GIS is a discipline that heavily relies on data. In this presentation we highlight all the geospatial data sources for crime mapping.
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This document summarizes a crime mapping and analysis project conducted for the Georgia Tech Police Department. The objectives were to map crime incidents from 2010-2015, identify crime hot spots, and direct police resources. Crime data was cleaned, geocoded and analyzed in ArcGIS. Point density analysis identified the most crime-heavy grids, with the area around Student Center, Ferst Drive, and North Avenue Apartments among the highest. The analysis can help GTPD better deploy patrols and resources to reduce crime in these locations.
This document outlines a project to analyze crime and census data in London. It describes a multi-phase approach including: 1) loading and visualizing crime data, 2) adding census data to the model and performing clustering and regression analysis, and 3) using the results to inform data mining. Key analysis techniques include k-means clustering of census variables to categorize areas, linear regression of census factors on crime types, and decision tree analysis using both crime and census data. The goal is to understand how socioeconomic factors relate to crime levels and types in different parts of London.
Abstract : Crime prediction is a topic of significant research across the fields of criminology, data mining, city planning, law enforcement, and political science. Crime patterns exist on a spatial level; these patterns can be grouped geographically by physical location, and analyzed contextually based on the region
in which crime occurs. This paper proposes a mechanism to parameterize street-level crime, localize crime hotspots, identify correlations between spatiotemporal crime patterns and social trends, and analyze the resulting data for the purposes of knowledge discovery and anomaly detection. The subject of this study is the county of Merseyside in the United Kingdom, over a span of 21 months beginning in December 2010 (monthly) through August 2012. Several types of crime are analyzed in this dataset, including Burglary and Antisocial Behavior. Through this analysis, several interesting findings are drawn about crime in Merseyside, including: hotspots with steadily increasing crime levels, hotspots with unstable crime levels, synchronous changes in crime trends throughout Merseyside as a whole, individual months in which certain hotspots behaved anomalously, and a strong correlation between crime hotspot locations and borough/postal code locations. We believe that this type of statistical and correlative analysis of crime patterns will help law enforcement agencies predict criminal activity, allocate resources, and promote community awareness to reduce overall crime rates.
For more information, please visit: http://people.cs.vt.edu/parang/ or contact parang at firstname at cs vt edu
This document discusses challenges with crime data analysis and mapping. It notes that all relevant data must be included to fully understand crimes like robbery-motivated homicides. Data quality issues like errors and omissions must be addressed. The appropriate level of detail, such as citywide versus block-level analysis, depends on the goals of the analysis. Different sources provide crime data, including the FBI's UCR and NIBRS programs, but each has weaknesses. Non-police sources can also supply useful contextual data.
GIS aids crime analysis by identifying patterns and trends, supporting intelligence-led policing strategies, and integrating diverse data sources. It enhances crime analysis by highlighting suspicious incidents, supporting cross-jurisdictional pattern analysis, and educating the public. GIS provides tools to capture crime series, forecast crime, and optimize resource allocation to reduce crime and disorder.
Crime mapping and analysis in the dansoman police subdivision, accra, ghana ...Alexander Decker
This document summarizes a study that used GIS to map and analyze crime in the Dansoman Police Subdivision of Accra, Ghana. The study analyzed spatial data on 142 crime incidents from 8 categories collected over a few months. Assault, causing damage, and unlawful entry had the highest counts, while rape and stealing had the lowest. Crime density maps showed the smallest district, Mamprobi, had the highest crime density. Statistical analysis found crimes were randomly distributed except for rape and stealing, which were dispersed. The mean centers of crimes were within 1 km of each other. The study aims to help the police visualize and understand crime patterns. It is recommended to collect longer-term crime data including perpetrator attributes to improve
This document discusses the OpenAus project, which aims to increase transparency of government spending in Australia by compiling and presenting budget, grants, and tenders data in an open and accessible format. It provides an overview of the types of spending data available on OpenAus, including top-down budget data and bottom-up data on grants and tenders. It also describes some of the features and capabilities of the OpenAus tools for searching, analyzing, and downloading government spending information.
Crime analysis involves the systematic study of crime and disorder problems using qualitative and quantitative data. It examines sociodemographic, spatial, and temporal factors to assist police in apprehension, reduction, prevention, and evaluation. Crime analysis developed from early uses of pin maps and began professionalizing in the 1980s. It includes administrative, investigative, tactical, and strategic types. Ratcliffe's Hotspot Matrix examines crime concentrations spatially as dispersed, clustered, or a hotpoint and temporally as diffused, focused, or acute to determine appropriate police tactics. Strategic crime analysis uses tactical analysis to identify long-term community problems and generate innovative solutions in partnership with community policing.
The document discusses the creation of the 2011 OAC (Office for National Statistics Area Classification), which organized areas into three tiers - Supergroups, Groups, and Subgroups - using statistical techniques. It then provides demographic and geographic data for the area within a 1km buffer of Kingston University, including percentages of the area covered by different 2011 OAC Subgroups and Acorn Types. The data comes from the 2011 UK Census and 2015 Acorn data from CACI, and shows generalizations due to clustering techniques.
The UN recently released a report analyzing casualty figures from 7 sources reporting deaths in Syria. The report estimates that nearly 60,000 deaths have occurred, more than previous estimates from non-government sources of around 40,000. It finds that violence can reduce reporting and that each source likely has its own biases. While crowd-sourced data is imperfect, it provides valuable near real-time information in such a constrained environment. Syria Tracker endorses the report and analysis of strengths and limitations of using crowd-sourced data.
