Geocoding block using ArcGIS Desktop?

Geocoding block using ArcGIS Desktop?

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The address table that I am trying to geocode does not have specific addresses; rather, it has blocks (e.g. 200 Block FIRESTONE LN).

Is it possible for me to still geocode the table?

I can't just open the table in Excel and remove all mentions of "Block", as I then wouldn't have actual existing addresses for most of my table (200 FIRESTONE LN is not an address).

I am using ArcGIS Desktop 10.2.2.

As commented by @ChrisW:

Technically 200 Firestone Ln is an address - the first point on the 200 block of that road. It may not be a mailing address, as perhaps house numbers start at 210. So there's basically two problems you have to decide on an approach to. First, if you have multiple addresses in the 200 block, there's no way to separate them and they'll get the same point. Second, the geocoder has an address range for each street segment. It might be a pattern like 200-299, and you could use 250 to stick it in the middle. But if you want valid mailing address results, no, you don't have enough info.

What's included in the geocoded results

After a table of locations is geocoded, the output point layer contains a copy of the address fields from the address table. One purpose of carrying over the address fields is for rematching. The names of this set of address fields are prefixed with IN_ , and the original fields from your table are prefixed with USER_ so that they are easy to differentiate. When an address is modified during rematching, the new address is saved in the IN_ fields rather than overwriting the original USER_ fields.

    Loc_name —The name of the locator used to return a match result. This field is available only if the locator used for matching the table is a composite locator.

The Loc_name field is used internally by ArcGIS software and is not intended for use by client applications.

Geocoding block using ArcGIS Desktop? - Geographic Information Systems

Graduate Certificate Program

Geographic Information Systems (GIS) is the process of managing and analyzing spatial data for decision-making purposes. Data have become more and more integral in the functioning of many businesses and industries. Uses include crime mapping, urban planning, logistics, environmental issues, environmental monitoring, business/public facilities location analysis, etc.

The Graduate Certificate is a 18 hour graduate three-semester sequence designed to prepare students for proficiency in the field. Students seeking admission to the certificate program are required to fulfill the general requirements for admissions to graduate programs at Chicago State University (CSU), which includes attainment of a 3.0 GPA at the undergraduate level. In addition, students who lack at least 3 hours of introductory computer programming and 3 hours of introductory GIS may be required to make up these deficiencies. Students who have already taken some of the required courses at CSU or elsewhere are encouraged to consult with the graduate advisor. Fieldwork and internships are a key part of the program. The department has established relationships with a variety of businesses, community organizations, and public agencies that hire frequently in the GIS area. For those students wishing to continue their degree program can register for one of the Master's degree program, i.e., the M.A. in Geography or the M.A. in Geography with Geographic Information Systems Concentration.

Upon completion of the certificate students should be able to:

  • Explain earth-map relationships and distortions on map projections
  • Process analog and digital remote-sensing data to prepare imagery for analysis
  • Analyze analog and digital remote-sensing data to extract/create new information
  • Build spatial databases consisting of raster and/or vector data for GIS analysis and modeling
  • Use analytical capabilities of ArcGIS and ERDAS IMAGINE for spatial analysis and modeling
  • Design and implement a major/semester-long GIS project to address a significant research question(s)
  • Design a web map that allows viewers to display and query layers on a map and
  • Organize analysis results into coherent written and oral presentations.

The Geographic Information Systems Laboratory at CSU consists of 16 Windows 10 workstations, two servers, and several printers for map output. The machines contain the latest releases ArcGIS and ERDAS IMAGINE software. Other map composition tools, geocoding and statistical software, including Corel Draw and SPSS are loaded on the workstations. Global Positioning Systems equipment is available for use in course and project work.

Also, several local and regional datasets are stored in the lab and are available for research purposes. Among these datasets are a library of Landsat satellite imagery for the past three decades covering Illinois and large parts of neighboring states, IKONOS imagery of the Lake Calumet Region, and several sets of census information. Other resources include the Calumet Environmental Resource Center (CERC) and the Fredrick Blum Neighborhood Assistance Center (NAC) .

Certificate Courses (18 hours):

Geog 5800 Introduction to GIS

Geog 4810 Cartographic Design & Visualization

Geog 5820 Environmental Remote Sensing

Geog 5830 Advanced Geographic Information Systems

Geog 5840 Advanced Remote Sensing

Geog 5850 Geographic Information Systems Applications

Additional Information About This Program

This certificate primarily prepares students to work in various career areas that focus on economic development, business, government, teaching, advanced research and community development. For information about program costs, employment, and other information, click here for gainful employment.

Address Geocoding

A guide for UW-Milwaukee GIS learners and users

In this guide, you will learn about different options for geocoding addresses, also known as address locating. Although there are other types of geocoding using geographies like census tracks or even zip codes, this page will focus on address geocoding. Address geocoding is the process of turning text addresses into geographic information for use in GIS software or mapping applications.

