scholarly journals ECOLOGY OF CRIME IN URBAN AND SUBURBAN AREA – SPATIAL PATTERNS OF CRIME IN NIS (SERBIA)

2020 ◽  
pp. 037
Author(s):  
Dušan Stanković
Keyword(s):  
Empirical Research ◽  
Spatial Patterns ◽  
Routine Activity Theory ◽  
Point Pattern ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
The Impact ◽  
The City ◽  
Spatial Point Pattern Test ◽  
Crime Pattern

Ecological perspective in criminology has been introduced with the cartographic school at the beginning of criminology science. Ecology theory of crime has been developed in the city of Chicago and it is followed by the routine activity theory, crime pattern theory, and rational choice theory. The impact of the ecological theory in research of crime is noticeable in today's studies too. Modern scientists, researchers, and practitioners are studying crime using the geographic information system, mapping crime, using statistical and geostatistical methods. With the aim to study spatial patterns of crime, empirical research of the poverty and violent criminal acts committed in the City of Nis, Republic of Serbia, during the years 2008, 2013 and 2018. All the cases are geocoded into spatial units that represent urban and suburban areas in Nis. A descriptive statistic is used to identify areas where crime happens the most. The application of Andersen’s Spatial Point Pattern Test is used to check the hypothesis that spatial crime pattern is stable over time. This hypothesis is not confirmed and it is found that crime move from the city core towards cities’ urban and suburban settlements. The results from the empirical research are of scientific and practical value. This kind of spatial analysis is one of the first in Serbia and Balkans, and the application of the Spatial Point Pattern Test is very first in this region. The results could be useful when creating security strategies and policies to prevent crime by the police, decision-makers, and others.

The Spatial Effect of Police Foot Patrol on Crime Patterns: A Local Analysis

2019 ◽  
Vol 63 (8) ◽  
pp. 1446-1464
Author(s):  
Martin A. Andresen ◽  
Jen-Li Shen
Keyword(s):  
Local Analysis ◽  
Point Pattern ◽  
Data Sets ◽  
Spatial Point Pattern ◽  
Foot Patrol ◽  
Spatial Point ◽  
Spatial Similarity ◽  
Treatment Data ◽  
Spatial Point Pattern Test ◽  
Crime Pattern

A foot patrol program was implemented in Lower Lonsdale, British Columbia, in the summer of 2010 and continues today. As a part of assessing the foot patrol’s effect on crime in the neighbourhood, the spatial similarity was examined by comparing the crime pattern before the foot patrol initiative (2007-2009) with the crime pattern during the foot patrol program (2010-2012). Considering these baseline and treatment data sets and a spatial point pattern test, the spatial similarity between two data sets is analyzed. In general, the continued presence of foot patrol appears to have created a concentration of crime in specific areas, rather than a diffusion effect. The areas that continued to experience increased crime during foot patrol presence were often in the catchment area, suggesting displacement does occur, or along the border between the catchment and primary patrol area.

scholarly journals Spatial point-pattern analysis as a powerful tool in identifying pattern-process relationships in plant ecology: an updated review

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mariem Ben-Said
Keyword(s):  
Spatial Patterns ◽  
Pattern Analysis ◽  
Biotic Interactions ◽  
Plant Ecology ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Summary Statistics ◽  
Spatial Point Pattern ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis

Abstract Background Ecological processes such as seedling establishment, biotic interactions, and mortality can leave footprints on species spatial structure that can be detectable through spatial point-pattern analysis (SPPA). Being widely used in plant ecology, SPPA is increasingly carried out to describe biotic interactions and interpret pattern-process relationships. However, some aspects are still subjected to a non-negligible debate such as required sample size (in terms of the number of points and plot area), the link between the low number of points and frequently observed random (or independent) patterns, and relating patterns to processes. In this paper, an overview of SPPA is given based on rich and updated literature providing guidance for ecologists (especially beginners) on summary statistics, uni-/bi-/multivariate analysis, unmarked/marked analysis, types of marks, etc. Some ambiguities in SPPA are also discussed. Results SPPA has a long history in plant ecology and is based on a large set of summary statistics aiming to describe species spatial patterns. Several mechanisms known to be responsible for species spatial patterns are actually investigated in different biomes and for different species. Natural processes, plant environmental conditions, and human intervention are interrelated and are key drivers of plant spatial distribution. In spite of being not recommended, small sample sizes are more common in SPPA. In some areas, periodic forest inventories and permanent plots are scarce although they are key tools for spatial data availability and plant dynamic monitoring. Conclusion The spatial position of plants is an interesting source of information that helps to make hypotheses about processes responsible for plant spatial structures. Despite the continuous progress of SPPA, some ambiguities require further clarifications.

scholarly journals Spatial point pattern analysis of urban retail stores: the case of twelve large- and medium-sized Greek cities

