https://www.icpsr.umich.edu/web/ICPSR/studies/3372/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3372/terms
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.
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.
https://www.icpsr.umich.edu/web/ICPSR/studies/2824/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2824/terms
CrimeStat III is a spatial statistics program for the analysis of crime incident locations, developed by Ned Levine and Associates under the direction of Ned Levine, PhD, that was funded by grants from the National Institute of Justice (grants 1997-IJ-CX-0040, 1999-IJ-CX-0044, 2002-IJ-CX-0007, and 2005-IJ-CX-K037). The program is Windows-based and interfaces with most desktop GIS programs. The purpose is to provide supplemental statistical tools to aid law enforcement agencies and criminal justice researchers in their crime mapping efforts. CrimeStat is being used by many police departments around the country as well as by criminal justice and other researchers. The program inputs incident locations (e.g., robbery locations) in 'dbf', 'shp', ASCII or ODBC-compliant formats using either spherical or projected coordinates. It calculates various spatial statistics and writes graphical objects to ArcGIS, MapInfo, Surfer for Windows, and other GIS packages. CrimeStat is organized into five sections: Data Setup Primary file - this is a file of incident or point locations with X and Y coordinates. The coordinate system can be either spherical (lat/lon) or projected. Intensity and weight values are allowed. Each incident can have an associated time value. Secondary file - this is an associated file of incident or point locations with X and Y coordinates. The coordinate system has to be the same as the primary file. Intensity and weight values are allowed. The secondary file is used for comparison with the primary file in the risk-adjusted nearest neighbor clustering routine and the duel kernel interpolation. Reference file - this is a grid file that overlays the study area. Normally, it is a regular grid though irregular ones can be imported. CrimeStat can generate the grid if given the X and Y coordinates for the lower-left and upper-right corners. Measurement parameters - This page identifies the type of distance measurement (direct, indirect or network) to be used and specifies parameters for the area of the study region and the length of the street network. CrimeStat III has the ability to utilize a network for linking points. Each segment can be weighted by travel time, travel speed, travel cost or simple distance. This allows the interaction between points to be estimated more realistically. Spatial Description Spatial distribution - statistics for describing the spatial distribution of incidents, such as the mean center, center of minimum distance, standard deviational ellipse, the convex hull, or directional mean. Spatial autocorrelation - statistics for describing the amount of spatial autocorrelation between zones, including general spatial autocorrelation indices - Moran's I , Geary's C, and the Getis-Ord General G, and correlograms that calculate spatial autocorrelation for different distance separations - the Moran, Geary, Getis-Ord correlograms. Several of these routines can simulate confidence intervals with a Monte Carlo simulation. Distance analysis I - statistics for describing properties of distances between incidents including nearest neighbor analysis, linear nearest neighbor analysis, and Ripley's K statistic. There is also a routine that assigns the primary points to the secondary points, either on the basis of nearest neighbor or point-in-polygon, and then sums the results by the secondary point values. Distance analysis II - calculates matrices representing the distance between points for the primary file, for the distance between the primary and secondary points, and for the distance between either the primary or secondary file and the grid. 'Hot spot' analysis I - routines for conducting 'hot spot' analysis including the mode, the fuzzy mode, hierarchical nearest neighbor clustering, and risk-adjusted nearest neighbor hierarchical clustering. The hierarchical nearest neighbor hot spots can be output as ellipses or convex hulls. 'Hot spot' analysis II - more routines for conducting hot spot analysis including the Spatial and Temporal Analysis of Crime (STAC), K-means clustering, Anselin's local Moran, and the Getis-Ord local G statistics. The STAC and K-means hot spots can be output as ellipses or convex hulls. All of these routines can simulate confidence intervals with a Monte Carlo simulation. Spatial Modeling Interpolation I - a single-variable kernel density estimation routine for producin
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
DISCLAIMER In May of 2021 the department’s method of Uniform Crime Reporting (UCR) transitioned from the Summary Reporting System (SSR) to the federally mandated National Incident-Based Reporting System (NIBRS). When comparing SSR and NIBRS data, the user should be aware of the differences between the two reporting methodologies. This dataset reflects reported incidents of crime (with the exception of sexual assaults, which are excluded by statute) that occurred in the City of Hartford from January 1, 2005 to May 18, 2021. Should you have questions about this dataset, you may contact the Crime Analysis Division of the Hartford Police Department at 860.757.4020 or policechief@Hartford.gov. Disclaimer: These incidents are based on crimes verified by the Hartford Police Department's Crime Analysis Division. The 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 Hartford 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 Hartford 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. The Hartford 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 Hartford or Hartford Police Department web page. The user specifically acknowledges that the Hartford 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 "Hartford Police Department", "Hartford Police", "HPD" or any colorable imitation of these words or the unauthorized use of the Hartford Police Department logo is unlawful. This web page does not, in any way, authorize such use.
