This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

As a first step in understanding law enforcement agencies' use and knowledge of crime mapping, the Crime Mapping Research Center (CMRC) of the National Institute of Justice conducted a nationwide survey to determine which agencies were using geographic information systems (GIS), how they were using them, and, among agencies that were not using GIS, the reasons for that choice. Data were gathered using a survey instrument developed by National Institute of Justice staff, reviewed by practitioners and researchers with crime mapping knowledge, and approved by the Office of Management and Budget. The survey was mailed in March 1997 to a sample of law enforcement agencies in the United States. Surveys were accepted until May 1, 1998. Questions asked of all respondents included type of agency, population of community, number of personnel, types of crimes for which the agency kept incident-based records, types of crime analyses conducted, and whether the agency performed computerized crime mapping. Those agencies that reported using computerized crime mapping were asked which staff conducted the mapping, types of training their staff received in mapping, types of software and computers used, whether the agency used a global positioning system, types of data geocoded and mapped, types of spatial analyses performed and how often, use of hot spot analyses, how mapping results were used, how maps were maintained, whether the department kept an archive of geocoded data, what external data sources were used, whether the agency collaborated with other departments, what types of Department of Justice training would benefit the agency, what problems the agency had encountered in implementing mapping, and which external sources had funded crime mapping at the agency. Departments that reported no use of computerized crime mapping were asked why that was the case, whether they used electronic crime data, what types of software they used, and what types of Department of Justice training would benefit their agencies.

The Tempe Police Department prides itself in its continued efforts to reduce harm within the community and is providing this dataset on hate crime incidents that occur in Tempe.The Tempe Police Department documents the type of bias that motivated a hate crime according to those categories established by the FBI. These include crimes motivated by biases based on race and ethnicity, religion, sexual orientation, disability, gender and gender identity.The Bias Type categories provided in the data come from the Bias Motivation Categories as defined in the Federal Bureau of Investigation (FBI) National Incident-Based Reporting System (NIBRS) manual, version 2020.1 dated 4/15/2021. The FBI NIBRS manual can be found at https://www.fbi.gov/file-repository/ucr/ucr-2019-1-nibrs-user-manua-093020.pdf with the Bias Motivation Categories found on pages 78-79.Although data is updated monthly, there is a delay by one month to allow for data validation and submission.Information about Tempe Police Department's collection and reporting process for possible hate crimes is included in https://storymaps.arcgis.com/stories/a963e97ca3494bfc8cd66d593eebabaf.Additional InformationSource: Data are from the Law Enforcement Records Management System (RMS)Contact: Angelique BeltranContact E-Mail: angelique_beltran@tempe.govData Source Type: TabularPreparation Method: Data from the Law Enforcement Records Management System (RMS) are entered by the Tempe Police Department into a GIS mapping system, which automatically publishes to open data.Publish Frequency: MonthlyPublish Method: New data entries are automatically published to open data. Data Dictionary

The Regional Crime Analysis GIS (RCAGIS) is an Environmental Systems Research Institute (ESRI) MapObjects-based system that was developed by the United States Department of Justice Criminal Division Geographic Information Systems (GIS) Staff, in conjunction with the Baltimore County Police Department and the Regional Crime Analysis System (RCAS) group, to facilitate the analysis of crime on a regional basis. The RCAGIS system was designed specifically to assist in the analysis of crime incident data across jurisdictional boundaries. Features of the system include: (1) three modes, each designed for a specific level of analysis (simple queries, crime analysis, or reports), (2) wizard-driven (guided) incident database queries, (3) graphical tools for the creation, saving, and printing of map layout files, (4) an interface with CrimeStat spatial statistics software developed by Ned Levine and Associates for advanced analysis tools such as hot spot surfaces and ellipses, (5) tools for graphically viewing and analyzing historical crime trends in specific areas, and (6) linkage tools for drawing connections between vehicle theft and recovery locations, incident locations and suspects' homes, and between attributes in any two loaded shapefiles. RCAGIS also supports digital imagery, such as orthophotos and other raster data sources, and geographic source data in multiple projections. RCAGIS can be configured to support multiple incident database backends and varying database schemas using a field mapping utility.