Syrian activists, Arab and international human rights organizations and journalists have been collecting information to document crimes committed by the Syrian security forces against Syrian citizens. YouTube videos, reports by Non-Governmental Organizations (NGO), demanded of the United Nations (UN), interview transcripts, and news reports: all such sources of information exist independently, left unorganized and thus unable to make an optimal impact on advocacy for an international response to the crisis in Syria. This website, Syria Tracker, was developed to leverage information that is produced by citizen reporters and in collaboration with a variety of entities and made publicly available in disparate locations to produce a free centralized source of information. Hereinafter, we refer to this method of harnessing labor and information contributed by a large group of people as opposed to an employee or an expert contractor as crowdsourcing.
Professor Hendrik Speck - Crimeblips - Web Based Framework for Crime Incident...Hendrik Speck
Professor Hendrik Speck, Crimeblips, crime statistics, Kriminalstatistik, Polizei, Berlin, mapping, visualizing, map, analysis, visualization, hot spots, trends, incident patters, police department, law enforcement, data mining, GIS, indexing, linguistic processing, clustering, filtering, web based services, graphical user interface, University of Applied Sciences Kaiserslautern
The document summarizes several data tools provided by the U.S. Census Bureau, including the American Community Survey Information Guide, QuickFacts, Narrative Profiles, and Data.Census.gov. The ACS Information Guide is a comprehensive resource for ACS data. QuickFacts provides statistics for states, counties, and larger cities and towns. Narrative Profiles are short reports on select estimates for geographic areas. Data.Census.gov aims to make Census data more accessible in one central location.
The Global Justice Information Sharing Initiative (Global) aims to promote broad information sharing between justice entities to support public safety. It establishes working groups to focus on specific issues and develop solutions. The Global Intelligence Working Group was formed to serve as the Criminal Intelligence Coordinating Council and develop the National Criminal Intelligence Sharing Plan. The Plan establishes standards and guidelines for intelligence functions, recommends networks and systems for sharing intelligence, and protects civil rights while enabling information sharing.
The document discusses various data sources related to elections in Afghanistan, including a master list of polling centers from the Independent Election Commission, preliminary election results, and complaint data from the Electoral Complaints Commission. It describes how the data can be analyzed and mapped at the district level, including overlaying ethnic distributions and election results to examine voting patterns. Users can interact with the maps to drill down to different regions and levels of data.
Misi I Mewujudkan Pemerintahan yang Bersih dan MelayaniSugono Aprianto
This document discusses the implementation of e-government in Pesawaran Regency, Indonesia. It outlines 31 government and public service applications that have been implemented, including domains, online permitting, tax payment applications, and electronic archives. It also discusses awards received for transparency and compliance with public services. Cooperation agreements with other agencies to improve services are highlighted.
The Admin Data Census Team are now producing administrative based population estimates down to small area level. This SlideShare highlights some challenges with our small area estimates when we compare these with the official population estimates at Census Output Area (OA) level. We have demonstrated a number of challenges in estimating the population for small areas using case studies, along with possible ways we could address these. We are seeking feedback from our users on these findings. Contact [email protected]
This paper investigates the degree of association between major four crimes in Sudan, including illegal drug trafficking, murder, theft, and prostitution, with indicators of institutional weakness that include surge in other four crimes: duty & customs, forgery, passport related, and firearms & ammunition crimes. These later four crimes has been considered indicators of institutional weakness because upswing in these crimes is a reflection of corruption or negligence, or incompetence of institutional performance in the country. The canonical correlation test result indicates there is a very high and significant association between the major four crimes and the indicators of institutional weakness. This finding implies institutional weakness can nurture crime surge in the country. Cluster analysis indicates the type of crimes in conflict states of Darfor region are featured in the rest of the country except in the capital state, Khartoum which represent a separate cluster on its own. Cluster analysis also indicate murder crime is connected with prostitution; and theft crime is associated with firearms & ammunition crimes; custom & duty crimes connected with passport -related and illegal drugs crimes. However, illegal drugs crime is connected with murder, theft, and prostitution crimes.
Crime Data Analysis and Prediction for city of Los AngelesHeta Parekh
This document analyzes crime data from Los Angeles from 2010-2020 to identify trends, predict future crime rates, and make recommendations to law enforcement. Key findings include:
- Crime rates have generally declined over the past decade but dropped significantly in 2020 due to the pandemic.
- Robbery, burglary, and vandalism are the most common crimes.
- Areas with lower median household incomes tend to have higher crime rates.
- Females are consistently the most impacted victims of crime over the past 10 years.
- Southwest LA and other areas have been identified as "hot spots" for criminal activity.
Predictive analysis indicates crime rates will continue increasing post-lockdown in
This paper focuses on finding spatial and temporal criminal hotspots. It analyses two different real-world crimes datasets for Denver, CO and Los Angeles, CA and provides a comparison between the two datasets through a statistical analysis supported by several graphs. Then, it clarifies how we conducted Apriori algorithm to produce interesting frequent patterns for criminal hotspots. In addition, the paper shows how we used Decision Tree classifier and Naïve Bayesian classifier in order to predict potential crime types. To further analyse crimes’ datasets, the paper introduces an analysis study by combining our findings of Denver crimes’ dataset with its demographics information in order to capture the factors that might affect the safety of neighborhoods. The results of this solution could be used to raise people’s awareness regarding the dangerous locations and to help agencies to predict future crimes in a specific location within
a particular time.