Warning: Some of the methods discussed in this guide are available only to UWM affiliates with an epanther ID.

Warning: Some of the methods discussed in this guide consumes credits on your ArcGIS Online account.

What is Address Geocoding?

Geocoding translates a text description of a location into spatial data. An example is mapping a list of customers by their zip code. The zip code allows us to assign each customer to a geographic area and view our customers on a map.

If you're trying to find your way to a place you have never visited before, you might enter the address into Google Maps. Google Maps will quickly use address geocoding to translate your query into a point on the map. Behind the scenes, the software is comparing the address you supplied to a list of addresses generated by querying their vast database of street and address data.

An address locator is a software object that actually does the translating from text to spatial data. In order to do its job, it needs reference data. Most often, this will be in the form of street network data with address features. A very common type of address locating in the United States is called dual range where each side of the street has a range of addresses such as 2400-2498 (even) on the left side and 2401-2499 (odd) on the right side. The address locator will take a given address and compare it to these ranges and estimate where on the block the address is likely to fall and which side of the street it is on.

Some reference data may be even more detailed and give a specific location for any valid address in the given area. This could take the form of an address points dataset or a parcel dataset. Many address locators use multiple datasets to decrease mismatches and errors.

You can read much more about address locating and other types of geocoding on their respective platforms:

Create a locator view

You can create a new view of ArcGIS World Geocoding Service to search only for specific types of locations within an area of interest. For example, you may want a locator view to limit search results to particular areas, or you may want to enforce a specific level of precision when members perform batch geocoding of addresses.

The option to create a locator view is available only if your portal is configured to use the Esri World Batch Geocoder.

To create and configure a locator view, do the following:

  1. Verify that you are signed in to your organization and have privileges to create content.
  2. From the My Content tab of the content page, click Create and click Locator (view) .
  3. Specify a title, tags, and summary for the locator, and choose a folder in which to save the locator item.
  4. Click OK to create the locator view item.

The item page for the locator view you created opens to the Settings tab.

  • All Types —Choose this option if you don't want any restrictions on the types of locations returned.
  • Addresses, Postal Codes and Populated Places —Choose this option to limit results to streets, cities, states, or postal codes.
  • Coordinates —Choose this option to limit results to MGRS or a specific format for latitude, longitude.
  • Places of Interest —Choose this option to limit results to the names of places or landmarks.
  • If you chose Addresses, Postal Codes and Populated Places and only want ArcGIS World Geocoding Service to return matches with street address or better, check the Point Address and Street Address boxes.
  • If you chose Coordinates and want to make latitude, longitude the accepted format for coordinates, check the Latitude, Longitude box.
  • If you chose Places of Interest and only want ArcGIS World Geocoding Service to return matches to airports, check the Airport box.

If your data contains a country value, search results will include any countries explicitly defined in the data. However, if countries are not explicitly defined in the data, results will be restricted to the country or countries you define using this locator view setting.

  • On the side of the street (routing location)
  • On the rooftop or parcel centroid (address location)

Your preference may not be available for all locations. If the selected preference is not available for a location, the location will be displayed with the highest precision available.

  • As defined for the country —Keep this option selected to return the default city name defined for the country. For example, cities in the United States are returned by default using the postal city name.
  • Postal city name —Select this option to return the primary postal city name even if it's different from the city name entered in the search. The postal city name is the primary name assigned to the postal code of the address. For example, the 45420 postal code in Ohio has a primary postal city value of Dayton. Addresses in the city of Kettering are assigned this postal code, which means that searches for addresses in Kettering are returned as Dayton addresses. If this option is selected and an organization member searches for 2109 E Dorothy Ln, Kettering, OH, 45420 , the match label returned is 2109 E Dorothy Ln, Dayton, Ohio, 45420, even though the address is within the Kettering city limits.
  • Local city name —Select this option to return the locally known city name even if it's different from the city name entered in the search. The local city name is the name of the city in which the address is located, and may be different from the postal city. For example, if this option is selected, a search for 2109 E Dorothy Ln, Dayton, OH, 45420 —an address in Kettering, Ohio—returns the match label of 2109 E. Dorothy Ln, Kettering, Ohio, 45420, even though Dayton is included in the search string and the postal code entered has a postal city value of Dayton.
  • Matched city name —Select this option to return the matched city name value when the city name entered in a search matches any of the local city name or postal city name values.

Not all addresses have postal city and local city values assigned to them. If the requested preferred city does not exist in the data, a different city value is returned based on default address formats.

  • As defined for the country —Keep this option selected to return the default street name. The default street name is the matched street name.
  • Matched street name —Select this option to return the matched street name value when the street name entered in a search matches any of the supported street names assigned to an address.
  • Primary street name —Select this option to return the primary street name even if it's different from the alternate street name entered in the search. The primary street name is the primary name assigned to a street. For example, if this option is selected, a search for CA-138, Pearblossom, CA returns the match label of Pearblossom Hwy, Pearblossom, California, 93553.