2020 ◽  
Vol 11 (4) ◽  
pp. 36-63
Author(s):  
Michail-Christos TSOUTSOS ◽  
◽  
Yorgos Photis
Keyword(s):  
Spatial Patterns ◽  
Pattern Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Retail Stores ◽  
High Population Density ◽  
Spatial Point Pattern ◽  
Professional Activities ◽  
Spatial Point ◽  
Spatial Point Pattern Analysis

The retailers’ profitability and the consumers’ satisfaction depend on finding the optimal location for a retail store. When considering the stores’ spatial distribution, business potential can be understood and a squandering planning of resources can be avoided. In this paper we identify the spatial patterns of retail stores located in the traditional commercial centers of twelve large -and medium-sized Greek cities, aiming to explain why such patterns exist. The type of retail activities was determined using the image of the ground-floor stores provided by the Google Street View (GSV) service and thus 7322 stores were recorded in a geodatabase as point features. The results reveal that the retail stores’ distribution has a clustered and random spatial pattern at least in one city, where the high population density and the increase in rental prices of premises for professional activities constitute the factors that form these spatial patterns respectively.

scholarly journals The impact of strict measures as a result of the COVID-19 pandemic on the spatial pattern of the demand for police. Case study Antwerp (Belgium)

2021 ◽  
Author(s):  
Maite Dewinter ◽  
Philipp M. Dau ◽  
Christophe Vandeviver ◽  
Frank Witlox ◽  
Tom Vander Beken
Keyword(s):  
Spatial Pattern ◽  
Radical Change ◽  
Point Pattern ◽  
Spatial Point Pattern ◽  
Daily Lives ◽  
Daily Work ◽  
The Impact ◽  
Street Segments ◽  
Spatial Point Pattern Test

COVID-19 impacts the daily lives of millions of people. This radical change in our daily activities affected many aspects of life, but acted as well as a natural experiment for research into the spatial distribution of 911 calls. We analyse the impact of the COVID-19 measures on the spatial pattern of police interventions. Crime is not uniformly distributed across street segments, but how does COVID-19 affect these spatial patterns? To this end, a proportion differences spatial point pattern test is applied to compare the similarity of the patterns of incidents before, during, and after the first lockdown in Antwerp, Belgium. With only essential mobility being allowed, the emergency call pattern has not significantly changed before, during or after this lockdown, however, a qualitative shift in police officer’s daily work may have had an effect on the daily operation of the Antwerp police force.

Spatial epidemiology of hemorrhagic fever with renal syndrome and rodent hantavirus infection in Guangzhou city, China: lessons learned from a study with long-term surveillance data

2019 ◽  
Author(s):  
Dehao Chen ◽  
Shouyi Chen ◽  
Song Liang ◽  
Jianmin Xu ◽  
Zhicong Yang ◽  
...  
Keyword(s):  
Hemorrhagic Fever ◽  
Temporal Analysis ◽  
Surveillance Data ◽  
Point Pattern ◽  
Hantavirus Infection ◽  
Spatial Point Pattern ◽  
Period Prevalence ◽  
Guangzhou City ◽  
Spatial Point ◽  
The City

Abstract Background: Though Guangzhou city is not a region with a high burden of hemorrhagic fever with renal syndrome (HFRS) comparing with other areas in China, outbreaks still occur in the city due to the existence of urban rodents and a large urban population at risk. In this study, descriptive temporal analysis and geographic information system (GIS)-based spatial analysis were performed on reported HFRS cases and rodent surveys with the goals of identifying risk areas for public health interventions and presenting the methods and outcomes of the surveillance that can be studied by similar urban settings. Methods: Period prevalence and the number of positive cases at different geographical scales of the city during 2008-2016 were calculated and summarized based on HFRS and rodent-borne disease surveillance data. Spatial point pattern analyses were conducted to describe global and local clustering effects of different measurements of human HFRS and rodent hantavirus at old-town and whole-city levels. Results: Geographical distributions of HFRS cases and traps with hantavirus antibody-carrying rodents from 2008 to 2016 were mapped at the city and old-district levels in the aspect of the crude number of positive cases and period prevalence. The weighted K-function suggested that no global clustering effect existed for both the rodent and human cases in different scales of the city. Using Gi*(d) statistic, 22 significant local clusters of high infection (P<0.05) with different radius were discovered for the human and rodent surveillance data, and a zoonotic link was built based on the overlay of clusters of the two species. Also, the seasonal occurrence of HFRS presented a summer peak in the city. Conclusion: The applications of descriptive temporal analysis, GIS and spatial point pattern analysis, offer ways to quantify zoonotic hantavirus risks across different times and spatial scales and to further recognize putative environmental determinants potentially influential in increased disease risks. The study also fills information gaps about hantavirus surveillance in the non-endemic region, and the methods used for rodent survey in China for controlling HFRS, which is not well documented.

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