Crime Analysis based on Historical and Transportation DataValerii Klymchuk
Contains experimental results based on real crime data from an urban city. Our set of statistics reveals seasonality in crime patterns to accompany predictive machine learning models assessing the risks of crime. Moreover, this work provides a discussion on implementation, design for a prototype of cloud based crime analytics dashboard.
Database and Analytics Programming - Project reportsarthakkhare3
The document summarizes research conducted on crime data from New York City in 2018. The researchers collected data on complaints, arrests, court summons, and prison admissions. They analyzed relationships between these datasets and performed visualizations. Key findings include: the number of complaints exceeded arrests and further declined on the paths to court summons and prison admissions; the top crimes differed between complaints/arrests and court summons/prison admissions; males and those aged 25-44 committed most crimes; Bronx and Manhattan had higher crime rates per capita than other boroughs. The research was limited to one year, and additional analysis could provide more insights into factors affecting proportions and more accurate crime prediction.
Crime mapping and analysis in the dansoman police subdivision, accra, ghana ...Alexander Decker
This document summarizes a study that used Geographic Information Systems (GIS) to map and analyze crime distribution in the Dansoman Police Subdivision of Accra, Ghana. 142 crime incident records were analyzed in GIS software. Assault, Causing Damage, and Unlawful Entry had the highest counts, while Rape and Stealing had the lowest. Crime density maps showed Mamprobi district had high crime density despite its small size. Spatial analysis found crimes were randomly distributed except for Rape and Stealing, which were statistically dispersed. The mean centers of crimes were within 1 km radius. The study aims to help police better understand and respond to crime patterns.
IRJET- Crime Analysis using Data Mining and Data AnalyticsIRJET Journal
This document discusses using data mining and analytics techniques to analyze crime data and predict crime rates. It proposes using linear regression on crime data from the Indian government to predict future crime occurrences and identify high-risk regions. The system would analyze factors like crime type, offender age, month, and year to build a regression model. This model could then predict crime rates and indicate whether a region is high or low risk for criminal activity. Graphs and tables would visualize the predictions to help law enforcement allocate resources. The goal is to help reduce crime and increase public safety by identifying patterns in historical crime data.
An Intelligence Analysis of Crime Data for Law Enforcement Using Data MiningWaqas Tariq
The concern about national security has increased significantly since the 26/11 attacks at Mumbai, India. However, information and technology overload hinders the effective analysis of criminal and terrorist activities. Data mining applied in the context of law enforcement and intelligence analysis holds the promise of alleviating such problem. In this paper we use a clustering/classify based model to anticipate crime trends. The data mining techniques are used to analyze the city crime data from Tamil Nadu Police Department. The results of this data mining could potentially be used to lessen and even prevent crime for the forth coming years
Spatial analysis of Mexican Homicides and Proximity to the US BorderKezia Dinelt
This document describes a spatial analysis of homicides related to drug trafficking organizations (DTOs) in Mexico in 2010 in relation to proximity to the U.S. border. The author hypothesizes that DTO homicides will be more prevalent closer to border crossings due to drug trafficking between Mexico and the U.S. The analysis uses GIS shapefiles including Mexican municipalities, DTO homicides in 2010, U.S. border cities, and population/inequality data. Regression is performed to analyze the relationship between DTO homicides and distance from border points while controlling for population density and inequality.
This document discusses the application of geographic information systems (GIS) in criminology and defense intelligence. It provides examples of how GIS has been used to map crime rates and identify spatial patterns in criminal behavior. GIS allows crime analysis to identify crime hotspots, support investigative leads, and help allocate law enforcement resources more efficiently. The document also outlines how GIS aids tactical crime analysis and criminal investigations through geographic profiling. Finally, it notes that GIS is increasingly important for military applications by helping commanders understand terrain influences on operations.
The document discusses the creation of the 2011 OAC (Office for National Statistics Area Classification), which organized areas into three tiers - Supergroups, Groups, and Subgroups - using statistical techniques. It then provides demographic and geographic data for the area within a 1km buffer of Kingston University, including percentages of the area covered by different 2011 OAC Subgroups and Acorn Types. The data comes from the 2011 UK Census and 2015 Acorn data from CACI, and shows generalizations due to clustering techniques.
The UN recently released a report analyzing casualty figures from 7 sources reporting deaths in Syria. The report estimates that nearly 60,000 deaths have occurred, more than previous estimates from non-government sources of around 40,000. It finds that violence can reduce reporting and that each source likely has its own biases. While crowd-sourced data is imperfect, it provides valuable near real-time information in such a constrained environment. Syria Tracker endorses the report and analysis of strengths and limitations of using crowd-sourced data.
Syrian activists, Arab and international human rights organizations and journalists have been collecting information to document crimes committed by the Syrian security forces against Syrian citizens. YouTube videos, reports by Non-Governmental Organizations (NGO), demanded of the United Nations (UN), interview transcripts, and news reports: all such sources of information exist independently, left unorganized and thus unable to make an optimal impact on advocacy for an international response to the crisis in Syria. This website, Syria Tracker, was developed to leverage information that is produced by citizen reporters and in collaboration with a variety of entities and made publicly available in disparate locations to produce a free centralized source of information. Hereinafter, we refer to this method of harnessing labor and information contributed by a large group of people as opposed to an employee or an expert contractor as crowdsourcing.
