Transaction Search Form: please type in any of the fields below.
Date: November 22, 2024 Fri
Time: 11:40 am
Time: 11:40 am
Results for geospatial analysis
5 results foundAuthor: Mack, Elizabeth A. Title: Sex Offenders and Residential Location: A Predictive Analytic Framework Summary: Despite the growing body of research dealing with sex offenders and the collateral consequences of legislation governing their post release movements, a complete understanding of the residential choices of registered sex offenders remains elusive. The purpose of this paper is to introduce a predictive analytical framework for determining which demographic and socioeconomic factors best forecast the residential choices of convicted sex offenders. Specifically, using a derived index of social disorganization (ISDOR) and a commercial geographic information system (GIS), we implement both linear statistical and non-linear data mining approaches to predict the presence of sex offenders in a community. The results of this analysis are encouraging, with nearly 75% of registered offender locations predicted correctly. The implications of these approaches for public policy are discussed. Details: Tempe, AZ: Arizona State University, GeoDa Center for Geospatial Analysis and Computation, 2010. 37p. Source: Internet Resource: Working Paper No. 2010-03: Accessed October 14, 2010 at: http://geodacenter.asu.edu/drupal_files/2010-03_0.pdf Year: 2010 Country: United States URL: http://geodacenter.asu.edu/drupal_files/2010-03_0.pdf Shelf Number: 119955 Keywords: Data MiningGeographic StudiesGeospatial AnalysisGISResidency RestrictionsSex OffendersSocioeconomic Status |
Author: Nobis, Elizabeth Title: Improving the Epidemiology of Alcohol-Related Violence in the City of Philadelphia Using Geospatial Analysis Summary: In the United States, alcohol related violence is a major public health problem. There is a significant amount of evidence suggesting that the density of alcohol outlets and the level of social disorganization in a neighborhood are related to levels of violent assault. Less is known about the spatial distribution of assaults surrounding these alcohol outlets including the neighborhood characteristic of vacant lots. Better understanding these spatial linkages will contribute to improvements in the public health efforts to suppress violence and morbidity. Objective: This project aims to determine whether the density of alcohol outlets in Philadelphia is associated with neighborhood levels of violence and whether this relationship is influenced by the density of vacant lots. It was then investigated how violence geographical clusters around these spaces. Methods: This study utilized police-recorded data of aggravated assaults in Philadelphia, alcohol outlet addresses in Philadelphia, and 2010 Census Bureau block group information. Descriptive statistics, regression, spatial clustering, and qualitative mapping analysis were used to identify the distribution and relationships of assaults in the city. Results: Areas with higher percentages of vacant housing in combination with high density of alcohol outlets have a positive relationship with increased levels of aggravated assaults. This effect is most evident in economically disadvantaged areas. Conclusion: There is significant evidence that aggravated assaults are spatially linked to alcohol outlets and vacant lots. Development of alcohol policy, as well as improving neighborhood environments in low-income areas will reduce alcohol-related violence and improve the safety of Philadelphia’s general public. Details: Philadelphia: Drexel University, School of Public Health, 2012. 59p. Source: Internet Resource: Thesis: Accessed April 25, 2013 at: http://idea.library.drexel.edu/handle/1860/3946 Year: 2012 Country: United States URL: http://idea.library.drexel.edu/handle/1860/3946 Shelf Number: 128500 Keywords: Aggravated AssaultsAlcohol-Related Crime, Disorder (Philadelphia, U.SGeographical Information Systems (GIS)Geospatial AnalysisViolenceViolent Crimes |
Author: Bond, Brenda J. Title: Lowell, Massachusetts, Smart Policing Initiative: Reducing Property Crime in Targeted Hot Spots Summary: From 2007 through 2008, the city of Lowell, Massachusetts, experienced a 15 percent increase in property crime, driven by surges in car theft (12 percent), burglary (14 percent), and larceny (21 percent). Much of the increase was tied to drug offenders who committed crimes to support their addictions. The Lowell Smart Policing Initiative (SPI), funded by the Bureau of Justice Assistance (BJA), sought to address drug-related property crime through problem-oriented policing and the SARA model: Scanning, Analysis, Response, and Assessment. A Steering Committee composed of department staff and researchers who were well versed in advanced problem solving led the Lowell SPI. In order to avoid some of the traditional problems with SARA implementation, the Lowell SPI team employed a more sophisticated problem-solving process that assessed the congruence or "fit" among the targeted crime problems and the different elements of the SPI strategy. As part of the analysis phase, the Lowell SPI team collaborated with the city Health Department to examine the background and history of all individuals who died as a result of a drug overdose in Lowell from 2005 through 2008. Results confirmed the strong link between drug use and property crime. The SPI team then identified 12 property crime hot spots across three sectors, most of which were near known drug markets. Lowell crime analysts identified comparison hot spots that were matched to targeted hot spots using a matched-pair design. Captains in each of the three sectors generated response plans which were discussed, modified, and monitored at the bi-weekly SPI Steering Committee meetings. Sector Captains also completed bi-weekly surveys which systematically captured the strategies and tactics that were employed in the targeted hot spots. The survey results documented a high degree of congruence between the targeted crime problems and the selected crime reduction strategies. Results from the assessment phase indicate that each sector experienced significant declines in property crime from the pre-intervention period (9/2009-10/2010) to the intervention period (9/2011-12/2012). These crime declines ranged from 16 to 19 percent, though specific hot spots experienced much larger drops in certain crime types (e.g., from 40-50 percent in some hot spots). In the East and West Sectors, the crime declines were notably different from crime patterns in the matched comparison hot spots. In the North Sector, crime declined significantly in both the targeted hot spots and the comparison hot spots. Taken together, these findings provide compelling evidence that the Lowell SPI led to substantial reductions in drug-related property crime. The Lowell SPI highlights the importance of accessing non-traditional data to extend the problem analysis process. The Lowell experience also demonstrates the importance of near-real time monitoring of the problem-solving model, with a focus on achieving alignment or fit between identified crime problems and response strategies. The emphasis on congruence between problems and responses can allow law enforcement agencies to avoid "shallow" problem solving, which has often emerged in problem-oriented policing projects and can limit the potential for successful crime reduction. Details: Arlington, VA: CNA Analysis & Solutions, 2014. 