You must share the locator view to make it available to members of your organization or the public. Once it's shared, an administrator can add it to your organization's list of locators available for members to use for geosearch and batch geocoding.

Anonymous users will only have access to your locator view if you share it with the public. Locator views that are shared with the organization and included in your organization's list of locators are only accessible to organization members. Anonymous users will not be able to perform geosearch in any apps using locators that are only shared with the organization.

If your locator view is added to the organization's list of locators, it is recommended that you enable delete protection on the locator item to prevent accidental deletion. Once it's added, if you decide to delete your locator view in the future, your administrator must first remove it from the organization's list of locators.

Introducing Geographic Information Systems with ArcGIS: A Workbook Approach to Learning GIS, 3rd Edition

Introducing Geographic Information Systems with ArcGISintegrates a broad introduction to GIS with a software-specific workbook for Esri's ArcGIS. Where most courses make do using two separate texts, one covering GIS and another the software, this book enables students and instructors to use a single text with an integrated approach covering both in one volume with a common vocabulary and instructional style.

This revised edition focuses on the latest software updates&mdashArcGIS 10.0 and 10.1. In addition to its already successful coverage, the book allows students to experience publishing maps on the Internet through new exercises, and introduces the idea of programming in the language Esri has chosen for applications (i.e., Python). A DVD is packaged with the book, as in prior editions, containing data for working out all of the exercises.

This complete, user-friendly coursebook:

  • Is updated for the latest ArcGIS releases&mdashArcGIS 10.0 and 10.1
  • Introduces the central concepts of GIS and topics needed to understand spatial information analysis
  • Provides a considerable ability to operate important tools in ArcGIS
  • Demonstrates new capabilities of ArcGIS 10.0 and 10.1
  • Provides a basis for the advanced study of GIS and the study of the newly emerging field of GIScience

Introducing Geographic Information Systems with ArcGIS, Third Edition is the ideal guide for undergraduate students taking courses such as Introduction to GIS, Fundamentals of GIS, and Introduction to ArcGIS Desktop. It is also an important guide for professionals looking to update their skills for ArcGIS 10.0 and 10.1.

Type and level of course
The course is an upper-level introduction to GIS aimed at environmental studies students and other students from across campus.

Geoscience background assumed in this assignment

GIS/remote sensing skills/background assumed in this assignment
Add shapefiles, understand attribute tables, and change symbology. Export JPEG maps.

Software required for this assignment/activity:
ArcView 9.3

Time required for students to complete the assignment:
6 hours, including followup assignment

About location types


Use the Coordinates location type if your dataset contains X,Y coordinates. ArcGIS Insights can usually detect the X (longitude) and Y (latitude) fields in your dataset. You can override the suggested fields, and specify other fields.

For example, if your data contains two sets of coordinates, you might want to specify which coordinates you want to add location to. The default spatial reference is World Geodetic System (WGS) 1984 (4326). You can specify a different spatial reference. If you are unsure of which coordinate system to use, check with the person who created the spreadsheet or collected the data.

If your latitude (Y) values fall between -90 and 90 and the longitude (X) values fall between -180 and 180, use WGS84. If your latitude and longitude values are in meters and have 6, 7, or 8 digits before (to the left of) the decimal point, use Web Mercator.


In Insights in ArcGIS Enterprise , your portal must be configured to allow batch geocoding and you must have the Geocoding privilege to enable location by address (a transaction called geocoding).

In Insights in ArcGIS Online , you must have the Geocoding privilege to enable locations by address. The Geocoding privilege is included in both the Administrator and Publisher role. ArcGIS World Geocoding Service can be used to enable location in your data by address. Credits will be used to enable location with ArcGIS World Geocoding Service . You can also configure a custom batch geocoder for your organization. For more information, see Configure utility services.

In Insights desktop , you must be signed in to an ArcGIS organization using an account that supports Geocoding to enable location by address.

Use the Address location type to enable location using the following:

One field when location descriptions are contained in a single field. Example:

Each row in the above column generates a single point feature. You can choose a less descriptive field, such as PostalCode if you want to see each postal code as a point on a map. For area features, it's best practice to use the Geography location type (below).

Multiple fields when address information is separated across multiple fields. Example:

Each row across the selected fields generates a single point feature.


Use the Geography location type to enable location for area features, such as a postal code boundary layer from Boundaries in the Add to page window (see Add data) or custom boundaries from other datasets on your page, such as police districts.

When you use the Geography location type, a join is performed behind the scenes between the current dataset and a custom or standard boundary layer from the data pane that you specify.

Geocoding and producing Census FIPS codes for 53 million addresses: A combination approach using ArcGIS and PostgreSQL

For a recent project we had to geocode 53.1 million addresses (in CSV format), and determine the 2000 and 2010 U.S. Census block group FIPS codes for each address. The Dell PC used for all processing was running 64-bit Windows 7 Enterprise SP1 operating system machine with:
i7-2600 CPU @ 3.40GHz *2 and 16 GB of RAM.