Professor Hendrik Speck - Crimeblips - Web Based Framework for Crime Incident...Hendrik Speck
Professor Hendrik Speck, Crimeblips, crime statistics, Kriminalstatistik, Polizei, Berlin, mapping, visualizing, map, analysis, visualization, hot spots, trends, incident patters, police department, law enforcement, data mining, GIS, indexing, linguistic processing, clustering, filtering, web based services, graphical user interface, University of Applied Sciences Kaiserslautern
The document summarizes several data tools provided by the U.S. Census Bureau, including the American Community Survey Information Guide, QuickFacts, Narrative Profiles, and Data.Census.gov. The ACS Information Guide is a comprehensive resource for ACS data. QuickFacts provides statistics for states, counties, and larger cities and towns. Narrative Profiles are short reports on select estimates for geographic areas. Data.Census.gov aims to make Census data more accessible in one central location.
The Global Justice Information Sharing Initiative (Global) aims to promote broad information sharing between justice entities to support public safety. It establishes working groups to focus on specific issues and develop solutions. The Global Intelligence Working Group was formed to serve as the Criminal Intelligence Coordinating Council and develop the National Criminal Intelligence Sharing Plan. The Plan establishes standards and guidelines for intelligence functions, recommends networks and systems for sharing intelligence, and protects civil rights while enabling information sharing.
The document discusses various data sources related to elections in Afghanistan, including a master list of polling centers from the Independent Election Commission, preliminary election results, and complaint data from the Electoral Complaints Commission. It describes how the data can be analyzed and mapped at the district level, including overlaying ethnic distributions and election results to examine voting patterns. Users can interact with the maps to drill down to different regions and levels of data.
Misi I Mewujudkan Pemerintahan yang Bersih dan MelayaniSugono Aprianto
This document discusses the implementation of e-government in Pesawaran Regency, Indonesia. It outlines 31 government and public service applications that have been implemented, including domains, online permitting, tax payment applications, and electronic archives. It also discusses awards received for transparency and compliance with public services. Cooperation agreements with other agencies to improve services are highlighted.
The Admin Data Census Team are now producing administrative based population estimates down to small area level. This SlideShare highlights some challenges with our small area estimates when we compare these with the official population estimates at Census Output Area (OA) level. We have demonstrated a number of challenges in estimating the population for small areas using case studies, along with possible ways we could address these. We are seeking feedback from our users on these findings. Contact [email protected]
This paper investigates the degree of association between major four crimes in Sudan, including illegal drug trafficking, murder, theft, and prostitution, with indicators of institutional weakness that include surge in other four crimes: duty & customs, forgery, passport related, and firearms & ammunition crimes. These later four crimes has been considered indicators of institutional weakness because upswing in these crimes is a reflection of corruption or negligence, or incompetence of institutional performance in the country. The canonical correlation test result indicates there is a very high and significant association between the major four crimes and the indicators of institutional weakness. This finding implies institutional weakness can nurture crime surge in the country. Cluster analysis indicates the type of crimes in conflict states of Darfor region are featured in the rest of the country except in the capital state, Khartoum which represent a separate cluster on its own. Cluster analysis also indicate murder crime is connected with prostitution; and theft crime is associated with firearms & ammunition crimes; custom & duty crimes connected with passport -related and illegal drugs crimes. However, illegal drugs crime is connected with murder, theft, and prostitution crimes.
Crime Data Analysis and Prediction for city of Los AngelesHeta Parekh
This document analyzes crime data from Los Angeles from 2010-2020 to identify trends, predict future crime rates, and make recommendations to law enforcement. Key findings include:
- Crime rates have generally declined over the past decade but dropped significantly in 2020 due to the pandemic.
- Robbery, burglary, and vandalism are the most common crimes.
- Areas with lower median household incomes tend to have higher crime rates.
- Females are consistently the most impacted victims of crime over the past 10 years.
- Southwest LA and other areas have been identified as "hot spots" for criminal activity.
Predictive analysis indicates crime rates will continue increasing post-lockdown in
This paper focuses on finding spatial and temporal criminal hotspots. It analyses two different real-world crimes datasets for Denver, CO and Los Angeles, CA and provides a comparison between the two datasets through a statistical analysis supported by several graphs. Then, it clarifies how we conducted Apriori algorithm to produce interesting frequent patterns for criminal hotspots. In addition, the paper shows how we used Decision Tree classifier and Naïve Bayesian classifier in order to predict potential crime types. To further analyse crimes’ datasets, the paper introduces an analysis study by combining our findings of Denver crimes’ dataset with its demographics information in order to capture the factors that might affect the safety of neighborhoods. The results of this solution could be used to raise people’s awareness regarding the dangerous locations and to help agencies to predict future crimes in a specific location within
a particular time.
Crime Analysis based on Historical and Transportation DataValerii Klymchuk
Contains experimental results based on real crime data from an urban city. Our set of statistics reveals seasonality in crime patterns to accompany predictive machine learning models assessing the risks of crime. Moreover, this work provides a discussion on implementation, design for a prototype of cloud based crime analytics dashboard.
Database and Analytics Programming - Project reportsarthakkhare3
The document summarizes research conducted on crime data from New York City in 2018. The researchers collected data on complaints, arrests, court summons, and prison admissions. They analyzed relationships between these datasets and performed visualizations. Key findings include: the number of complaints exceeded arrests and further declined on the paths to court summons and prison admissions; the top crimes differed between complaints/arrests and court summons/prison admissions; males and those aged 25-44 committed most crimes; Bronx and Manhattan had higher crime rates per capita than other boroughs. The research was limited to one year, and additional analysis could provide more insights into factors affecting proportions and more accurate crime prediction.
