AEGAEUM JOURNAL ISSN NO: 0776-3808
DEMOGRAPHIC PARAMETERS AND CRIMES IN TIRUCHIRAPPALLI CITY, TAMIL NADU USING GEO- STATISTICAL APPROACH
P. Mary Santhi 1, S. Balaselvakumar 2 & K. Kumaraswamy 3
1Research Scholar, 2Assistant Professor & 3Emeritus Professor 1&2 Department of Geography, Periyar E.V.R. College (Autonomous), Tiruchirappalli – 620 023 3Department of Geography, Bharathidasan University, Tiruchirappalli – 620 024, Affiliated to Bharathidasan University, Tiruchirappalli – 620 024
ABSTRACT: The purpose of this study is to understand the relationship between demographic parameters and crimes in Tiruchirappalli city. Major crimes of six variableshave been associated with 2011 census of population, sex ratio, literacy ratio and work participation rate of the city, then with the help of geo-statistics technique four components have been derived andmapped namely Heinous Crimes and Total Population-I, Sex Ratio and Felony-II, Occupation and Literacy-III and Murder for Gain-IV. Woraiyur police station followed by Fort police station has prominently associated with the components of I & II and Sessions Court, Edamalaipattipudur, Thillainagar and Government Hospital police stations have associated with the componentof IV. The occurrences of crimes such as robbery, theft and dacoity were of great concern, especially in Srirangam range.
KEYWORDS: Crime Occurrences, Demographic Parameters, Statistical Components, Police Stations, Geoinformatics. 1.INTRODUCTION
Crime is an issue of global stability that hampers economic growth. The types of crime and the
intensity of crime rate may differ from country to country, region to region and from time to time. Though
crimes of one sort or another must have taken place even in prehistoric societies, the intensity and
diversity of the crimes have increased multiple today. Over the decades, the crime rate has increased
phenomenally in developed and in developing countries on account of overpopulation, corruption, lack of
internal peace and security, political turmoil and environmental factors. Technological developments have
further added sophistication and perfection to the mode of crimes. Countries rife with such problems have
a strikingly high crime rate due to these socio-economic factors. Crimes create a feeling of insecurity
among citizens and cast a shadow over a country and its people.The risk of suffering a crime is not
uniformly distributed over a region (Johnson 2010) and nor is it uniformly distributed across members of
the same community (Grove et al. 2012), some population groups and regions are more affected by crime
than others (Farrell 2015). Identifying the demographic components of crime is a prerequisite to deciding
for the social rank of a city.
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Demographic factors and criminal phenomena was applied byLi and Juhola 2013; Li
2014;hierarchical linear (multilevel) models (Beirne 1987); ecometrics of crime measurement
(Raudenbush and Sampson 1999); trajectory models for criminal development of individuals (Nagin
1999);crime trajectories model for geographical entities (Griffiths and Chavez 2004; Weisburd et al.
2004); spatial econometrics (Anselin 1988); link between communities and crime (Bursik and
Grasmick1993); economic factors (Li &Juhola, 2015); crime risk estimation with suburban population
(Lucy Mburu and Marco Helbich 2014); socio-economic and location of neighbourhood burglary rates
(Martin 2002); multivariate spatial statistics for crime pattern (Friendly 2007); relationship between
population characteristics and crime rate Vijaykumar and Chandrasekar2011; to test the super linear
relationship between crime and population (Bettencourt, et al. 2007a); historical developments (Li
&Juhola, 2014b); particular offence, homicide and its social context to correlate occurrences of
relationship(Li et al., 2015); urban population and unemployment rate with crimes to find out whether
these factors closely related or quite irrelevant to crimes(Li and Juhola 2014a); demographic factors such
as age, sex and race to understand the variation in crime rates with regard to temporal and spatial
elements bySouth &Messner 2000.Geoinformatics were used for crime mapping, direction, hotspots, type
of hotspot, the proximity of crimes to police stations, displacement of crime across time, the crime rate of
each ward and the social-economic characteristics of the city by Ravi Sharma et al. 2016;Ratcliffe and
McCullagh 2001; Harries 1999; Murray et al. 2001 and Mafumbabete et al. 2019. The above studies have
analysed demographic parameters and crime types. Therefore, this present research also has focused to
understand the relationship between demographic parameters and crimes by using Geoinformatics along
with the statistical method.
2.STUDY AREA
Tiruchirappalli city’s base map had been framed from the Survey of India (SOI) Toposheets Nos.
58 J/9, 10, 13 and 14. The city lies between the latitudes 10° 43' 40''- 10° 53' 00'' North and the longitudes
78° 38' 14'' - 78° 48' 50'' East (Map. 1).The Cauvery delta begins to form 16 km west of the city where the
river splits into two the Cauvery and the Kollidam to form the island of Srirangam.
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The topography of Tiruchirappalli city is relatively flat and its average elevation is 88 metres
from mean sea level. Some isolated hillocks grow beyond the surface, the topmost of which is the
Rockfort. Its projected age is 3,800 million years and it is marked as one of the ancient rocks in the
world. Other prominent hillocks include the Golden Rock, Khajamalai, Uyyakondan
Thirumalai and Thiruverumbur.
The river Cauvery and its distributary Kollidam facilitate Tiruchirappalli city also the city is
fertilised by the Uyyakondan, Kudamuritti and Koraiyar canal. The land closely adjoining the Cauvery
River, which crosses Tiruchirappalli city from west to east, consists of fertile alluvial soil deposits on
which crops like paddy, banana and sugarcane are cultivated and in dry soil, finger millet and maize are
cultivated nearby areas.
