A Crime Prevention System in Spatiotemporal Principles With Repeat, Near-Repeat Analysis and Crime Density Mapping: Case Study Turkey, Trabzon

2018 ◽  
Vol 64 (14) ◽  
pp. 1820-1835 ◽  
Author(s):  
Gamze Bediroglu ◽  
Sevket Bediroglu ◽  
H. Ebru Colak ◽  
Tahsin Yomralioglu
Keyword(s):  
Kernel Method ◽  
Crime Data ◽  
Density Mapping ◽  
Repeat Analysis ◽  
Crime Type ◽  
Density Maps ◽  
Prevention System ◽  
Standardization Process ◽  
Near Repeat

In this study, we investigated crime events with repeat and near-repeat analysis for Turkey’s Trabzon city’s crime data after standardization process on raw crime data. First, a new crime geodatabase model was created. All types of recorded crime data for events between the years 2010 and 2014 were standardized, generalized, and Geo-referenced. We gave certain locations to crime events with geocoding techniques. Then, we created density maps of crime events with Kernel method in Geographic Information Systems (GIS). Repeat and near-repeat methods were tested on Burglary crime type in this geodatabase. Studies focused to applying prediction analysis besides showing current situation. These predictive analyses may be applied for all the security, intelligence, or defense departments at local, national, or international levels.

The sensitivity of repeat and near repeat analysis to geocoding algorithms

2020 ◽  
pp. 101721
Author(s):  
Cory P. Haberman ◽  
David Hatten ◽  
Jeremy G. Carter ◽  
Eric L. Piza
Keyword(s):  
Repeat Analysis ◽  
Near Repeat

scholarly journals A Few GIS Clarifications on Tornado Density Mapping

2016 ◽  
Vol 55 (2) ◽  
pp. 283-296 ◽  
Author(s):  
Yongxin Deng ◽  
Brendan Wallace ◽  
Derek Maassen ◽  
Johnathan Werner
Keyword(s):  
Uncertainty Modeling ◽  
The United States ◽  
Distance Decay ◽  
Geographical Information ◽  
Density Mapping ◽  
Probability Mapping ◽  
Density Maps ◽  
Distance Weighted ◽  
Inverse Distance ◽  
Eastern Half

AbstractA geographical information system (GIS) perspective is taken to examine conceptual and methodological complications present in tornado density and probability mapping. Tornado density is defined as the inverse-distance-weighted count of tornado touchdown points or tornado-affected cells within a neighborhood area. The paper first adds a few geographic elements into the tornado definition and then characterizes tornado density as a density field in GIS that depends on predefined, modifiable areas to exist. Tornado density is therefore conceptually distinguished from both individual tornadoes and tornado probability. Three factors are identified to be vital in tornado density mapping: the neighborhood size, the distance decay function, and the choice of tornado properties. Correspondingly, 12 neighborhood sizes ranging from 20 to 360 km are tested, four distance decay functions are compared, and two tornado properties—tornado touchdown locations and pathlengths—are separately incorporated in mapping. GIS interpretations, clarifications, and demonstrations are provided for these factors to reach a thorough understanding of how the factors function and affect the resultant tornado density maps. Historical tornado data of the eastern half of the United States from 1973 to 2013 are used in these demonstrations. Uncertainty and propagation analyses are recommended for future tornado density and probability mapping, and a Monte Carlo simulation using tornado pathlength data is conducted as an example of uncertainty modeling. In all, tornado density mapping is diagnosed as a largely subjective activity, and the mapper needs to make multiple choices according to the mapping purpose, scale, and the involved tornado record data.

Construction of Urban Flooding Prevention System under “One City, One Executor, and One Network” Model: Case Study of Kunming, China

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
Fei Zhao ◽  
Jingzhi Cai ◽  
Hongyun Zeng ◽  
Zhiqiang Xie ◽  
Qingyun Du ◽  
...  
Keyword(s):  
Network Model ◽  
Urban Flooding ◽  
Model Case ◽  
Prevention System

scholarly journals Crime mapping features

2020 ◽  
Vol 79 (4) ◽  
pp. 66-72
Author(s):  
О. В. Манжай ◽  
А. О. Потильчак
Keyword(s):  
Theoretical Basis ◽  
Hot Spot ◽  
Kernel Density ◽  
Crime Mapping ◽  
Density Mapping ◽  
Criminal Intelligence ◽  
Symbol Mapping ◽  
Near Repeat ◽  
Artificial Intelligence Systems ◽  
Clinical Strategy

In this paper tools, organization and tactics of crime mapping are analyzed. The directions of application of mapping for maintenance of public safety and order, in criminal intelligence process, etc. are outlined. The domestic experience of mapping is briefly analyzed. The main goals that are achieved with the use of mapping are defined. Features of visualization of criminogenic cells are revealed. Pin mapping features (when points which symbolize a certain event are placed on the map on the corresponding coordinates) are outlined. Kernel density mapping is described, which makes it much easier to detect criminogenic foci, as hot-spot maps clearly reflect the concentration of certain events in the region. A method of mapping using proportional symbol mapping is disclosed when the increase in the size of the symbol denoting a point on the map is proportional to the increase in the number of events or other parameters at these coordinates. The building of geographical profiles of criminals is briefly described. The theoretical basis of mapping for the prediction of crimes is outlined. Prediction strategies based on equations and machine calculations and actuarial strategies based on expertise and clinical strategy are analyzed. Considerations are given to the appropriateness of applying appropriate strategies in different countries. The phenomenon of near repeat patterns is studied. Some software solutions for the implementation of the tasks of mapping criminal manifestations and the use of artificial intelligence systems for this purpose are described. Examples are given. It is noted that the use of cartography to prevent and predict crimes in Ukraine is in its infancy. Some solutions are proposed that could improve the situation in the field of crime mapping in Ukraine.

