing the Repeat and Near Repeat tools.
Crime Analysis tools
The Crime Analysis solution contains many tools to support key analytical functions to manage data, select crime incidents, conduct tactical and strategic analysis, investigate crime patterns, and share information with other law enforcement personnel. These tools are accessed through the Crime Analysis tab and ribbon which is automatically added to your projects when you install the Crime Analysis add-in. The following sections contain a list of the tool groups on the ribbon, with details for each tool in chronological order according to a typical crime analysis process.
Note:
You will need to ensure the Crime Analysis add-in is installed before you can review the Crime Analysis tools. See Configure Crime Analysis for more information.
Data Management tools
Crime analysts can import data from disparate record systems to perform spatial analysis using ArcGIS Pro. In many cases, the data must also be geocoded and prepared for analysis. For example, you many want to append information about police operational boundaries, transform date values, or perform other transformation functions. The Data Management group includes a series of tools that can be used for manual or automatic data import, geocoding, and enhancing of data for use in crime mapping and spatial analysis.
The following tools and commands are included in the Data Management group of the Crime Analysis ribbon:
| Name | Description |
|---|---|
| An ArcGIS Pro menu command that references data management tools that add data to the map. | |
| An ArcGIS Pro menu command that provides a way to include simple notations on a map or layout that highlight particular areas or label places. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox that converts a nonspatial table to point features based on x,y coordinates or street addresses and updates an existing dataset with new or updated record information from the table. | |
| An ArcGIS Pro Data Management tool that converts time values stored in a string or numeric field to a date field. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox that creates a 3D feature class using date values from input features. | |
| An ArcGIS Pro Data Management tool that converts coordinate notations contained in one or two fields from one notation format to another. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox that adds fields containing date or time properties from an input date field, such as day, month, and year. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox that joins attributes from input polygon features to input point features. | |
| An ArcGIS Pro Analysis tool that enriches data by adding demographic and landscape facts about the people and places that surround or are inside data locations. |
Selection tools
Before applying spatial analysis methods, crime analysts use queries to select subsets of data related to their topic of analysis. The Selection group on the ribbon includes a series of tools to perform spatial, temporal, or location-based queries of your data.
The following tools and commands are included in the Selection group of the Crime Analysis ribbon:
| Name | Description |
|---|---|
| An ArcGIS Pro command that allows you to explore maps and scenes by zooming in and out and moving around, or, in the case of scenes, moving up or down and looking around. | |
| An ArcGIS Pro command that provides an interactive feature selection by clicking a single feature in the view or digitizing a shape to select a set of features. | |
| An ArcGIS Pro Data Management tool that adds, updates, or removes a layer or table-view selection based on an attribute query. | |
| An ArcGIS Pro Data Management tool that selects features in a layer based on a spatial relationship to features in another dataset. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox used to select records based on date and time ranges or date properties, such as a single date, a time range, a time period, days of the week, a month, or a year. | |
| Attributes | An ArcGIS Pro command that displays the Attribute pane. |
| Clear | An ArcGIS Pro command that clears the current selection in the active map. |
| An ArcGIS Pro command that creates a layer based on a selected set of features in an existing layer. |
Analysis tools
Crime analysts perform many types of analyses to support the needs of law enforcement decision makers in their organization. The Analysis Tools group includes a gallery of tools that can be used to perform a variety of hotspot detection techniques and other spatial methods that can be applied as part of tactical or strategic crime analysis projects. The gallery also includes tools to apply spatial methods in support of investigations, such as cell phone analysis, crime series sequencing, or motor vehicle theft to recovery linking.