Crime mapping and analysis in the dansoman police subdivision, accra, ghana ...Alexander Decker
This document summarizes a study that used Geographic Information Systems (GIS) to map and analyze crime distribution in the Dansoman Police Subdivision of Accra, Ghana. 142 crime incident records were analyzed in GIS software. Assault, Causing Damage, and Unlawful Entry had the highest counts, while Rape and Stealing had the lowest. Crime density maps showed Mamprobi district had high crime density despite its small size. Spatial analysis found crimes were randomly distributed except for Rape and Stealing, which were statistically dispersed. The mean centers of crimes were within 1 km radius. The study aims to help police better understand and respond to crime patterns.
IRJET- Crime Analysis using Data Mining and Data AnalyticsIRJET Journal
This document discusses using data mining and analytics techniques to analyze crime data and predict crime rates. It proposes using linear regression on crime data from the Indian government to predict future crime occurrences and identify high-risk regions. The system would analyze factors like crime type, offender age, month, and year to build a regression model. This model could then predict crime rates and indicate whether a region is high or low risk for criminal activity. Graphs and tables would visualize the predictions to help law enforcement allocate resources. The goal is to help reduce crime and increase public safety by identifying patterns in historical crime data.
An Intelligence Analysis of Crime Data for Law Enforcement Using Data MiningWaqas Tariq
The concern about national security has increased significantly since the 26/11 attacks at Mumbai, India. However, information and technology overload hinders the effective analysis of criminal and terrorist activities. Data mining applied in the context of law enforcement and intelligence analysis holds the promise of alleviating such problem. In this paper we use a clustering/classify based model to anticipate crime trends. The data mining techniques are used to analyze the city crime data from Tamil Nadu Police Department. The results of this data mining could potentially be used to lessen and even prevent crime for the forth coming years
Spatial analysis of Mexican Homicides and Proximity to the US BorderKezia Dinelt
This document describes a spatial analysis of homicides related to drug trafficking organizations (DTOs) in Mexico in 2010 in relation to proximity to the U.S. border. The author hypothesizes that DTO homicides will be more prevalent closer to border crossings due to drug trafficking between Mexico and the U.S. The analysis uses GIS shapefiles including Mexican municipalities, DTO homicides in 2010, U.S. border cities, and population/inequality data. Regression is performed to analyze the relationship between DTO homicides and distance from border points while controlling for population density and inequality.
This document discusses the application of geographic information systems (GIS) in criminology and defense intelligence. It provides examples of how GIS has been used to map crime rates and identify spatial patterns in criminal behavior. GIS allows crime analysis to identify crime hotspots, support investigative leads, and help allocate law enforcement resources more efficiently. The document also outlines how GIS aids tactical crime analysis and criminal investigations through geographic profiling. Finally, it notes that GIS is increasingly important for military applications by helping commanders understand terrain influences on operations.
The document analyzes burglary crime data from England between 2010-2021 to determine if burglaries occur more in affluent or deprived areas, and if the trend is increasing, decreasing, or stable. The analysis found that most burglaries occurred in non-affluent areas, though the decline in burglaries was slower in affluent and deprived areas. Association rule mining showed affluence and high deprivation were most associated with burglaries. Overall, burglaries were found to be decreasing nationwide, with the decline slower in affluent and deprived areas. The findings support targeting affluent areas with premium insurance and deprived areas with lower-cost policies.
This document provides a summary of predictive policing technologies and their implications. It discusses how policing has evolved from political to community-based models using broken windows theory. Two predictive policing software programs, PredPol and HunchLab, use data analysis to predict future crime locations. While these programs aim to efficiently allocate police resources, concerns include privacy violations, implementation costs, and potential biases. The document examines debates around predictive policing and big data collection in law enforcement.
Geospatial Crime Hotspot Detection: A Robust Framework using Birch Clustering...dannyijwest
Crime causes physical and mental damage. Several crime prevention measures have been developed by law enforcement officials since they realized how serious this problem is. These preventative measures are not strong enough to help lower crime rates because they are typically slow-paced and ineffectual. In this regard, machine learning community has started developing automated approaches for detecting crime hotspot, after performing a careful analysis of the crime trend incorporating geospatial, temporal, demographic, or other relevant information. In this research, we look at detecting crime hotspots using geospatial information of prior crime occurrences. We proposed BIRCH algorithm to detect high crime prone areas with four essential aspects: (1) PCA (Principle Component Analysis) has been used to minimize the dimensionality of crime data, (2) Silhouette score Elbow and Calinski Harabaz have been used to find the optimal number of cluster (3) utilized hyper-parameter tuning to choose the best hyperparameters for the BIRCH algorithm (4) applied BIRCH with the three aspects mentioned above. The results of the suggested framework were then contrasted with those of alternative clustering techniques, such as K-means, DBSCAN, and the agglomerative algorithm. We explored our approaches on the London Crime Dataset and found some fascinating results that can help reducing crime by helping people take the appropriate measures.
GEOSPATIAL CRIME HOTSPOT DETECTION: A ROBUST FRAMEWORK USING BIRCH CLUSTERING...IJwest
Crime causes physical and mental damage. Several crime prevention measures have been developed by law
enforcement officials since they realized how serious this problem is. These preventative measures are not
strong enough to help lower crime rates because they are typically slow-paced and ineffectual. In this
regard, machine learning community has started developing automated approaches for detecting crime
hotspot, after performing a careful analysis of the crime trend incorporating geospatial, temporal,
demographic, or other relevant information. In this research, we look at detecting crime hotspots using
geospatial information of prior crime occurrences. We proposed BIRCH algorithm to detect high crime
prone areas with four essential aspects: (1) PCA (Principle Component Analysis) has been used to
minimize the dimensionality of crime data, (2) Silhouette score Elbow and Calinski Harabaz have been
used to find the optimal number of cluster (3) utilized hyper-parameter tuning to choose the best hyper-
parameters for the BIRCH algorithm (4) applied BIRCH with the three aspects mentioned above. The
results of the suggested framework were then contrasted with those of alternative clustering techniques,
such as K-means, DBSCAN, and the agglomerative algorithm. We explored our approaches on the London
Crime Dataset and found some fascinating results that can help reducing crime by helping people take the
appropriate measures.