Albuquerque, NM 2016 crimes. Created using ArcGIS Pro Geoprocessing tools (Create Space Time Cube, Emerging Hot Spot Analysis). Data obtained from the Albuquerque Police Department (see ABQ Data). Note: Composite of all crime types reported by APD.
An ArcGIS Dashboards app used by the public to explore statistical trends by crime type.
Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...
Alaska crime data from 2000 to present from the FBI Uniform Crime Reporting (UCR) program. Information includes data on both violent and property crime.The UCR Program's primary objective is to generate reliable information for use in law enforcement administration, operation, and management; over the years, however, the data have become one of the country’s leading social indicators. The program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.Source: US Federal Bureau of Investigation (FBI)This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: FBI UCR Program.
DISCLAIMER In May of 2021 the department’s method of Uniform Crime Reporting (UCR) transitioned from the Summary Reporting System (SSR) to the federally mandated National Incident-Based Reporting System (NIBRS). When comparing SSR and NIBRS data, the user should be aware of the differences between the two reporting methodologies. This dataset reflects reported incidents of crime (with the exception of sexual assaults, which are excluded by statute) that occurred in the City of Hartford from January 1, 2005 to May 18, 2021. Should you have questions about this dataset, you may contact the Crime Analysis Division of the Hartford Police Department at 860.757.4020 or policechief@Hartford.gov. Disclaimer: These incidents are based on crimes verified by the Hartford Police Department's Crime Analysis Division. The 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 Hartford 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 Hartford 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. The Hartford 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 Hartford or Hartford Police Department web page. The user specifically acknowledges that the Hartford 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 "Hartford Police Department", "Hartford Police", "HPD" or any colorable imitation of these words or the unauthorized use of the Hartford Police Department logo is unlawful. This web page does not, in any way, authorize such use.
DISCLAIMER In May of 2021 the department’s method of Uniform Crime Reporting (UCR) transitioned from the Summary Reporting System (SSR) to the federally mandated National Incident-Based Reporting System (NIBRS). When comparing SSR and NIBRS data, the user should be aware of the differences between the two reporting methodologies. This dataset reflects reported incidents of crime (with the exception of sexual assaults, which are excluded by statute) that occurred in the City of Hartford from January 1, 2005 to May 18, 2021. Should you have questions about this dataset, you may contact the Crime Analysis Division of the Hartford Police Department at 860.757.4020 or policechief@Hartford.gov. Disclaimer: These incidents are based on crimes verified by the Hartford Police Department's Crime Analysis Division. The 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 Hartford 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 Hartford 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. The Hartford 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 Hartford or Hartford Police Department web page. The user specifically acknowledges that the Hartford 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 "Hartford Police Department", "Hartford Police", "HPD" or any colorable imitation of these words or the unauthorized use of the Hartford Police Department logo is unlawful. This web page does not, in any way, authorize such use.
Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.
DISCLAIMER In May of 2021 the department’s method of Uniform Crime Reporting (UCR) transitioned from the Summary Reporting System (SSR) to the federally mandated National Incident-Based Reporting System (NIBRS). When comparing SSR and NIBRS data, the user should be aware of the differences between the two reporting methodologies. This dataset reflects reported incidents of crime (with the exception of sexual assaults, which are excluded by statute) that occurred in the City of Hartford from January 1, 2005 to May 18, 2021. Should you have questions about this dataset, you may contact the Crime Analysis Division of the Hartford Police Department at 860.757.4020 or policechief@Hartford.gov. Disclaimer: These incidents are based on crimes verified by the Hartford Police Department's Crime Analysis Division. The 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 Hartford 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 Hartford 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. The Hartford 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 Hartford or Hartford Police Department web page. The user specifically acknowledges that the Hartford 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 "Hartford Police Department", "Hartford Police", "HPD" or any colorable imitation of these words or the unauthorized use of the Hartford Police Department logo is unlawful. This web page does not, in any way, authorize such use.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The City of Ferndale uses the service CrimeMapping.com to provide near-live mapping of local crimes, sorted by category. Our goal in providing this information is to reduce crime through a better-informed citizenry. Crime reports older than 180 days can be accessed in this data set. For near-live crime data, go to crimemapping.com. A subset of this historic data has also been geocoded to allow for easy analysis and mapping in a different data set.