18p. Source: Internet Resource: Accessed June 11, 2014 at http://www.cna.org/sites/default/files/research/SPILowellSpotlight.pdf Year: 2014 Country: United States URL: http://www.cna.org/sites/default/files/research/SPILowellSpotlight.pdf Shelf Number: 132441 Keywords: Crime Hot-SpotsDrug Abuse and CrimeGeospatial AnalysisProblem-Oriented Policing (Massachusetts)Property Crime |
Author: United Nations Institute for Training and Research Title: UNOSAT Global Report on maritime piracy: A geospatial analysis 1995-2013 Summary: This global report on maritime piracy has identified several important trends related to maritime security. Based on a refined and detailed analysis of primarily data from International Maritime Organization (IMO) Global Integrated Shipping Information System (GISIS) "Piracy and Armed Robbery" module UNITAR has been able to explore how trends in geospatial patterns and severity of reported piracy incidents are developing, from 1995 to 2013. Some detailed geospatial analyses focus on the period 2006-2013 due to improved records for geo-locating incidents. Our analysis includes the added cost of piracy for the maritime industry at a global level and how these are linked to anti-piracy initiatives. Furthermore, costs related to paid ransoms and effects on the local economy in piracy land-bases are explored. There are two areas where significant trends in piracy activities are observed: the Western Indian Ocean, including the Gulf of Aden, and the Gulf of Guinea. In other areas, notably eastern Indian Ocean, including the Malacca Strait, and in South America, no major trends are observed. While activities in South America are relatively minor, piracy in the Malacca Strait continues to be a major disruptior for safe routes in the eastern Indian Ocean. Details: Geneva: United Nations Institute for Training and Research, 2014. 40p. Source: Internet Resource: Accessed April 1, 2015 at: http://unosat.web.cern.ch/unosat/unitar/publications/UNITAR_UNOSAT_Piracy_1995-2013.pdf Year: 2014 Country: International URL: http://unosat.web.cern.ch/unosat/unitar/publications/UNITAR_UNOSAT_Piracy_1995-2013.pdf Shelf Number: 135104 Keywords: Geospatial AnalysisMaritime CrimeMaritime PiracyMaritime SecurityPirates/PiracyRansoms |
Author: Magalingam, Pritheega Title: Complex network tools to enable identification of a criminal community Summary: Retrieving criminal ties and mining evidence from an organised crime incident, for example money laundering, has been a difficult task for crime investigators due to the involvement of different groups of people and their complex relationships. Extracting the criminal association from enormous amount of raw data and representing them explicitly is tedious and time consuming. A study of the complex networks literature reveals that graph-based detection methods have not, as yet, been used for money laundering detection. In this research, I explore the use of complex network analysis to identify the money laundering criminals' communication associations, that is, the important people who communicate between known criminals and the reliance of the known criminals on the other individuals in a communication path. For this purpose, I use the publicly available Enron email database that happens to contain the communications of 10 criminals who were convicted of a money laundering crime. I show that my new shortest paths network search algorithm (SPNSA) combining shortest paths and network centrality measures is better able to isolate and identify criminals' connections when compared with existing community detection algorithms and k-neighbourhood detection. The SPNSA is validated using three different investigative scenarios and in each scenario, the criminal network graphs formed are small and sparse hence suitable for further investigation. My research starts with isolating emails with 'BCC' recipients with a minimum of two recipients bcc-ed. 'BCC' recipients are inherently secretive and the email connections imply a trust relationship between sender and 'BCC' recipients. There are no studies on the usage of only those emails that have 'BCC' recipients to form a trust network, which leads me to analyse the 'BCC' email group separately. SPNSA is able to identify the group of criminals and their active intermediaries in this 'BCC' trust network. Corroborating this information with published information about the crimes that led to the collapse of Enron yields the discovery of persons of interest that were hidden between criminals, and could have contributed to the money laundering activity. For validation, larger email datasets that comprise of all 'BCC' and 'TO/CC' email transactions are used. On comparison with existing community detection algorithms, SPNSA is found to perform much better with regards to isolating the sub-networks that contain criminals. I have adapted the betweenness centrality measure to develop a reliance measure. This measure calculates the reliance of a criminal on an intermediate node and ranks the importance level of each intermediate node based on this reliability value. Both SPNSA and the reliance measure could be used as primary investigation tools to investigate connections between criminals in a complex network. Details: Melbourne: School of Mathematical and Geospatial Sciences, College of Science, Engineering and Health, RMIT University, 2015. 129p. Source: Internet Resource: Dissertation: Accessed May 13, 2017 at: https://researchbank.rmit.edu.au/eserv/rmit:161407/Magalingam.pdf Year: 2015 Country: Australia URL: https://researchbank.rmit.edu.au/eserv/rmit:161407/Magalingam.pdf Shelf Number: 145462 Keywords: Criminal InvestigationCriminal NetworksGeospatial AnalysisMoney LaunderingNetwork AnalysisOrganized Crime |