Discover population demographics, real estate value, and lifestyle segmentation with Census maps. Get insights into your target market for better decision-making
This document summarizes research analyzing crime data from Atlanta and Georgia Tech. It discusses using patrol analysis and identifying hot spots to optimize police patrol routes. Time series analysis of crime data revealed seasonal patterns, with some crime types peaking in September. Hot spot analysis identified concentrated areas of crime in Atlanta using statistical tests, with the nearest neighbor index method most accurately representing hot spots. In conclusion, optimizing patrol routes based on crime patterns and hot spots could lower crime rates and improve police efficiency.
This document presents an approach for generating valuable traffic density data to simulate route planning for patrol cars. It involves extracting location data from GPS and tracking devices of patrol cars over time. This data is used to calculate route frequencies, which are then encoded with color to represent density on a map. The route density data is then correlated with crime hotspot information to propose a new route planning simulation for law enforcement. This aims to more efficiently dispatch patrol cars by considering both traffic patterns and crime trends.
Developing a Crime Mapping GIS System For Law Enforcement: A Case Study of Ow...Editor IJCATR
This paper examines the use of GIS in the development of a crime analysis information system for the Nigeria police. In recent times, criminality has been on the increase with criminals using new and more sophisticated ways to commit crime; resulting to fear and restlessness among the citizens. They police have found it difficult to manage and control these crimes largely due to the obsolete methods and resources they employ in doing so. The purpose of this study is to see how the Nigerian Police Force can adopt the use of crime maps in its operations and reap the benefits. The system will help the police in the analysis of crimes which will lead to crime hotspots identification. Using ArcGIS Software 10.0, we created a digital land use map of crime hotspots in the area and a crime-geospatial database. The results of the spatial analysis and a 500m buffering done on the data shows that areas that are more vulnerable to crime, have no police stations situated around them. This study shows that a GIS based Information system will give the police better insights into crime mapping and analysis which will be a tool to help them effectively manage and combat crime. This study recommends full government involvement in the area of human personnel and infrastructure development for the police to effectively change from the traditional to GIS based ways of combating crime.
Propose Data Mining AR-GA Model to Advance Crime analysisIOSR Journals
This document proposes a data mining model to advance crime analysis using association rule (AR) and genetic algorithm (GA). The model has three correlated dimensions: a crime dataset, criminal dataset, and geo-crime dataset. AR will be applied to each dataset separately to extract patterns, then GA will be used to mix the resulting ARs and exploit relationships across the three dimensions. This is intended to help detect universal crime patterns and speed up the crime solving process. The model was applied to real crime data from a sheriff's office and validated. Privacy-preserving techniques are also suggested to hide sensitive rules from appearing in the results.
A mother gave birth vaginally to a baby girl. During labor and delivery, she experienced preeclampsia and gestational hypertension. She received magnesium to lower her blood pressure. An epidural and oxytocin were administered and she underwent shoulder dystocia maneuvers and an episiotomy. The birth was successful but the baby had a bruised posterior skull. To address impaired parent-infant bonding and the baby's risk of nutritional imbalance, the baby was breastfed and given skin-to-skin contact with the mother. Evaluations found the newborn successfully breastfed and bonded with the mother, and had good APGAR scores and nutritional prognosis.
Nitrobenzene is an organic compound represented by the chemical formula C6H5NO2. It has significant roles both commercially, and within the laboratory as a solvent. The upload is a lab report of how the experiment goes on within the lab, through a process of electrophilic aromatic substitution.
Commonly Used Parametric Statistical Tests in SPSS and STATAExpert Writing Help
We present to you common statistical tests as used in SPSS and STATA. These test include correlations for measuring degree of association. T-test as used in determining independence of variables. Regression tests are used to measure causal effect among variables.
Expert Writing Help is a nursing writing service that assists students write Paediatric nursing care plan and other diagnosis plans. This upload offers nursing students with a Paediatric nursing care plan example to teach them on the best template for writing nursing care plans.
1) The document examines Starbucks' expansion strategies into different countries including Japan, Korea, Britain, and Thailand. It discusses the various entry modes companies can use, including exporting, franchising, joint ventures, and wholly owned subsidiaries.
2) When expanding to the UK, Starbucks relied on a wholly owned subsidiary model by acquiring 65 existing stores. This allowed them to quickly gain a foothold in the market while maintaining control over operations.
3) The document provides context on business environments and regulations in each target country to understand factors influencing Starbucks' entry mode decisions.
The Australian Securities and Investments Commission (ASIC) has admitted that Australia's disclosure regime has inherent weaknesses that failed to prevent investors from losing money on complex financial products like collateralized debt obligations. ASIC is considering requiring investors to pass basic assessments showing they understand products before investing, to address these weaknesses. ASIC chairman Greg Medcraft acknowledged that both wholesale and retail investors lost significantly on these products since 2008 due to an inability to understand the risks. ASIC is looking at ways to better regulate these products, including through investor education programs.