First, the CSV file was geocoded using the ESRI Business Analyst 2013 for Desktop USA Geocoding Service address locator, using ArcGIS 10.2 software. The processing took about 106 hours (4.5 days) to run. Results were saved into a file geodatabase that ended up being 12 GB in size. The geocoding rate started out at 10,000 per hour, but then steadily increased to as much as 900,000 per hour, averaging about 500,000 per hour for the duration. 99.4% of the addresses were matched.

Next, determining the census block group 2000 and 2010 FIPS codes for each address was necessary. ArcGIS has several ways to accomplish this, including the tools spatial join, identity, and intersect. The 2000 and 2010 block group polygon boundaries were copied from the ESRI Data and Maps datasets into the file geodatabase holding the geocoded addresses. Each block group file has just over 200,000 polygons. The spatial join, identity, and intersect tools were run on the addresses and 2000 block groups, and each time ArcGIS threw an "Out of Memory" error. Having run into this error before (ArcGIS running out of memory when attempting analyses with datasets numbering in the millions), a simple python script (included in "Python Script" section below) was written to process a subset of the full dataset each subset represented a single US State. Although this approach was extremely easy to implement, it was not so efficient due to the long processing time of roughly 20 hours of processing time per state.

Therefore we turned to a solution using the PostgreSQL 9.2 enterprise level database able to do spatial analyses using the PostGIS 2.1 extension. Importing the addresses and census block group polygons into PostgreSQL took 30 hours. Processing the block group 2000 and 2010 determination for all 53.1 million address locations using the PostGIS "Intersects" command took 50 hours. See the "PostgreSQL workflow" section below, where each command is listed.

  • While ArcGIS 10.2 was capable of geocoding 53.1 million addresses, it ran out of memory when trying to perform point in polygon determination both with and without the use of scripting in a file geodatabase format. This is not to say this task is impossible in ArcGIS. Some other things to try would be 1) Using a machine with more RAM, 2) Trying different python scripts in a Hadoop framework, 3) Explore using Python multithreading capability, Connect to the data in PostgresSQL from ArcGIS.
  • PostgreSQL with the PostGIS extension was able to efficiently handle this large data analysis task.
  • Having the access to and ability to use multiple GIS is often beneficial when tackling difficult spatial analyses.

import arcpy
from arcpy import env
env.overwriteOutput = True
env.workspace = r"

arcpy.MakeFeatureLayer_management("z01_diff", "test_lyr")
arcpy.MakeFeatureLayer_management("blkgrp2000", "blkgrp2000_lyr")
arcpy.MakeFeatureLayer_management("blkgrp2010", "blkgrp2010_lyr")
f = open('workfile_5.txt', 'w')
f.write("ID,"+ "blk2000," + "blk2010 ")
for a in range(1, 662690):
query = "OBJECTID test_lyr", "NEW_SELECTION", query)
arcpy.SelectLayerByLocation_management ("blkgrp2000_lyr", "INTERSECT", "test_lyr")
arcpy.SelectLayerByLocation_management ("blkgrp2010_lyr", "INTERSECT", "test_lyr")
with arcpy.da.SearchCursor("blkgrp2000_lyr", ("FIPS")) as cursor:
for row in cursor:
blk2000 = row[0]
with arcpy.da.SearchCursor("blkgrp2010_lyr", ("FIPS")) as cursor:
for row in cursor:
blk2010 = row[0]
f.write(str(a) + "," + blk2000 + "," + blk2010 + " ")

#The following part is done in terminal
#import addresses, and census block groups from file geodatabase into postgres
ogr2ogr -overwrite -f "PostgreSQL" PG:"host=localhost user=postgres dbname=mypgdb password=postgres" "

/53Milliondata.gdb" "Geocoding_Result"
ogr2ogr -overwrite -f "PostgreSQL" PG:"host=localhost user=postgres dbname=mypgdb password=postgres" "

/Census.gdb" "blkgrp2010"
ogr2ogr -overwrite -f "PostgreSQL" PG:"host=localhost user=postgres dbname=mypgdb password=postgres" "

#connect to the database
#create (spatial) index (optional as importing will automatically build index) to increase performance
CREATE INDEX geocoding_result_gist
ON geocoding_result
USING GIST (wkb_geometry)

#Intersection for 2010 boundary
SELECT geocoding_result.*,blkgrp2010.fips
FROM geocoding_result,blkgrp2010
WHERE ST_Intersects(geocoding_result.wkb_geometry,blkgrp2010.wkb_geometry)

#Rename new field "fips" to fips 2010
ALTER TABLE geofipsall RENAME COLUMN fips TO fips2010

#Intersection for 2000 boundary
CREATE TABLE geofipsall AS
SELECT geofips.*,blkgrp2000.fips
FROM geofips,blkgrp2000
WHERE ST_Intersects(geofips.wkb_geometry,blkgrp2000.wkb_geometry)