Law Enforcement StructuresThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey (USGS), displays police and prison landmarks in the U.S. Per the USGS, "Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations."Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Law Enforcement) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: USGS National Structures Dataset - USGS National Map Downloadable Data CollectionGeoplatform: USGS National Structures Dataset - USGS National Map Downloadable Data CollectionFor more information, please visit: The National MapFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

The Police Stations layer shows the point locations of law enforcement and sheriff offices in Massachusetts, covering local, county and state jurisdictions. The Massachusetts Emergency Management Agency (MEMA) GIS Program in cooperation with the Regional Planning Agencies and participating communities created the original data as part of the development of Homeland Security Data Layers. MassGIS has since incorporated updates into the data.The features represented include municipal police stations and Massachusetts State Police barracks. Although sheriffs are not technically charged with the same law enforcement tasks as local and state police, county sheriff headquarters are also included in this layer. The duties of the sheriffs include the management and operation of regional correctional systems and transportation of prisoners, service of judicial process and delivery of legal documents needed to support the operation of the courts, community policing, running various outreach services, and the enforcement of laws enacted for the public safety, health and welfare of the people. Not included in this layer are Environmental Police, campus police and various state and federal level law enforcement locations.Map service also available.More details...

Feature layer showing the locations of Sworn Law Enforcement Officer Locations in California.This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. This also applies to mounted police in New Mexico. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection in the United States and its territories. This dataset is comprised completely of license free data. At the request of NGA, FBI entities are intended to be excluded from this dataset, but a few may be included. The HSIP Freedom Law Enforcement dataset and the HSIP Freedom Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. With the merge of the Law Enforcement and the Correctional Institutions datasets, the HSIP Themes and NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard HSIP fields that TGS populated. Double spaces were replaced by single spaces in these same fields. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 12/07/2004 and the newest record dates from 09/10/2009.Use Cases: Use cases describe how the data may be used and help to define and clarify requirements.1. An assessment of whether or not the total police capability in a given area is adequate. 2. A list of resources to draw upon in surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can help to determine those entities who are able to respond the quickest. 3. A resource for emergency management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for federal government events.

Public Safety GIS Software Market Outlook

According to our latest research, the Public Safety GIS Software market size reached USD 2.86 billion in 2024, demonstrating robust adoption across emergency response and law enforcement sectors worldwide. The market is experiencing significant momentum, driven by the imperative need for real-time geospatial intelligence in public safety operations. With a projected compound annual growth rate (CAGR) of 11.2% from 2025 to 2033, the market is forecasted to reach USD 7.36 billion by 2033. This remarkable expansion is fueled by increasing investments in digital transformation of public safety infrastructure, rising incidences of natural disasters, and the growing complexity of urban environments necessitating advanced GIS solutions.

One of the primary growth factors propelling the Public Safety GIS Software market is the escalating frequency and severity of natural and man-made disasters worldwide. As cities become more densely populated and climate change intensifies, the demand for sophisticated geospatial analysis tools to support disaster preparedness and response has surged. Public safety agencies are leveraging GIS software to map hazard zones, optimize evacuation routes, and allocate resources effectively in real time. This technological evolution enables a more proactive and coordinated approach to emergency management, significantly reducing response times and enhancing situational awareness for first responders. The integration of GIS with IoT sensors, drones, and real-time data feeds further amplifies its value, providing a comprehensive operational picture that is critical for life-saving interventions.

Another significant driver is the increasing adoption of cloud-based deployment models, which are transforming the accessibility and scalability of GIS solutions for public safety. Cloud-based GIS platforms offer cost-effective, flexible, and secure options for agencies of all sizes, enabling seamless data sharing and collaboration across departments and jurisdictions. This democratization of geospatial intelligence is particularly beneficial for smaller municipalities and rural areas that previously lacked the resources for advanced on-premises systems. Enhanced interoperability with other public safety technologies, such as computer-aided dispatch (CAD) and records management systems (RMS), is further accelerating market growth. The ongoing digitalization of public safety processes, coupled with supportive government policies and funding initiatives, is expected to sustain the market’s upward trajectory over the forecast period.