The following tools and commands are included in the Analysis Tools group of the Crime Analysis ribbon:
| Name | Description |
|---|---|
| An ArcGIS Pro Analysis tool that calculates summary statistics for field(s) in a table. | |
| An ArcGIS Pro Analysis tool that creates buffer polygons around input features to a specified distance using a parallel processing approach. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox used to conduct an 80/20 analysis of features and determines cluster locations by creating a graduated symbol layer based on the number of incidents occurring at each location. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox used to create a feature class with coincident point counts. Coincident point counts for line and point features are determined by a specified maximum distance. Point counts for polygon features are determined by whether point features or portions of features overlap with the polygon feature. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox used to calculate the percent change for features that correspond with point features that represent two equal comparison time periods. | |
| An ArcGIS Pro Spatial Statistics tool that creates a map of statistically significant hot and cold spots using the Getis-Ord Gi* statistic. | |
| An ArcGIS Pro Spatial Analyst tool that calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline. This tool requires a Spatial Analyst license. | |
An ArcGIS Pro Spatial Analyst tool that expands kernel density calculations from analyzing the relative position and magnitude of the input features to include other dimensions such as time and depth (elevation). The resulting output identifies the magnitude-per-unit area using the multiple kernel functions to fit a smoothly tapered surface to each input point. | |
An ArcGIS Pro Spatial Statistics tool that compares two hot spot analysis result layers and measures their similarity and association. | |
| An ArcGIS Pro Spatial Analyst tool that subtracts the value of the second input raster from the value of the first input raster on a cell-by-cell basis. | |
| An ArcGIS Pro Space Time Pattern Mining tool that summarizes a set of points into a netCDF data structure by aggregating them into space-time bins. | |
| An ArcGIS Pro Space Time Pattern Mining tool that identifies trends in the clustering of point densities. | |
| An ArcGIS Pro Intelligence tool that measures local patterns of spatial association, or colocation, between two categories of point features using the colocation quotient statistic. | |
| An ArcGIS Pro Spatial Statistics tool that finds clusters of point features within surrounding noise based on their spatial distribution. | |
| An ArcGIS Pro Intelligence tool that converts a series of output paths from time-enabled sequences of input point data, such as GPS points. | |
| An ArcGIS Pro Analysis tool that generates connecting lines from origin features to destination features. The result is often referred to as a spider diagram. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox tool used to create cell site points and sector polygons based on input latitude, longitude, azimuth, beamwidth, and radius information from a cell site table. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox tool used to import cell phone records from wireless network providers and associates those records with a cell site and sector feature classes as generated by the Cell Site Records To Feature Class tool based on identifier fields. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox tool used to create line features that represent the call links between phones, using cell site points or cell site antenna sectors based on the start date and time of the call. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox tool that identifies matches between two feature classes based on proximity, time extent, or both. | |
| An ArcGIS Pro Crime Analysis and Safety toolbox tool used to create line features that represent the extent of cell site antenna sectors. | |
| An ArcGIS Pro Data Management tool that aggregates features based on specified attributes. | |
| A Repeat and Near Repeat tool that creates a CSV file in the format required by the Near Repeat Calculator from an input feature class. The Near Repeat Calculator is a tool published by Temple University for examining the statistical significance of repeat and near-repeat patterns in a dataset. | |
| A Repeat and Near Repeat tool that uses a series of distance and time values to classify incidents as originators, repeats, or near repeats, and to identify potential spatial and temporal relationships between incidents. | |
| A Repeat and Near Repeat tool that identifies areas at risk of repeat and near-repeat incidents by specifying the spatial and temporal range of influence of past incidents. |
Information products
After an analysis is complete, crime analysts often prepare hard-copy maps and web-based information products to help their organizations make data-driven decisions. The Information Products group includes a series of tools to create information products for analysis consumers, including link charts, hard-copy maps, charts, and reports, and to publish maps and layers to organizational web GIS portals.
The following tools and commands are included in the Information Products group of the Crime Analysis ribbon:
| Name | Description |
|---|---|
| An ArcGIS Pro command that creates a chart to visualize categories, distribution, change and relationships in your data. | |
| An ArcGIS Pro command used to generate a link chart to visualize relationships between entities in your data and is a complementary view to the map. | |
| An ArcGIS Pro command used to generate a report to share a well-formatted, multipage representation of your data. A report can contain a tabular list of attributes, summary information, or both. | |
| An ArcGIS Pro command that creates a layout and adds it to the project. | |
| An ArcGIS Pro command used to share the active map as a web map to your organization. | |
| An ArcGIS Pro command used to share all data layers in the active map as a new web layer to your organization. | |
An ArcGIS Pro command used to capture a screenshot of the visible portion of an active map or a layout to the clipboard for insertion into other applications. |
Repeat and Near Repeat Analysis tools
Repeat Victimization is an empirically observed phenomenon where when a location becomes the victim of a specific type of crime, that location has an elevated risk of subsequent victimization, a risk which drops precipitously over time. A corollary phenomenon is known as Near-Repeat Victimization, whereby locations immediately around a location that has been victimized are at elevated risk, a level that drops both as time passes and as the distance from the originating victim increases. Repeat and Near Repeat patterns have been observed across a wide variety of crime types, are believed to be spatial artifacts of serial offending behaviors, and thus have important implications for crime prevention and investigations.