#Rename new field "fips" to fips 2000
ALTER TABLE geofipsall RENAME COLUMN fips TO fips2000

#Add Column fips2010, fips2000 to geocoding_result
ALTER TABLE geocoding_result ADD COLUMN fips2010 varchar(12)
ALTER TABLE geocoding_result ADD COLUMN fips2000 varchar(12)

#Select non-geocoded results
SELECT * FROM geocoding_result WHERE status='U'

#Union two tables together
CREATE TABLE geocoding_final_result AS (
SELECT * FROM geofipsall
SELECT * FROM ustatus)

#export result to csv
COPY geocoding_final_result(loc_name,status,x,y,match_addr,altpatid,address,city,state,zip_code,fips2010,fips2000)
TO 'C:Tempgeocoding_final_result_new.csv' DELIMITER ',' CSV HEADER

#export a sample result for reviewing
COPY (SELECT loc_name,status,x,y,match_addr,altpatid,address,city,state,zip_code,fips2010,fips2000
FROM geocoding_final_result LIMIT 1000)
TO 'C:Tempgeocoding_final_result_1000.csv' DELIMITER ',' CSV HEADER

Geocoding by Jeff Blossom, PostgresSQL by Zhenyang Hua, Python by Giovanni Zambotti.

Geocoding block using ArcGIS Desktop? - Geographic Information Systems

(Version 1/13/00)

Arthur Getis, John Gartin, Richard Wright, Pat Drummy, Wilpen Gorr, Keith Harries, Peter Rogerson, and Debra Stoe


A number of researchers have documented the usefulness of computer generated maps (CGM) in developing crime fighting capability (85% of police departments taking part in a recent survey said that CGM are valuable tools Mamalian et al. 1999). Unfortunately, many law enforcement agencies have yet to take advantage of GIS, of which CGM are a part.

Only 13 percent of the respondents to a National Institute of Justice survey of law enforcement departments in the United States reported using any computerized mapping at all (Mamalian et al. 1999). The majority of users are large departments, with more than 100 police officers. Those that employ computerized maps use them primarily for geo-coding and mapping offenses (automated pin maps), calls for service, and stolen vehicle recovery. The maps are also used for resource allocation decisions and to inform local communities about criminal activity. Although clusters of crime (hot spots) are most often identified visually, about twenty-five percent of the large departments use various software packages for cluster identification, and of these very few use statistical and/or spatial analysis.


Fortunately, the country is well served by a variety of agencies that promote the use of technology in crime prevention. Most of these agencies work with a variety of local law enforcement interests. At the national level, the Office of Administration in the Department of Justice (DOJ) houses a Geographic Information Systems and Spatial Crime Analysis System. The DOJ supports a National Institute of Justice Crime Mapping Research Center and a Crime Mapping and Analysis Program. In addition, the Federal Bureau of Investigation has extensive computer mapping capabilities.

National level initiatives also include National Community Demonstration sites. The goals of these projects focus on informed decision making at the community level, improve land and resource use, transfer data between the Federal Government and communities, and have communities contribute data sets to national data clearinghouses. Currently, the largest city participating in the project is Baltimore. In addition, Vice-President Gore has spoken out on the promise of the new technologies in the fight against crime.

Many states support crime mapping endeavors. Most prominent is the Illinois Criminal Justice Authority, which produces and disseminates perhaps the most widely used crime/cluster analysis package: Spatial and Temporal Analysis of Crime (STAC). At the local level, a number of police departments lead the nation in the use of computer mapping of crime and in crime analysis. Among large cities, New York with its CompStat system and Chicago with its ICAM2 system are well known. The Baltimore County Police Department currently works with the DOJ on a regional crime analysis GIS (RCAGIS). San Diego employs an elaborate and detailed data gathering system (ARJIS) and uses both in-house and third party analytical routines based on ARCINFO/ARCVIEW mapping software. In addition, smaller communities such as Charlotte-Mecklenburg, North Carolina, and Ada County, Idaho, use extensive crime mapping systems.

A number of technologically oriented firms and universities conduct research in crime mapping. Environmental Systems Research Institute (ESRI), the makers of ARC products, financially supports crime analysis research both in-house and outside. Several smaller firms such as, the Omega Group and GeoSpatial Technologies, are developing systems that they market to police departments around the country. An International Association of Crime Analysts is based at Tiffin University in Ohio. The University of Denver has a crime mapping and analysis program. Perhaps most imaginative are the crime analysis and mapping tutorials used at the Heinz School of Public Policy and Management at Carnegie Mellon University. Several universities have received large grants from NIJ for work in this area including the University at Buffalo and Temple University.

The Federal Government supports National Community Demonstration sites. The goals of these projects focus on informed decision making at the community level, improve land and resource use, transfer data between the Federal Government and communities, and have communities contribute data sets to national data clearinghouses. Currently, the largest city participating in the project is Baltimore. In addition, Vice-President Gore has spoken out on the promise of the new technologies in the fight against crime.


