Use of Geographically Weighted Regression on Ecology of Crime, Response to Hurricane in Miami, Florida

Walker, William C.; Sim, Sunhui; Keys-Mathews, Lisa

doi:10.1007/978-94-017-8757-4_12

Cited by 10 publications

(12 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Areas with high unemployment, high population density, and/or which lacked a motor-vehicle and central heating system had higher likelihood for burglary. This is consistent with previous studies that attributed high burglary risk with populous areas [29,30] and high vulnerability of households with insufficient controls [13,17,45]. It also agrees with the hypothesis related to increased risk within unstable institutions [16,17].…”

Section: Discussionsupporting

confidence: 93%

“…This line of investigation pursues the area-based socioeconomic and land-use factors which are likely to promote or hinder the development of crime [2]. Sociological studies have investigated links between burglary and concentrated disadvantage [22,25], high population density [29,30], disadvantage [1,20,25], and residential instability [31][32][33], and many significant associations have been found. In an extensive study of 352 U.S. cities over 30 years, Hipp [34] discovered that the level of economic stratification had significant implications for burglary.…”

Section: Area-based Burglary Influencesmentioning

confidence: 99%

See 1 more Smart Citation

Modeling Spatial Interactions between Areas to Assess the Burglary Risk

Mburu

Bakillah

2016

IJGI

View full text Add to dashboard Cite

It is generally acknowledged that the urban environment presents different types of risk factors, but how the structural effects of areas influence the risk levels in neighboring areas has been less widely investigated. This research assesses the local effects of burglary contributory factors on burglary over small areas in a large metropolitan region. A comparative framework is developed for analyzing the effects of geographic dependence on burglary rates, and for assessing how such dependence conditions the community context and the urban land use. A local indicators spatial autocorrelation analysis assesses burglaries over five years (2011)(2012)(2013)(2014)(2015) to identify risk clusters. Thereafter, effects of different variables (e.g., unemployment, building density) on burglary frequency are estimated in a series of regression models while controlling for changes in the risk levels of nearby surrounding areas. Results uncover strong evidence that the configuration of the surroundings influences risk. After controlling for area-based interaction, patterns are identified that contrast with the previous literature, such as lower burglary frequency in areas with higher tenancy in social housing units. Together the findings demonstrate that the spatial arrangement of areas is as crucial as contextual crime factors, particularly when assessing the risk for small areas.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Area-based Burglary Influencesmentioning

confidence: 99%

Modeling Spatial Interactions between Areas to Assess the Burglary Risk

Mburu

Bakillah

2016

IJGI

View full text Add to dashboard Cite

show abstract

“…For instance, in Ref. [36], the authors subtract the 'typical' (or average) total crime value, from the 'high period' (i.e., with the biggest crime scores) crime value, to represent changes between the 'typical' daily crime values and the 'highest' daily crime values. When dealing with risk related topics, the natural logarithm of the density ratio is an advised choice [37]:…”

Section: Methods For Landmines and Erw Risk Mappingmentioning

confidence: 99%

Hazard Mapping of Landmines and ERW Using Geo-Spatial Techniques

Alegria

Zimányi

Cornelis³

et al. 2017

J Remote Sensing & GIS

View full text Add to dashboard Cite

Landmines and Explosive Remnants of War (ERW) continue to represent a significant nuisance for society in affected countries. Coping with humanitarian and development activities, mine action aims at both, reducing the impacts of the presence of landmines/ ERW on the population, and ultimately returning cleared land to the communities. These are the main tasks of mine action decision makers. This study combines landmine/ERW contamination data with explanatory variables that contain information about underlying targets. They are integrated into a risk mapping framework using Geographic Information Systems with other information sources, such as remote sensing. The aim of this paper is to provide insights into the populations and/or locations at risk caused by landmine and ERW impacts on a broad and local scale. Thus, the concept of 'hotspots' is particularly useful because it provides a visual representation of exposure, aided by a geo-spatial representation of 'priority areas for mine action planners to focus on. We apply the Kernel Density Estimator (KDE) to derive such 'hotspots'. KDE is proposed as the basis to define landmine and ERW hazard, vulnerability, and element-at-risk maps, which enable producing a final output, the landmine/ERW risk map. This is accomplished by using an adaptive kernel bandwidth for datasets with highly heterogeneous spatial distributions, and a problem specific method for generating point samples from polygon data, before using them as inputs for KDE. The geo-statistical model presented here is a time-and-cost-efficient method to construct a landmine risk map, that is as representative as those produced by mine action actors. It can be used as a complement to the risk area maps made by these actors because they are slightly different but show a large degree of overlap. Moreover, the method helps revealing the variables which are the most linked to landmine/ERW-related events in the study area.

show abstract

“…In crime ecology, the physical and societal surroundings play a significant role to comprehend the chronological blueprint of crime (Walker et al 2014). The results of a study carried out by Glaeser et al (1996) reveals that social interaction, strong ancestral backgrounds, marital position, regularity of visiting any religious place have considerable impinge on the possibility of involving the individual in immoral conducts as well as regional variation of crime incidences.…”

Section: Regional Stereotype Of Crimesmentioning

confidence: 99%

Ethnicity and Multi-Party Democracy: The Nigerian Experience

Jiboku¹

2018

JSS

View full text Add to dashboard Cite

Society is an organization of heterogeneous entities and all social orders countenance the inevitable and complex dilemma of crime. The variation of its occurrence is determined by the amalgamation of miscellaneous socio-cultural, economic and others aspect of its surrounding. The present paper is based on secondary data derived from National Crime Records Bureau, Ministry of Home Affairs under Government of India and other sources and agencies. Crime has been defined under Indian Penal Code (IPC) and the ten categories that are; murder, rape, kidnapping and abduction, dacoity, robbery, burglary, theft, riots, cheating and dowry deaths have been used for the spatial pattern of incidence of crime at the district level. The interrelationship of crime and its determinants has been analyzed by Pearson's correlation technique. Kendall's ranking method is applied for calculation of the composite index. The study reveals the overall increase in incidences of crime in the study area and as per composite score, the maximum criminal activities occur in the surrounding of the National Capital Region because these areas are experiencing rapid industrial and economic development as well as change in social structure. The correlation statistic also verified that crime and its determinants form a chain reaction and facilitate the growth of each other.

show abstract

Use of Geographically Weighted Regression on Ecology of Crime, Response to Hurricane in Miami, Florida

Cited by 10 publications

References 20 publications

Modeling Spatial Interactions between Areas to Assess the Burglary Risk

Modeling Spatial Interactions between Areas to Assess the Burglary Risk

Hazard Mapping of Landmines and ERW Using Geo-Spatial Techniques

Ethnicity and Multi-Party Democracy: The Nigerian Experience

Contact Info

Product

Resources

About