The Crime Analysis solution includes three custom geoprocessing tools to support analyses relative to Repeat and Near Repeat Victimization patterns. The Export Near Repeat Calculator Table tool can be used with Temple University’s Near Repeat Calculator to identify statistically significant patterns of Repeat and Near Repeat Victimization. The Near Repeat Classification tool can be used to identify historical patterns of repeat and near-repeat victimization, which can support investigative efforts to connect and clear cases that were not otherwise known to be part of a pattern. The Calculate Prediction Zones tool can be used to generate daily tactical crime risk predictions based on Repeat Victimization and Near-Repeat Victimization risk for recent crime locations. These risk predictions can be used to inform police operational strategies for crime reduction.
The tools in the Crime Analysis solution related to Repeat and Near Repeat Victimization (Export Near Repeat Calculator Table, Repeat and Near Repeat Classification, and Calculate Prediction Zones) were developed in cooperation with Spencer Chainey, Ph.D., Associate Professor in Security and Crime Science at the Jill Dando Institute of Security and Crime Science, University College London.
Export Near Repeat Calculator Table Tool
The Near Repeat Calculator is a tool published by Temple University for examining the statistical significance of repeat and near-repeat patterns in a dataset. When a statistically significant repeat or near-repeat pattern is found, the spatial and temporal bandwidths of the pattern can then be used as parameters for analyses involving the Repeat and Near Repeat Classification Tool and the Calculate Prediction Zones tool. This tool creates a comma-separated values (CSV) file from an input feature class in the format required by the Near Repeat Calculator.
Usage
- Input features must have a date field.
- The output comma-separated values (CSV) file does not contain any field headers because they are not supported by the Near Repeat Calculator. In order, the output fields are X, Y, Date.
Syntax
ExportNearRepeatCalculatorTable_crime (Input_Feature_Class, Output_Table, Date_Field)
| Parameter | Explanation | Data Type |
|---|---|---|
| Output Table | Specify the path and file name of output comma-separated values (CSV) file. | File |
| Date Field | The field in the input feature class that contains the date on which each incident occurred. If the date of the incident spans a range (for example, date information is recorded in two fields that represent the from and to dates), choose the date field you consider to be most appropriate. It will usually be the date at the beginning of the date range. | Field |
Licensing information:
- ArcGIS Desktop Basic: Yes
- ArcGIS Desktop Standard: Yes
- ArcGIS Advanced: Yes
Repeat and Near Repeat Classification tool
Use a series of distance and time values to classify incidents as originators, repeats, or near repeats, and to identify potential spatial and temporal relationships between incidents.
Usage
- The Input Features must be a point feature class or shape file with a date field, representing the locations of incidents.
- The tool will use all points with date values. Incidents without valid dates will be excluded and a warning message will print to the screen listing the skipped incidents.
- This tool will honor a selected set of features. When the Input Features contain a selection, only the selected features will be considered when classifying features and building connections.
- Incidents are classified as O (Originator), NR (near repeat), or R (repeat) according to their proximity to each other in space and time using each combination of the specified spatial and temporal band values and the specified repeat distance.
- Incidents are classified as originators if they are the originator of at least one other incident and have no preceding incidents within the current spatial and temporal ranges.
- Incidents are classified as near-repeat incidents when they follow a previous repeat, near-repeat, or originating incident within the current spatial and temporal ranges, and do not meet the criteria to be classified as a repeat incident.
- Incidents are classified as repeat incidents when they occur within the specified repeat distance and the current temporal range. An incident that meets the requirements for both a repeat and a near-repeat incident is classified as a repeat.
- Incidents that do not meet the criteria for any of the above are left unclassified.
- This tool creates the following three outputs:
- A copy of the input incident features with classification fields added. These fields are populated with the classification values for each incident within each set to spatial and temporal ranges. For example, if a repeat distance of 1 map unit (Feet), spatial bands of 100 and 200 map units (Feet), and temporal bands of 7 and 14 days are specified, the tool will append six fields with the following field names and aliases:
- sb0tb1 (1 ft / 7 Days): Classification of incidents that are originators of repeat incidents occurring no more than 7 days later and incidents that occurred within the repeat distance and 7 days of a previous incident.
- sb0tb1 (1 ft / 14 Days): Classification of incidents that are originators of repeat incidents occurring no more than 14 days later, and incidents that occurred within the repeat distance and 14 days of a previous incident.
- sb1tb1 (100 ft / 7 Days): Classification of incidents that are originators of repeat and near-repeat incidents occurring no more than 7 days later and incidents that occurred within 100 map units and 7 days of a previous incident.
- sb1tb2 (100 ft / 14 Days): Classification of incidents that are originators of repeat and near-repeat incidents occurring no more than 14 days later and incidents that occurred within 100 map units and 14 days of a previous incident.
- sb2tb1 (200 ft / 7 Days): Classification of incidents that are originators of repeat and near-repeat incidents occurring no more than 7 days later and incidents that occurred within 200 map units and 7 days of a previous incident.