For this section, the panel considered crime analysis in the context of the already documented UCGIS research challenges (see Research Challenges White Paper at the UCGIS web page). We asked ourselves: How does the application area called crime analysis relate to these challenges? The purpose of this section is to identify the interface between the fundamental research interests of UCGIS and the needs and characteristics of the crime mapping community. Only those UCGIS research challenges that are relevant to crime analysis are discussed.

Police departments need large amounts of detailed locational data on: crime type, site of crime, perpetrator address, victim address, and the exact nature of the crime. Most departments have now developed or obtained some sort of computerized data base management system to record this information. If the data are geo-referenced accurately, it is possible to create maps showing many aspects of crime patterns. It is especially helpful if accurate street maps are available for the GIS systems. In addition, there is a need for zoning, land use, terrain, and census tract maps.

The major technical problems in this area involve the need to:

  1. Develop systems that make it possible to map combinations of information, such as census data and crime patterns
  2. Match different sources of data collected at different times and scales
  3. Find ways to share data between departments, agencies and communities and

Reduce barriers to data ownership.

In general, the goal is to standardize and integrate data. National standards for information recording, with regard to both maps and to non-mappable information, would help in this endeavor. At the least, there is a need for a strong effort to reduce inconsistencies among cooperating law enforcement and non-law enforcement departments.

Since a myriad of police and non-police reporting systems are currently in use, the dissemination of their information can only be confusing and possibly misunderstood. It would be helpful to move toward having a core location storage of regional or national crime and related data. Several agencies already are moving in this direction. For example, the ARJIS system, used by various agencies in San Diego County, stores police reports for all police departments within the county. It is the primary repository of information used by the San Diego Police Department. These data are easily transferred into a GIS for use on desktop computers. Because crime is not greatly hindered by jurisdictional boundaries, it is important that data from adjoining cities and suburbs can be integrated easily. On the negative side, the NCIC system in use for national criminal checks cannot be used in a GIS. In general, the existence of different reporting systems for each police department stands in the way of distributed computing.

Many police officials want to have available effective representations of crime location patterns. For analytical and decision making purposes, useful representations of hot spots and other locational information are needed. Simulations are becoming more important as visualization techniques become more sophisticated. Care should be given to using logical formats for representations so that the chances of misinterpretation are minimized. New technology that features 3-D representations would be helpful to police, especially in the study of crime patterns in large buildings and underground structures. In general, geographic presentation is an area with vast potential for developing new types of maps and charts that can aid police authorities.

Cognition of Geographic Information

Information is understood and used in different ways by individuals and interest groups. For example, the police may interpret a particular map differently than do community leaders or business people. Viewpoints are conditioned by the objectives of the different interest groups. The problem boils down to the question: Who needs what and in what format? Spatial decision support systems must be developed that allow map users to find common ground for the solution of crime related problems.

This is the joint problem of integrating spatial information taken from a variety of map scales and finding ways to analyze data in some consistent fashion when scales are different. Reducing all information to the same scale is clearly not the solution to these problems. Depending on the make-up of their region of jurisdiction, police departments need maps and attendant information at a variety of scales. Federal, state, local jurisdictional areas can overlap with other jurisdictions, creating a problem of who stores and has access to data. Multi-scale analyses and smooth scale change technology are needed to move easily from one scale to another.

Spatial Analysis in a GIS Environment

This is a critical challenge. Currently, spatial analysis programs and GIS systems are poorly integrated. Fortunately, this is a subject to which a considerable amount of attention has been given in recent years. The principal question is: What types of analytical routines can be developed within a GIS environment that will help answer societal questions about the degree and spatial and temporal occurrence of crime?

There is a need to improve analytical packages so that they integrate easily into mapping systems. Cluster or hot spot analysis is currently one area of concern. Ellipses or circles surrounding hot spots are of only limited value. Police need to know the exact dimensions of hot spots in time and space and to evaluate them in terms of previous patterns or non-crime variables. They need to identify statistically significant patterns.

Currently, a number of packages in the early stages of development attempt to analytically explore crime data. Very promising is the Spatial Crime Analysis System (SCAS), a Department of Justice Arc View-based GIS application designed to enable police departments to perform spatial analysis and mapping. Others include: STAC (mentioned above), Geographic Analysis Machine (GAM), CrimeView (the Omega Group), CrimeMapper (GeoSpatial Technologies). Other packages, not geared specifically for crime analysis, have the capability to analytically identify geo-referenced clustering. Some of these are SpaceStat (obtain from BioMedWare), BioMedWare (Ann Arbor), Point Pattern Analysis (San Diego State University), and InfoMap (University of Lancaster).