Explosive violence: A near-repeat study of hand grenade detonations and shootings in urban Sweden

2019 ◽  
Vol 17 (5) ◽  
pp. 661-677 ◽  
Author(s):  
Joakim Sturup ◽  
Manne Gerell ◽  
Amir Rostami
Keyword(s):  
Urban Areas ◽  
Temporal Analysis ◽  
Descriptive Data ◽  
Repeat Analysis ◽  
Disadvantaged Neighbourhoods ◽  
Spatio Temporal ◽  
Criminal Groups ◽  
Near Repeat ◽  
Forms Of Violence ◽  
Observation Period

Hand grenade attacks have increasingly been reported in Sweden. However, to date no research on the topic exists. The present study aims to describe the illegal use of hand grenades and to test its spatio-temporal relationship with gun violence to explore whether the two forms of violence are connected. Data were collected for the years 2011 to 2016 from the Swedish police and from open sources about hand grenade detonations, which were considered alongside shootings as two types of violence commonly attributed to criminal groups. Descriptive data and trends are presented and spatio-temporal analysis of near-repeat patterns was performed using a near-repeat calculator. All in all, there were 77 incidents of detonated hand grenades in Sweden during the six-year observation period, in which nine individuals were injured and one killed. The number of incidents increased, with about half of the them occurring during the last year. A near-repeat analysis was performed on shootings ( N = 1048) and hand grenades ( N = 55) in Stockholm, Gothenburg and Malmö. The shootings exhibit a strong component of near-repeat patterns, but adding hand grenades to the analysis did not strengthen the patterns, suggesting that the two types of violence only partially share spatio-temporal patterns. The study confirms an increase in the use of hand grenades in Sweden, although the reason for the increase is unknown. The increase does fit with the overall changing pattern in violence in urban areas in Sweden, which broadly tends to be attributed to criminal groups in disadvantaged neighbourhoods.

scholarly journals Resource and service discovery in SOAs: A P2P oriented semantic approach

2011 ◽  
Vol 21 (2) ◽  
pp. 285-294 ◽  
Author(s):  
Giuseppe Di Modica ◽  
Orazio Tomarchio ◽  
Lorenzo Vita
Keyword(s):  
Service Discovery ◽  
Semantic Approach ◽  
Service Oriented Architectures ◽  
Technological Convergence ◽  
Service Oriented ◽  
Standardization Process ◽  
System Prototype ◽  
Grid Resources ◽  
Administrative Domains

Resource and service discovery in SOAs: A P2P oriented semantic approachAn intense standardization process is favouring the convergence of grids and Service Oriented Architectures (SOAs). One of the benefits of such technological convergence is that grid resources and applications can be virtualized by services and offered through the SOA paradigm. In the broad and interoperable scenarios enabled by the SOA, involving the participation of several grid infrastructures across many administrative domains, service discovery can be a serious issue. In this paper we present a P2P-based infrastructure that leverages semantic technologies to support a scalable and accurate service discovery process. The key concept of the presented idea is the creation of an overlay network organized in several semantic groups of peers, each specialized in answering queries pertaining to specific applicative domains. Groups are formed by clustering together peers offering services that are semantically related. The architecture details of the proposed solution are presented. A system prototype has also been implemented and validated through a case study deployed on the PlanetLab testbed.

scholarly journals Analyses of Crime Patterns in NIBRS Data Based on a Novel Graph Theory Clustering Method: Virginia as a Case Study

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Peixin Zhao ◽  
Marjorie Darrah ◽  
Jim Nolan ◽  
Cun-Quan Zhang
Keyword(s):  
Graph Theory ◽  
Reporting System ◽  
Test Case ◽  
Clustering Method ◽  
Crime Patterns ◽  
Crime Type ◽  
Crime Types

This paper suggests a novel clustering method for analyzing the National Incident-Based Reporting System (NIBRS) data, which include the determination of correlation of different crime types, the development of a likelihood index for crimes to occur in a jurisdiction, and the clustering of jurisdictions based on crime type. The method was tested by using the 2005 assault data from 121 jurisdictions in Virginia as a test case. The analyses of these data show that some different crime types are correlated and some different crime parameters are correlated with different crime types. The analyses also show that certain jurisdictions within Virginia share certain crime patterns. This information assists with constructing a pattern for a specific crime type and can be used to determine whether a jurisdiction may be more likely to see this type of crime occur in their area.

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