The growing emphasis on crime analysis and predictive policing is also contributing to the expansion of the Public Safety GIS Software market. Law enforcement agencies are increasingly utilizing GIS-driven analytics to identify crime hotspots, forecast criminal activity, and allocate patrol resources more efficiently. The ability to visualize and analyze spatial patterns of crime in conjunction with demographic, socioeconomic, and environmental data enhances strategic decision-making and supports community-oriented policing initiatives. Furthermore, advancements in artificial intelligence and machine learning are enabling more sophisticated geospatial modeling, empowering agencies to anticipate threats and deploy preventive measures proactively. This shift toward data-driven policing is fostering greater trust and transparency between law enforcement and the communities they serve.

From a regional perspective, North America continues to lead the global Public Safety GIS Software market in terms of both adoption and innovation. The presence of technologically advanced public safety infrastructure, high levels of government investment, and a strong ecosystem of GIS vendors and solution providers have made the region a pioneer in integrating geospatial intelligence into emergency response workflows. Europe is also witnessing substantial growth, driven by stringent regulatory mandates and cross-border collaboration on disaster management. Meanwhile, Asia Pacific is emerging as a high-growth market, fueled by rapid urbanization, increasing vulnerability to natural disasters, and ambitious smart city initiatives. Latin America and the Middle East & Africa are gradually catching up, with growing recognition of the value of GIS in enhancing public safety outcomes.

Component Analysis

The Component segment of the Pu

NOTE: This dataset is an older dataset that we have removed from the SGID and 'shelved' in ArcGIS Online. There may (or may not) be a newer vintage of this dataset in the SGID.NOTE: This dataset holds 'static' data that we don't expect to change. We have removed it from the SDE database and placed it in ArcGIS Online, but it is still considered part of the SGID and shared on opendata.gis.utah.gov.

This dataset contains point locations for all publicly identified sites and office locations including headquarters, station, field office and investigative unit locations. This dataset was created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO), MPD and participating D.C. government agencies. Facilities and offices were obtained from MPD's Office of Corporate Communications, through interviews with MPD's Criminal Intelligence, and Tactical Crime Analysis Unit and through site surveys conducted by DC GIS staff.

The local law enforcement locations feature class/ shapefile contains point location and tabular information pertaining to a wide range of law enforcement entities in the United States. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Census of State and Local Law Enforcement Agencies (CSLLEA). Unlike the previous version of this dataset, published in 2009, federal level law enforcement agencies are excluded from this effort. Data fusion techniques are utilized to synchronize overlapping yet disparate source data. The primary sources for this effort are the DOJ-BJS CSLLEA from 2008 and the previously mentioned 2009 feature class from Homeland Security Infrastructure Foundation-Level Data (HIFLD). This feature class contains data for agencies across all 50 U.S. states, Washington D.C. and Puerto Rico.

Reporting Districts form the basis of crime reporting, organizing crimes into specific areas.

Chicago Police district station locations. To view or use these files, compression software and special GIS software, such as ESRI ArcGIS, is required. To download, right-click the "Download" link above and choose "Save link as."

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 06/27/2006 and the newest record dates from 10/22/2009

Last update: 01/12/2024This data was developed for the Utah Department of Public Safety Bureau of Investigations for use in planning operations throughout the State. It indicates which law enforcement agency has responsibility in a specific area. Identification of local police departments was obtained from the Utah Chiefs of Police Association and from associated 911 dispatch centers. Boundaries for the police departments are the current municipal boundaries in SGID. Periodic boundary boundary changes will be made as municipal boundaries change and responsibilities of city police departments will be updated as they become known. Sheriffs Office boundaries are current county boundaries in SGID minus local police department boundaries.More information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/society/public-safety/

The dataset contains polygons representing of MPD Police Sectors, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. In 2017 the Metropolitan Police Department formed an additional operational geographic layer called Sector. The Sector model brings additional management accountability to districts and allows for faster dispatch, lower response times, and improved service to the community. Sectors are made up of multiple Police Service Areas (PSAs) and are headed by a Captain. Please note that PSA is still an active operational model used by MPD; Sector is an additional layer between the PSA and District levels.2019 Boundary Changes:Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, economic development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019.On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase.

   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.


   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Real-Time Crime Mapping Market Outlook

According to our latest research, the global Real-Time Crime Mapping market size reached USD 8.1 billion in 2024, with a robust growth driven by increasing adoption of advanced analytics and digital mapping technologies. The market is expected to expand at a CAGR of 13.4% from 2025 to 2033, reaching a projected value of USD 25.3 billion by 2033. This growth is propelled by the rising need for efficient crime prevention, rapid incident response, and the integration of AI-driven solutions in public safety infrastructure worldwide.