The Future of the Spatial Information Infrastructure

The main concern here is to consider the possibility of links among data storage, crime analysis, and daily police activities in a real-time environment. Questions of information access by police and the public and the technology that integrates information need to be answered for future ease of use. With technology changing at a rapid pace, how can a spatial information infrastructure be developed that has lasting usefulness? One understandable difficulty is the privacy or security issue, mentioned below, which inhibits the use of such information as exact addresses thus distorting what otherwise might be a true representation of the spatial distribution of crime.

Uncertainty in Geographic Data and GIS-based Analysis

The problem of data quality has been an issue in the past and will continue to be in the future. All analyses are based on data. If police officers record data poorly or citizens give faulty reports to the police, any map or analysis based on the data will be suspect. In addition, representing the address of a large building spread over many acres as a point or a giving an arbitrary address for a crime committed in a large open space may lead to errors in analysis. Efforts should be made to insure that great care and attention are given to the development of accurate primary databases.

There are a host of issues under this heading. Perhaps the most important at this time is the movement to encourage community partnerships with the police. GIS can play a role by facilitating the development of the timely and accurate visual nature of crime for the combined use of police and concerned civilians. GIS can support crime prevention efforts by illustrating the impact of crime on the community and of the impact of community efforts on crime. GIS can facilitate informed decision making on criminal activity and prevention. It can be useful for elevating interest and awareness of crime problems. GIS can be instrumental in helping society to learn what the linkages are between crime and other factors distributed in space, such as unemployment or drug use. By transferring local information to larger bodies such as state and federal government, the community can assist national efforts to reduce criminal activity. Privacy and information dissemination are issues the larger society must deal with when it becomes clear that our desire to protect citizens may be in conflict with constitutional guarantees of freedom. Issues of security, sensitivity, confidentiality, responsibility, reliability, data sharing, and data ownership are all of great societal importance.


Spatial Forecasting, Prediction and Projection

There is a need to identify the natural fluctuations in crime levels, to recognize crime types by season, day versus night, weekday versus weekend, all done spatially. Surveillance statistics must be developed so that leading indicators or trends in crime occurrences can be monitored in a meaningful way. In addition, crime needs to be placed into a space-time format, since these two basic dimensions are critical for understanding the subject.

Verification, Validation, and Evaluations of Research and Operations

GIS can be used to evaluate the effectiveness of police operations. Meta-types of analysis can be used to compare and contrast results found among different academic studies studying similar phenomena. Since so much of crime research is done by local authorities, there needs to be a clearinghouse for crime research so that duplication of effort is minimized. It would be useful if we knew precisely which measures are the most successful at evaluating crime analyses. Furthermore, study results need to be disseminated from readily available venues.

Computer Power Versus Data Set Size

As data sets become larger because of the greater ability to record criminal activity and the greater interest and competence in considering crime in detail, the GIS community will run up against the problem of the capability of hardware and software to handle extremely large data sets. Although the computers may have the capacity to handle the current data sets, there still is the problem of computer congestion. While one problem is running, the computer may not be available for other work.

Mapping the Causation of Crime

In addition to mapping crime, it would be useful to consider mapping what can be considered the causes of crime. Mapping low income, low educational levels, juvenile delinquency, unemployment, and so forth can be enormously helpful for crime analysis. The question of the relevant crime related variables and their spatial representation is also an issue. Can mapping domestic abuse, for example, help in crime prevention?


In the area of crime understanding and prevention, there are a number of issues related to having an informed populace, including law enforcement personnel, use GIS technology. Currently, there are a host of new technologies available for delivering GIS education. The most promising of these with regard to crime analysis is that produced by Wilpen Gorr at Carnegie Mellon University (Gorr and Kurland 1999). The program is built around the advanced use of GIS in a police data environment. Internet modules have been developed. This fits nicely into distance learning and CD ROM tutorial pedagogy discussed in the on-line white papers of the UCGIS educational challenges committee. Gorr's program contains videos and CDs with transcripts and full search capabilities.

Most crime analysis GIS users work in large metropolitan departments. With the declining cost of powerful desktop machines and affordable software, however, we can expect that increasingly police departments of all sizes will be engaged in this type of work. New low cost training for using GIS is now becoming available, but specific crime analysis oriented workshops are still few and far between. There are problems with regard to finding and retaining personnel who are familiar with modern data retrieval, software use, and technology maintenance techniques. More web sites with white papers and links to available data and curricula are needed.

Perhaps most important at this juncture is the need to find ways to share information, data, and technology. The problem of the difficult transjurisdiction interface looms as a formidable barrier for small as well as large departments, but particularly so for poorly-funded small departments. National and state grants should be made available so that personnel in small departments can be trained in geographical information sciences. There should be strong governmental support for data sharing and storage between agencies.