The Australian Securities and Investments Commission (ASIC) has admitted that Australia's disclosure regime has inherent weaknesses that failed to prevent investors from losing money on complex financial products like collateralized debt obligations. ASIC is considering requiring investors to pass basic understanding assessments before investing in such products. ASIC chairman Greg Medcraft acknowledged that wholesale and retail investors lost significantly on these products since 2008 due to an inability to understand the risks. ASIC is exploring ways to better regulate complex products, including through investor education modules.
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INTRO TO STATISTICS
INTRO TO SPSS INTERFACE
CLEANING MULTIPLE CHOICE RESPONSE DATA WITH EXCEL
ANALYZING MULTIPLE CHOICE RESPONSE DATA
INTERPRETATION
Q & A SESSION
PRACTICAL HANDS-ON ACTIVITY
How to manage Multiple Warehouses for multiple floors in odoo point of saleCeline George
The need for multiple warehouses and effective inventory management is crucial for companies aiming to optimize their operations, enhance customer satisfaction, and maintain a competitive edge.
Multi-currency in odoo accounting and Update exchange rates automatically in ...Celine George
Most business transactions use the currencies of several countries for financial operations. For global transactions, multi-currency management is essential for enabling international trade.
Title: A Quick and Illustrated Guide to APA Style Referencing (7th Edition)
This visual and beginner-friendly guide simplifies the APA referencing style (7th edition) for academic writing. Designed especially for commerce students and research beginners, it includes:
✅ Real examples from original research papers
✅ Color-coded diagrams for clarity
✅ Key rules for in-text citation and reference list formatting
✅ Free citation tools like Mendeley & Zotero explained
Whether you're writing a college assignment, dissertation, or academic article, this guide will help you cite your sources correctly, confidently, and consistent.
Created by: Prof. Ishika Ghosh,
Faculty.
📩 For queries or feedback: [email protected]
The Pala kings were people-protectors. In fact, Gopal was elected to the throne only to end Matsya Nyaya. Bhagalpur Abhiledh states that Dharmapala imposed only fair taxes on the people. Rampala abolished the unjust taxes imposed by Bhima. The Pala rulers were lovers of learning. Vikramshila University was established by Dharmapala. He opened 50 other learning centers. A famous Buddhist scholar named Haribhadra was to be present in his court. Devpala appointed another Buddhist scholar named Veerdeva as the vice president of Nalanda Vihar. Among other scholars of this period, Sandhyakar Nandi, Chakrapani Dutta and Vajradatta are especially famous. Sandhyakar Nandi wrote the famous poem of this period 'Ramcharit'.
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
This chapter provides an in-depth overview of the viscosity of macromolecules, an essential concept in biophysics and medical sciences, especially in understanding fluid behavior like blood flow in the human body.
Key concepts covered include:
✅ Definition and Types of Viscosity: Dynamic vs. Kinematic viscosity, cohesion, and adhesion.
⚙️ Methods of Measuring Viscosity:
Rotary Viscometer
Vibrational Viscometer
Falling Object Method
Capillary Viscometer
🌡️ Factors Affecting Viscosity: Temperature, composition, flow rate.
🩺 Clinical Relevance: Impact of blood viscosity in cardiovascular health.
🌊 Fluid Dynamics: Laminar vs. turbulent flow, Reynolds number.
🔬 Extension Techniques:
Chromatography (adsorption, partition, TLC, etc.)
Electrophoresis (protein/DNA separation)
Sedimentation and Centrifugation methods.
K12 Tableau Tuesday - Algebra Equity and Access in Atlanta Public Schoolsdogden2
Algebra 1 is often described as a “gateway” class, a pivotal moment that can shape the rest of a student’s K–12 education. Early access is key: successfully completing Algebra 1 in middle school allows students to complete advanced math and science coursework in high school, which research shows lead to higher wages and lower rates of unemployment in adulthood.
Learn how The Atlanta Public Schools is using their data to create a more equitable enrollment in middle school Algebra classes.
How to Customize Your Financial Reports & Tax Reports With Odoo 17 AccountingCeline George
The Accounting module in Odoo 17 is a complete tool designed to manage all financial aspects of a business. Odoo offers a comprehensive set of tools for generating financial and tax reports, which are crucial for managing a company's finances and ensuring compliance with tax regulations.
UNIT 3 NATIONAL HEALTH PROGRAMMEE. SOCIAL AND PREVENTIVE PHARMACYDR.PRISCILLA MARY J
GEOSPATIAL DATA SOURCES
1. GEOSPATIAL DATA SOURCES
Introduction
Intricacies and nuances of the data
Characteristics of the data source
Nature of the spatial units and georefencing
Crime figures
The reference spatial system adopted for the study is the SGB_1936_British_National_Grid while the
projection used is Transverse_Mercator Geographic Coordinate System: GCS_OSGB 1936. The use of two
different systems in the data makes it uncorrelated. When the data is overlaid on the boundary shapefiles,
it does not fall on the exact location and there is need to introduce a shift that lowers the accuracy of the
project.
Some of the statistical data lack the spatial information, thus the process of linking the data to a spatial
system is lengthy and in most cases it is not geo-specific. There is a need to standardise the parameters
used in the spatial representation of data for ease of representation in the GIS based software.
A geospatial data source provides the necessary information to a GIS platform or spatial based database for
numerous GIS manipulation and applications. There are wide geospatial data sources available. Choice of
which data source to be used in accruing geo-data depends on so many factors namely, project type,
geographic extent of the area of study, cost/budget of the project or data capture, time and so many others.