The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on communitycrimemap.comData Dictionary: Field Name Field Description Incident Number the number associated with either the incident or used as reference to store the items in our evidence rooms Date Reported the date the incident was reported to LMPD Date Occurred the date the incident actually occurred Badge ID Badge ID of responding Officer Offense Classification NIBRS Reporting category for the criminal act committed Offense Code Name NIBRS Reporting code for the criminal act committed NIBRS_CODE the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/view NIBRS Group hierarchy that follows the guidelines of the FBI National Incident Based Reporting System Was Offense Completed Status indicating whether the incident was an attempted crime or a completed crime. LMPD Division the LMPD division in which the incident actually occurred LMPD Beat the LMPD beat in which the incident actually occurred Location Category the type of location in which the incident occurred (e.g. Restaurant) Block Address the location the incident occurred City the city associated to the incident block location Zip Code the zip code associated to the incident block location Contact:LMPD Open Records lmpdopenrecords@louisvilleky.gov
The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on communitycrimemap.comData Dictionary:Field NameField DescriptionIncident Numberthe number associated with either the incident or used as reference to store the items in our evidence roomsDate Reportedthe date the incident was reported to LMPDDate Occurredthe date the incident actually occurredBadge IDBadge ID of responding OfficerOffense ClassificationNIBRS Reporting category for the criminal act committedOffense Code NameNIBRS Reporting code for the criminal act committedNIBRS_CODEthe code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewNIBRS Grouphierarchy that follows the guidelines of the FBI National Incident Based Reporting SystemWas Offense CompletedStatus indicating whether the incident was an attempted crime or a completed crime.LMPD Divisionthe LMPD division in which the incident actually occurredLMPD Beatthe LMPD beat in which the incident actually occurredLocation Categorythe type of location in which the incident occurred (e.g. Restaurant)Block Addressthe location the incident occurredCitythe city associated to the incident block locationZip Codethe zip code associated to the incident block locationContact:LMPD Open Records lmpdopenrecords@louisvilleky.gov
A public view of facilities (police departments, fire stations, emergency management, etc.) used to respond to emergency incidents.
The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. Part I categorizes incidents in two categories: violent and property crimes. Aggravated assault, forcible rape, murder, and robbery are classified as violent crime, while burglary, larceny-theft, and motor vehicle theft are classified as property crimes. This dataset contains FBI Uniform Crime Reporting (UCR) Part I crime data for the last 40 years in Greensboro, North Carolina. The crime rate or index is calculated on a per 100,000 resident basis.A crime rate describes the number of crimes reported to law enforcement agencies per 100,000 residents. A crime rate is calculated by dividing the number of reported crimes by the total population; the result is multiplied by 100,000. For example, in 2013 there were 496 robberies in Greensboro and the population was 268,176 according to the SBI estimate. This equals a robbery crime rate of 185 per 100,000 general population.496/268,176 = 0.00184953165085615 x 100,000 = 184.95The Greensboro Police Department is comprised of 787 sworn and non-sworn employees dedicated to the mission of partnering to fight crime for a safer Greensboro. We believe that effectively fighting crime requires everyone's effort. With your assistance, we can make our city safer. Wondering what you can do?Take reasonable steps to prevent being victimized. Lock your car and home doors. Be aware of your surroundings. If something or someonefeels out of the ordinary, go to a safe place.Be additional eyes and ears for us. Report suspicious or unusual activity, and provide tips through Crime Stoppers that can help solve crime.Look out for your neighbors. Strong communities with active Neighborhood Watch programs are not attractive to criminals. By taking care of the people around you, you can create safe places to live and work.Get involved! If you have children, teach them how to react to bullying, what the dangers of texting and driving are, and how to safely use the Internet. Talk with your older relatives about scams that target senior citizens.Learn more about GPD. Ride along with us. Participate in the Police Citizens' Academy. Volunteer, apply for an internship, or better yet join us.You may have heard about our philosophy of neighborhood-oriented policing. This is practice in policing that combines data-driven crime analysis with police/citizen partnerships to solve problems.In the spirit of partnership with the community, our goal is to make the Greensboro Police Department as accessible as possible to the people we serve. Policies and procedures, referred to as directives, are rules that all Greensboro Police Department employees must follow in carrying out the mission of the department. We will update the public copy of the directives in a timely manner to remain consistent with new policy and procedure updates.
Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov
Year-end, victim-based, listing of Carjacking offenses, a subset of Robberies, that occurred in calendar-years 2015-2017.NOTE: This PRELIMINARY INFORMATION is used on an ongoing basis by the Detroit Police Department for strategic planning and crime analysis. This data is not final and thus is not the crime data that is reported to the FBI Uniform Crime Reporting Program.
The Denver Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated Monday through Friday, adding new incidents and updating existing data with information gathered through the investigative process.Not surprisingly, crime data become more accurate over time, as new incidents are reported and more information comes to light during investigations.Crimes that occurred at least 30 days ago tend to be the most accurate, although records are returned for incidents that happened yesterday. This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Likewise, content provided on this site will probably differ somewhat from crime statistics published elsewhere by the City and County of Denver, even though they draw from the same database.
https://www.icpsr.umich.edu/web/ICPSR/studies/3372/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3372/terms
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.