Alternative Designs for Curriculum Content and Evaluation

It would be helpful if GIS curricula chose crime (as in the Carnegie Mellon University example) as one possible base for learning. GIS curricula could include a course that focuses on the use of GIS in a crime lab or police beat environment. This same idea can be extended to community development applications. Police officers, analysts, and citizens could be schooled in GIS use, mapping, projections, relational databases, address mapping, feature extraction, and crime analysis case studies. The training curricula should be user needs driven. For example, police officers could gain classroom type experience in choropleth crime change mapping, pin mapping, bringing together crime diagnostic data, and studying site profile information. The crime analyst can learn about data warehouses, aggregate crime codes, land use mapping, trend statistics and graphics, program evaluation, districting, etc. Detectives would study hot spot analyses, serial criminal patterns, variable linkage analysis, etc. Citizens might better learn how police departments are organized, how information is gathered and entered into data bases, about GIS capabilities, evaluating crime interventions, forecasting criminal activity, and detecting significant changes in crime patterns. Clearly, there are a number of useful pedagogical paths that could be taken.

Professional GIS Education Programs

We recognize that most GIS users receive their GIS training on the job. How can we insure that there are qualified personnel in the work environment who are able to effectively train personnel. Training and certificate programs should be made available in colleges and universities as part of their outreach activities to increase the competence of public employees in this area.

Research-based Graduate GIS Education

Graduate education in GIS crime analysis would contribute further support and advancement of the field. It would provide qualified employees in crime analysis units. There would be an upgrading of the standards for crime analysis activities. It would create an environment that generates research in new approaches and techniques that would improve analyses, user-system interfaces, and general crime theory as well as in the investigation into the effective application of new technology and methods.

There is a strong need to link universities with local police departments to better utilize research resources in both environments. A symbiotic relationship would go a long way toward bringing the fruits of the university research experience into the hands of those faced with the practical everyday requirements of law enforcement personnel.

Accreditation and Certification

Still an unresolved issue within the UCGIS is the idea of accreditation and certification in the area of GIS. Currently, forensics personnel in crime analysis laboratories must be certified. The pressure for such formalization usually comes from the official needs of courts of law. Should GIS crime analysts be certified? Should GIS training programs be accredited? These are questions that are currently being debated.


Benefits accrue both to those who engage in crime analysis and to the users of the fruits of the analysis when they are able to work together. Relationships between universities and police departments open the door for many worthwhile projects and associations. When what might be called "research culture" interacts with "police culture" which in turn responds to "public culture," can this result in practical solutions to many crime prevention problems? In addition, it is helpful for the public to be made fully aware of the activities of the analysts and practitioners so that they can appreciate the ways in which GIS and other technologies can improve community life.

A number of outcomes can result from the use of GIS in a crime analysis environment. Police departments find that they can improve their efficiency in the application of resources and more easily generate improved proposals for resource requests. Requiring better data for GIS work will add to the strength of proposals for public support. Good quality data and analysis encourage community leaders to support police operations in neighborhoods, and enable police to internally investigate their own policies for effectiveness and efficiency. In addition, the new technologies make possible changes in police department actions with regard to patterns of crime discerned by GIS crime analysis efforts. Better understanding of patterns of crime will result in more successful police outreach activities.


At this juncture, the major thrust in crime control and prevention is to incorporate appropriate advanced statistical techniques into GIS for crime analysis. Also, it is important to match the output of a GIS analysis with the needs of police and the communities they serve. Behind these needs is the critical area of meaningful data collection and organization. Much effort must be expended to develop appropriate geo-referenced data gathering systems and data base management systems. Concomitantly, it is important to improve accessibility to crime analysis education both in police departments and in universities. Another compelling need is for a central information contact that can be of assistance to police departments as they begin their GIS initiatives. They need to know start up procedures, what software to use, what are the costs, whether training is available, and so on. Currently, most police departments are at the mercy of the sales pitches of the various vendors.

The following bibliography was primarily gathered by Keith Harries, for which we are grateful. It contains items singularly associated with crime analysis research and items that combine crime analysis with GIS technology.

ArcGIS Performance Benchmarks

For good Service Optimization performance, the ArcGIS hosts should pass the following benchmark tests. Perform these tests after you have configured the ArcGIS services (see Configuring the Esri GIS Adapter). The cached map tiles and the ArcGIS routing cache must be fully prepared.

  • For a map request that returns a 500x500 pixel map at a scale (zoom) level of 14, the ArcGIS response time should be smaller than or equal to 7 seconds. The map request comprises several sub-requests for 256x256 map tiles.
  • For a routing request that returns travel time and distance, the ArcGIS response time should be smaller than or equal to 0.3 seconds. This includes complex routes having, for example, 12 turns and 50 km between locations.
  • Each instance of the ArcGIS routing service, running on a single CPU core, should process at least 5 routing requests per second.
  • For a geocoding request that returns matches for a full or partial address, the response time should be smaller than or equal to 0.2 seconds.
  • Each instance of the ArcGIS geocoding service, running on a single CPU core, should process at least 10 geocoding requests per second.

For potentially updated information about the performance benchmarks, see Prerequisites From GIS Vendor - SO Version 8.x.

If the benchmarks tests fail, consult with Esri about how to improve the performance.


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