Each data source has its pros and cons especially in this fields that is very critical and sensitive to the
authenticity of the geo-data in terms of accuracy, relevance, age and quality. One of the type of geospatial
data source highly embraced nowadays is the internet geoportals. Internet is a major player of providing GIS
data in digital format. Lets Focus On the following geospatial data source and more keenly on crime figures in
United Kingdom.
The information give the record of crimes recorded in
the area, the frequency of the crime, the locations the
incidence occurred and the status of the investigation
on the authorities’ part. The information keeps a
statistical follow up on the actual reported crime rate.
The data has spatial attribute linked to it for accurate
mapping of the hotspot areas.
The data has geographic coordinates that can be imported into the ArcGIS
software for the mapping. The correlation of the values and the software
enhances the accuracy in mapping the crime with the area it was reported. The
information helps to develop a hotspot map on where crime rate is high and a
linkage with other factors common to the area helps explain the patterns. For
instance we can see the rate and area where burglary in Westminster
And London in the large context
occured
The statistics reveal the geographic location where crimes have taken place and the reported crime is
recorded. The data given has been sourced from the government records on how the crimes have been
reported and the status of the crime that is either concluded, under investigation or suspect is being
charged (met.police.uk, 2015).
The data was linked to a spatial database to generate a map that shows the location of the crime. An
analysis was conducted to establish the neighbourhood correlation of the crime statistics, analysing the
correlation of the data with population, depravation index and the reported cases.
The currency of the data is limited to the level of statistics that the state reports, records and releases to
the public.
Population Census
The census shows the distribution of the population across the country in different wards. The population
is distributed based on the gender, age, income, location and income levels (Anon., 2016). The data is broad
and easy to manipulate by assessing the records of metadata. It gives the rate of population increase over
the years after census reports.
The data availed for the study was quite bulky without any analysis on the data. Data was
sampled from police records on the reported crime rates in the country with a major interest on
Strand and Whitehall area of Westminster.
The boundaries were provided as shapefiles and the metadata was in excel sheets that were
linked to the boundary data to show the relationship. The source of the data was deemed
accurate based on the person reporting the crime, the occurrence and frequency of reporting
crime. Burglary crime has a significant statistics at (5 percentage) with a high record at (33 in
Lambeth).
Index of Multiple Deprivation
The index is a tool used by the government to assess the deprivation in various areas in the U.K.
The index assesses seven aspects of the neighbourhood renewal unit to establish the correlation
these indices have with the levels of crime in U.K. The data is used to identify the most deprives
areas in the U.K, to compare different geographic areas and identify factors that shows the patter
of stud (Go.UK, 2015). In this study, the enviro-crime mapping will be
Education Skills and Training – Education reveals the reasons why the employment is low and
the crime rate is high.
Barriers to Housing and Services – Shelter is a basic need of any individual and the deprivation
of the same leave individuals to live on the street. The homeless people on the street steal
from the people thus increasing the crime rate in the state.
Crime-The assessment of the crime rate establishes the relationship between all other factors
and the deprivation. It is expected that crime is high in deprived area and it spreads across the
neighbouring regions.
Living Environment- it gives the condition of the population environment in terms of
accessibility to basic amenities, utilization of the same and hindrances to adequate use of the
resources.
This information gives the relocation rate of individuals within a given area. The
findings help
to correlate the migration into or out of an area and its relationship to crime and
the environment. The data is sourced from government records on the property
sales.
Residential property sales data
Mortality or morbidity statistics.
The data gives the birth rate, the death rate and the information is
used to assess increase or decrease in population and the rate of
change (go.uk, 2011).
The data acts as a measure of the effects of crime rate in causing
deaths, or establishing the correlation between the crime rate and
the increasing populations. The assessment gives a pattern that is
studies to show the correlation between data
Its strengths and weaknesses
The raw data is imperative without the analysis and the distribution of the crime
location. The format of the data requires a lot of linkages with other sources to
make conclusive derivation of it. Since, the storage is in different format, while
some are compatible, others are not and a common factor has to be generated
to make it logic.
Another challenge is the lack of clear facts to analyse since the data is collected
without specific focus on the analysis to be carried out.
The data however gives spatial location attributes that map out the areas where
it was reported that makes it easy to analyse the centre with the highest crime
rate reports. The density map analysis gives us an understanding of locality that
crime is likely to occur or rampant from the trends and patterns: seen as below
The level of spatial (geographical) detail
The analysis using GIS gives us the relationship between crime rate and other
non-spatial attributes such as education, health, population data and others.
The relevance of this data is linked to the depravation index of different wards
in the country and the areas with multiple depravation have high crime rates
compared with areas with low depravation.
The analysis helps the decision making process on areas to develop,
establishing ways to reduce the crime rate such as increase police vigilance,
positioning of cameras and engage the public.
The data can also be used to monitor the trends and patters on spatial and
non-spatial attributes over time by creating a real time and updatable database
The potential utility in GIS-based analyses
Bibliography
Anon., 2016. Crime and justice. [Online]
Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice
[Accessed 6 February 2017].
go.uk, 2011. peoplepopulationandcommunity. [Online]
Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/
[Accessed 6 February 2017].
Go.UK, 2015. Index of Multiple Deprivation. [Online]
Available at: https://www.gov.uk/government/statistics/englishindices-of-deprivation-
2015
[Accessed 6 February 2017].
landregistry, 2015. land registry. [Online]
Available at: http://landregistry.data.gov.uk/
[Accessed 6 February 2017].
met.police.uk, 2015. Crime map in U.K. [Online]
Available at: http://maps.met.police.uk/tables.htm
[Accessed 6 February 2017].