One of the primary growth factors for the Real-Time Crime Mapping market is the increasing demand for proactive public safety measures. Law enforcement agencies across the globe are prioritizing digital transformation to improve their crime response times and predictive policing capabilities. The integration of real-time data analytics with geographic information systems (GIS) allows agencies to visualize crime hotspots, deploy resources more efficiently, and make data-driven decisions. Furthermore, the surge in urbanization and the complexity of modern cities have necessitated more sophisticated surveillance and incident management systems, driving the adoption of real-time crime mapping solutions.

Another significant driver is the technological advancements in artificial intelligence, machine learning, and big data analytics. These technologies have revolutionized the way crime data is captured, analyzed, and presented. Real-time crime mapping platforms now offer predictive analytics, automated alerts, and seamless integration with other law enforcement databases. This has enabled agencies to not only map current incidents but also anticipate potential criminal activities and prevent them before they occur. The continuous innovation in cloud-based solutions and mobile applications further enhances accessibility and usability, making these tools indispensable for both government and commercial sectors.

The growing emphasis on community engagement and transparency has also contributed to the expansion of the Real-Time Crime Mapping market. Public-facing crime mapping portals empower citizens with timely information about incidents in their neighborhoods, fostering greater trust in law enforcement agencies. Additionally, the rise of smart city initiatives and increased investments in public safety infrastructure by governments worldwide have created a fertile environment for market growth. These initiatives often include the deployment of integrated surveillance, emergency response, and data sharing platforms, all of which rely heavily on real-time crime mapping technologies.

From a regional perspective, North America continues to dominate the Real-Time Crime Mapping market, accounting for the largest share in 2024. This is attributed to the presence of advanced law enforcement infrastructure, high adoption rates of digital technologies, and substantial government funding for public safety projects. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by rapid urbanization, increasing crime rates, and growing investments in smart city and surveillance projects. Europe also remains a significant market, with countries focusing on modernizing their public safety systems and enhancing cross-border crime data sharing. Latin America and the Middle East & Africa are gradually catching up, supported by rising awareness and international collaborations in crime prevention.

Component Analysis

The component segment of the Real-Time Crime Mapping market is categorized into software, hardware, and services, each playing a pivotal role in the ecosystem. Software solutions form the backbone of real-time crime mapping systems, encompassing GIS platforms, analytics engines, and user interfaces. These solutions enable the collection, processing, and visualization of crime data in real time, allowing law enforcement agencies to generate actionable insights.

Coronavirus (COVID-19): Resources for Law Enforcement (National Police Foundation)._Communities around the world are taking strides in mitigating the threat that COVID-19 (coronavirus) poses. Geography and location analysis have a crucial role in better understanding this evolving pandemic.When you need help quickly, Esri can provide data, software, configurable applications, and technical support for your emergency GIS operations. Use GIS to rapidly access and visualize mission-critical information. Get the information you need quickly, in a way that’s easy to understand, to make better decisions during a crisis.Esri’s Disaster Response Program (DRP) assists with disasters worldwide as part of our corporate citizenship. We support response and relief efforts with GIS technology and expertise.More information...

CrimeMapTutorial is a step-by-step tutorial for learning crime mapping using ArcView GIS or MapInfo Professional GIS. It was designed to give users a thorough introduction to most of the knowledge and skills needed to produce daily maps and spatial data queries that uniformed officers and detectives find valuable for crime prevention and enforcement. The tutorials can be used either for self-learning or in a laboratory setting. The geographic information system (GIS) and police data were supplied by the Rochester, New York, Police Department. For each mapping software package, there are three PDF tutorial workbooks and one WinZip archive containing sample data and maps. Workbook 1 was designed for GIS users who want to learn how to use a crime-mapping GIS and how to generate maps and data queries. Workbook 2 was created to assist data preparers in processing police data for use in a GIS. This includes address-matching of police incidents to place them on pin maps and aggregating crime counts by areas (like car beats) to produce area or choropleth maps. Workbook 3 was designed for map makers who want to learn how to construct useful crime maps, given police data that have already been address-matched and preprocessed by data preparers. It is estimated that the three tutorials take approximately six hours to complete in total, including exercises.