- sb2tb2 (200 ft / 14 Days): Classification of incidents that are originators of repeat and near-repeat incidents occurring no more than 14 days later and incidents that occurred within 200 map units and 14 days of a previous incident.
- The tool also appends a field called ZVALUE with values that represent the number of days between each incident and the smallest date value in the dataset. These values can be used to visualize the time sequence of incidents in ArcGIS Pro so that oldest incidents appear near the ground and more recent incidents appear farther from the ground.
- A line feature class that is populated with z-enabled line features representing the potential relationships between repeat and near-repeat incidents and their originators. The z values for each vertex correspond to the ZVALUE field value for the incident that occurs at that vertex.
- A comma-separated values (CSV) file summary report with the number of incidents processed, the counts and proportions of incidents that fall within each spatial and temporal band combination, and the estimated half-life and half-distance values which can be used as inputs for the Calculate Prediction Zones tool.
- A copy of the input incident features with classification fields added. These fields are populated with the classification values for each incident within each set to spatial and temporal ranges. For example, if a repeat distance of 1 map unit (Feet), spatial bands of 100 and 200 map units (Feet), and temporal bands of 7 and 14 days are specified, the tool will append six fields with the following field names and aliases:
- All distances are calculated using geodesic measurements.
Syntax
RepeatNearRepeatClassification_crime (Input_Feature_Class, Output_Incident_Points, Output_Incident_Connection_Lines, Output_Summary_Report_Location, Date_Field, Repeat_Incident_Distance, Spatial_Bands, Temporal_Bands)
| Parameter | Explanation | Data Type |
|---|---|---|
| Input Feature Class | Feature class containing points that represent the location of incidents to classify. The data contained in the features class will typically cover a long time period (for example, one year). The feature class must have a date field (in date format) and all features must have date values. | Feature Layer |
| Output Incident Points | Output feature class containing calculated classification values. | Feature Layer or Feature Class |
| Output Summary Report Location | The results from the analysis of repeats and near repeats written into a summary report (CSV file format) for review. The report can be found in this folder after the tool has completed successfully. The results are also written to the Messages section of the Results window. | Folder |
| Date Field | The field in the input feature class containing the date on which each incident occurred. If the date of the incident spans a range (for example, date information is recorded in two fields that represent the from and to dates), choose the date field you consider to be most appropriate. It will usually be the date at the beginning of the date range. Values in the date field are used to calculate the number of days between each incident. | Field |
| Repeat Incident Distance | Maximum distance in the units of the input feature class where adjacent incidents are considered repeats rather than near repeats. A value of 0 is exact to the accuracy of the coordinate system. If the geocoding of the input feature class is likely to vary very slightly, it is recommended this value be set to 1 (in other words, incidents will be classified as repeats if the distance between them is less than or equal to 1 map unit). | Double |
| Spatial Bands | Distance in the units of the input feature class to classify near incidents. Multiple bands can be entered. For example, bands of 200m and 400m will classify features that are located up to and including 200m from a previous incident and up to and including 400m of a previous incident. | Multiple Value |
| Temporal Bands | Number of days to classify near incidents. Multiple bands can be entered. For example, bands of 7, 14 and 21 days will classify features that took place up to and including 7 days, 14 days, and 21 days of a previous incident. | Multiple Value |
Licensing information:
- ArcGIS Desktop Basic: No
- ArcGIS Desktop Standard: No
- ArcGIS Advanced: Yes
Calculate Prediction Zones tool
Identify areas at risk of repeat and near-repeat incidents by specifying the spatial and temporal range of influence of past incidents.
Usage
- The Input Features must be a point feature class or shape file with a date field, representing the locations of incidents.
- The tool will use all points with date values in the Temporal Range of Influence preceding the Initial Processing Date. Features with date values outside this range and features with null or invalid date values will not be processed.
- This tool will honor a selected set of features. When the Input Features contain a selection, only the selected features will be considered when building the prediction zones.
- Incidents that occur closer in time to the Initial Processing Date will have more influence over the prediction zones than older incidents. Areas nearer to incidents will be considered to have a greater risk of future incidents, up to the Spatial Range of Influence. Use the Spatial Half Distance and Temporal Half Life parameters to modify the rate of decay of influence.
- The following fields are populated in the output feature class:
- CREATEDATE: Text field populated with the date and time the features are created.
- STARTDATE: The Initial Processing Date, or the calculated date if TODAY or YESTERDAY is the input value.
- TIMEBAND: The Temporal Range of Influence used to generate the features.
- SPACEBAND: The Spatial Range of Influence used to generate the features.
