GIS for Local Government: Public Safety

Authors: Brett Lucas and Stewart Berry

Introduction

This article explores how to use GIS in local or Municipal Government. Many local governments are being asked to have a more transparent relationship with their citizens, which has been supported by technologies like geographic information systems (GIS) and other data visualization tools which allows communities to manipulate, analyze, and present data in a geographic form. GIS as a tool, can help local government decision-makers, policymakers, and others visualize data for a variety of applications.

This could include:

Analyze crime patterns, assess public safety risk, and identify areas of concern.
Create maps to visualize and monitor changes in crime and emergency response.
Identify potential areas of public safety risk and plan for emergency response.
Examine how proposed changes in development or infrastructure might affect public safety.

As a local government, utilizing GIS can help you better communicate that data through a visual component. Many local governments have found ways to leverage geospatial data across an organization in areas like building permit inspections, code enforcement, and street repair.

GIS Software for Government

Maptitude mapping software is an ideal software platform for local governments (especially smaller municipalities on a tight budget at only $695) to leverage geospatial data across an organization. Maptitude is a full featured desktop or online GIS and mapping software that gives you the tools, maps, and demographic data to analyze and understand how geography affects you and your community.

In this article we will demonstrate an application of Maptitude in the municipal government sector for public safety mapping.

Public Safety – Mapping Income and Robberies

For this example, we will be using the City of Seattle, WA (USA). The city’s police department has downloadable crime data for the past 15 years in CSV file format, which can be opened in Excel. Because the file is large, you could edit the data to remove rows (years) or columns (variables) that are not of interest.

Download a free mapping software trial of Maptitude Desktop or use your existing Maptitude Desktop license.
Start Maptitude and select "New Map of my data/table/spreadsheet." Choose the .csv or .xlsx file that you downloaded from the Seattle Government web site.
When going through the "Create a MapWizard" steps, choose to map your data by latitude/longitude. The result will resemble Map 1. Alternatively, if your data is structured by address, you can pin-map the locations using the built-in geocoder in Maptitude.

Map 1: Maptitude Workspace showing crime locations

We are interested in robberies that occurred during the last third of 2022. The easiest way to filter for this time period is by using "selection sets". Using the "Selection Toolbar," create two new selection sets. For "Selection:1" use "Select by Condition", and type: [Offence Parent Group] = "ROBBERY" (Figure 1). Once that is done, and using "Selection:2", select by condition by typing (or by choosing from the drop-downs): Date between "9/1/2022" and "12/31/2022". The result will resemble Map 2.

Figure 1: Select by Condition dialogue box

Map 2: Maptitude Workspace showing crime locations, with sets on robberies and by date

We want:
[Offence Parent Group] = "ROBBERY" AND (Date between "9/1/2022" and "12/31/2022")
We could run this as a single Select by Condition. Instead, we will combine selection sets, using Selection > Combine Selection as shown in Figure 2. The result will resemble Map 3.

Figure 2: Combine Selection

Map 3: Maptitude Workspace showing crime locations, with the combined selection set (locations in yellow)

To better visualize the combined selection set we will want to create a heat (density or hot spot) map. Make "Crime Data Layer" the working layer. To create a heat map, choose the "Create Density Grids" button. When prompted, choose "Crime Data Layer", for Layer. For Set, choose "Selection:3". For settings, choose a radius of "0.5 miles" and a Cell Width of "0.02." Click "OK". A heat map will be created. To better visualize the heat map, turn off the "Crime Data Layer" in the Display Manager. The result should resemble Map 4. This map shows that the highest concentrations of robberies between 9/1/22 and 12/31/22 are in downtown Seattle with other concentrations or "hot spots" throughout the city.

Map 4: Maptitude Workspace showing a "heat map" of crime locations

Next, we want to assign crime to a specific geography or defined area such as a Census Block Group or a grid layer. A grid will keep geography constant. To do this, turn off the "Density" layer in the Display Manager and make the "Crime Data Layer" the working layer. Also, zoom into downtown Seattle, bounded by I-90 on the south and Lake Washington Ship Canal and Lake Union to the north.
Create a new selection set "Selection:4". Then choose Selection > Select by Map Window.
Combine "Selection:1" (Robberies) and ‘Selection:4" (geography) into a new set: Selection:5. The result will resemble Map 5. Use "Selection:5’ via File > Export > Geography to add a new "Compact Geographic file" layer to the map called "Crime Data Layer-2".

Map 5: Maptitude Workspace showing Selection:5

To analyze socioeconomic data, add the "Census Block Group" layer to the map. Maptitude has this layer available for purchase. Alternatively, you can use the included Census Tracts.
To keep geography constant, we need to create a Grid layer. Use Tools > Editing > New Grid Layer as shown in Figure 3. Name the layer "Grid-1". Under "Method" choose "Cover the map window with cells of a fixed size". For the fixed size (miles), choose 0.25 by 0.25, i.e., quarter mile squares. The result will resemble Map 6.

Figure 3: Grid window

Map 6: Maptitude Workspace showing a Grid layer

Next, we need to add some data to the new Grid layer. First, we need to modify the table and add a new field for "Median Household Income" and a field for "Robberies". To do that, use Dataview > Table > Modify as shown in Figure 4. Add a new field "Med HH Inc" and change the format to currency ($1,234) without decimals. Add a second field "Robberies", and change the format to number (1,234) without decimals. Click "OK".

Figure 4: Modify Table window

Next, we need to overlay some data. Make sure your "Grid-1" layer is the working layer. Choose Dataview > New Dataview, and a table for the layer will open. Right click on the ‘Med HH Inc" column and choose "Fill". Choose the "Aggregate" radio button. A new "Aggregate Data" window will appear. For "layer" choose "Block Group." Under Aggregate Settings, choose "average of", "[HH Median income]", and the choose "OK". Choose "OK". Repeat this process for "Robberies" using "Crime Data Layer-2" and using the Aggregate Settings to fill with "Count".
Next, we want to create a "Color Theme" for the cells within the grid, to show lower income and higher income areas. Choose Map > Thematic Mapping > Color. For "Field" choose "HH Median income", and then choose "Optimal Breaks", and choose 5 classes. Choose "Treat zeros as missing values". Under the Styles tab for "Other" choose "None" for the Fill Style. Choose a red (lower income) to purple (higher income) color ramp, with 40% opacity. The result should resemble Map 7.

Map 7: Maptitude Workspace showing a grid layer with lower/higher income distribution

To create a visual correlation between income and robberies, we want to show robberies as a graduated symbol theme. Make "Grid-1" the working layer. Choose Map > Thematic Mapping > Size. For Field choose "Robberies". Choose "Use perceptual scaling". On the Style tab, choose black for Color, and choose "Prevent overlapping labels". Click "OK". The result will resemble Map 8 with graduated symbols.

Map 8: Maptitude Workspace showing a grid layer with an income distribution and graduated symbols

To exclude data that falls into water areas, choose Map > Thematic Mapping > Size. Under Symbol Sizes, choose a Low Value of 1 with Size 4, and a High Value of 65 with Size 30. The result will resemble Map 9.

Map 9: Maptitude Workspace showing a grid layer with an income distribution and graduated symbols sized appropriately

Conclusion

After reviewing Map 9, one can see higher amounts of robberies in cells that are colored red and yellow, which tend to be lower income areas. While this visual approach is not as precise as performing a regression, it does provide one with a useful visual correlation between income and robberies.

Maptitude is an extremely powerful software package for municipal governments for public safety. For example, law enforcement could use the results of such an analysis to better deploy police resources to select geographies where crime activity is occurring.