- RISKRANGE: The classification of risk for the area defined by that polygon. Higher values have a higher level of risk and lower values have a lower value of risk based on the location and dates of nearby incidents.
- This tool creates up to two outputs:
- A raster representation of the levels of risk over the area covered by the incidents.
- Polygons generated by binning the raster values into a number of Risk Ranges are appended to the Output Prediction Zones Feature Class, as previously described.
- Although storing the output raster in a geodatabase is supported, it is recommended to store the raster in a folder rather than a geodatabase, especially if this tool will be run as a scheduled task.
- All distances are calculated using geodesic measurements.
- This tool requires the Spatial Analyst extension.
Syntax
CalculatePredictionZones_crime (Input_Features, Output_Prediction_Zones_Raster, Output_Prediction_Zones_Feature_Class, Date_Field, Initial_Processing_Date, Spatial_Range_of_Influence, Spatial_Half_Distance, Temporal_Range_of_Influence, Temporal_Half_Life, Risk_Calculation_Method, Number_of_Risk_Ranges)
| Parameter | Explanation | Data Type |
|---|---|---|
| Input Features | Feature class containing points that represent the location of incidents and from which prediction zones will be calculated. The feature class must have a date field (in date format) and all features must have date values. | Feature Layer |
| Point Join Features | Point features coincident with the input polygon or line features. | Feature Layer |
| Output Prediction Zones Raster | Output prediction zone raster. | Raster Layer |
| Output Prediction Zones Feature Class | Output feature class with polygons that represent the prediction zones. | Feature Class or Feature Layer |
| Date Field | The field in the input feature class containing the date on which each incident occurred. If the date of the incident spans a range (for example, date information is recorded in two fields that represent the from and to dates), choose the date field you consider to be most appropriate. It will usually be the date at the beginning of the date range. Values in the date field are used to calculate the level of future risk based on a combination of when the incident occurred, the Initial Processing Date and the temporal decay in risk (determined from the Temporal Range of Influence and the Temporal Half Life). | Field |
| Initial Processing Date | The date to use from the Input Feature Class for creating the prediction zones. | Date |
| Spatial Range of Influence | This value determines the size of the prediction zones around each incident (in the units of the coordinate system of the Input Feature Class). The value refers to the maximum distance from an incident that the incident is estimated to have on influencing the risk of future incidents taking place. Additionally, this value can be based on the area around an incident that is considered to be practical for resource targeting and deployment (for example, the area to which additional patrols are targeted). | Double |
| Spatial Half Distance | The distance from an incident at which the risk is estimated to be half that of another incident taking place (a near-repeat). This value is used to calculate the exponential rate of decay in the spatial risk of a near-repeat incident and must be lower than the value for the Spatial Range of Influence. Distance units are the units of the coordinate system of the input feature class. A useful initial value to apply is half the value of the Spatial Range of Influence. | Double |
| Temporal Range of Influence | This value refers to the number of days before the Initial Processing Date that incidents are estimated to have an influence on the risk of future incidents taking place. More recent incidents have the greatest level of influence on future risk. Incidents that took place between the Initial Processing Date and the value for the Temporal Range of Influence are used for creating prediction zones. For example, if this value is set to 3, only incidents for the Initial Processing Date and the two days prior would be used for creating prediction zones. Incidents that took place three days ago would have less of an influence on the risk of future incidents than those that took place on the Initial Processing Date. | Double |
| Temporal Half Life | The number of days before the Initial Processing Date on which the risk is estimated to be half that of further incidents taking place immediately after the Initial Processing Date. (For example, incidents that take place on the Initial Processing Date are considered to have the greatest influence on the risk of future incidents taking place. Incidents before the Initial Processing Date have less influence on future risk.) This value is used to calculate the exponential rate of decay in the temporal risk of a repeat and near-repeat incident and must be lower than the value for the Temporal Range of Influence. A useful initial value to apply is half the value of the Temporal Range of Influence. | Double |
| Risk Calculation Method | Choose the method for calculating the predictive risk. 'CUMULATIVE' (default) creates prediction zones where the value of each cell is the sum of any prediction zone cells that overlap. 'MAXIMUM' creates prediction zones where the value of each cell is the maximum value of any prediction zone cells that overlap. | String |
| Number of Risk Ranges | Integer value that represents the number of ranges that will be used in the polygon version of the output for representing the variation in predicted risk (for example, if this value is set to 2, two Risk Ranges would determine areas of primary risk from areas of secondary risk). | Long |
Licensing information:
- ArcGIS Desktop Basic: Requires Spatial Analyst
- ArcGIS Desktop Standard: Requires Spatial Analyst
- ArcGIS Advanced: Requires Spatial Analyst