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3.DATABASE AND METHODOLOGY
The current study is based on secondary data sources.Thecrimes, which have been reported and
registered in the FIRs of police stations, were collected from the City Crime Records Bureau (CCRB)
Tiruchirappalli City Commissioner of Police Office, for the years 2012 to 2017.Only those major crimes
(murder, murder for gain, dacoity, robbery, burglary and theft) a total of 560 as classified by CCRB have
been incorporated by statistics factor analytical technique with the 2011 census of population, sex ratio,
literacy ratio, and work participation rate collected from the City Municipal Cooperation.
About 10 variables for major crimes have been used to extract the factors by using statistical
factor analysis. Based on the Eigenvalues and cumulative percentage of variance, four components have
been identified, mapped and analysed by adoptingGeoinformatics techniques in the city. 4.RESULT AND DISCUSSION
4.1FACTOR ANALYSIS OF MAJOR CRIMES
Factor analysis was conducted on the major crime viewpoint in Tiruchirappalli city to determine
the factors that represent the data best. Simple components analysis was carried out to study the
Eigenvalues for all scales. Reliability of the factors was governed by calculating Cronbach alpha
coefficients. All factors were arrived at having the reliability of 0.734 which is greater than 0.60 (α>0.60).
Table 1 KMO and BARTLETT'S test statistics for major crimes in Tiruchirappalli city.
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .344 Approx. Chi-Square 58.063 Bartlett's Test of Sphericity df 45 Sig. .002
The results of the factor analysis on the major crime in the study area were found to have four
factors. The cumulative variance clarified by the factors mentioned above was found to be 78.97%.
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The overall significance of the correlation matrix with Bartlett’s test, considering the data in this
research, the correlations, when taken overall, are significant at the 0.002 level according to table 1 which
is 58.063 for the major crime in the city.
Data about these 10 variables for each of the 14 police stations have been entered and analysed
using SPSS 19.0 version to extract factors by using the Varimax method. The output of factor analysis is
obtained by principal component analysis and specifying the interpretation. There are two stages in factor
analysis. Stage-I is the factor withdrawal procedure, wherein the neutral is to pinpoint how many factors
are to be taken out from the statistics. The most popular method is called principal component analysis.
There is also a regulation of thumb based on the computation in Eigenvalue, to decide how many factors
to extract. The greater the Eigenvalue of a factor, the more is the amount of modification explicated by
the factor. Since four factors were taken out which is 78.97% of the variance was explained. It has been
found that the four factors acted together to account for 78.97% of the total variance (Table 2). Hence, the
number of variables is reduced from twenty-one to four underlying factors.
Table 2 Total Variance Explained (MC)
Extraction Sums Initial Eigenvalues of Squared Loadings Component Percentage Cumulative % of Cumulative Total (%) of Total % Variance % Variance 1 3.797 37.966 37.966 3.797 37.966 37.966 2 1.693 16.934 54.900 1.693 16.934 54.900 3 1.362 13.618 68.518 1.362 13.618 68.518 4 1.045 10.453 78.970 1.045 10.453 78.970
The first component accounts for 37.97% of the variance while the second component accounts
for 16.93% of the variance, the third component accounts about 13.62% of the variance and the fourth
component explains 10.45% of the variance.
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5. HEINOUS CRIMES AND TOTAL POPULATION COMPONENT-I
The analysis reveals that the major crime variables such as robbery, theft, burglary and dacoity
have loadings of 0.877, 0.784, 0.783 and 0.683 and the demographic parameter of the total population has
loadings of 0.798 on factor 1 indicating that it is a combination of these five variables and are called
‘Heinous Crimes and Total Population Component’.
Srirangam and Woraiyur police stations come under the very high category; K.K. Nagar and Fort
police stations come under a high category, Cantonment, Edamalaipattipudur, Golden Rock,
Ariyamangalam, Gandhi Market, Government Hospital and Thillainagar police stations belong to medium
category; and the remaining Sessions Court, Airport and Palakkarai police stations belong to low category
(Map 2).
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6. SEX RATIO AND FELONY COMPONENT – II
The major crime variable of murder has loadings of 0.828, and the demographic parameter of sex
ratio has loadings of 0.630 on factor 2 indicating that it is a mixture of these two variables and are called
‘Sex Ratio and Felony Component’.
Cantonment and Woraiyur police stations come under the very high category;
Edamalaipattipudur, Palakkarai, Gandhi Market, Fort and Government Hospital police stations come
under high category; K.K. Nagar, Golden Rock, Ariyamangalam and Thillainagar police stations belong
to medium category; and the remaining Sessions Court, Airport and Srirangam police stations belong to
low category (Map 3).
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7. OCCUPATIONAL AND LITERACY COMPONENT – III
The annexure V reveals that the demographic parameters- work participation rate and literacy
ratio have loadings 0.878 and 0.822 on factor 3 indicating that it is a combination of these two variables
and are called ‘Occupational and Literacy Component’.
K.K. Nagar police station comes under the very high category; Sessions Court, Golden Rock,
Cantonment, Airport, Palakkarai and Government Hospital police stations come under high category; Fort
police station belongs to medium category; and the remaining Edamalaipattipudur, Ariyamangalam,
Srirangam, Thillainagar, Gandhi Market and Woraiyur police stations belong to low category (Map 4).
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8.MURDER FOR GAINCOMPONENT – IV
The analysis reveals that the major crime variable of murder for gain has loadings of 0.927 on
factor 4 indicating that it is a combination of this variable and is called ‘Murder for Gain Component’.
Sessions Court, Edamalaipattipudur, Thillainagar and Government Hospital police stations come
under the very high category; K.K. Nagar and Fort police stations come under high category;
Cantonment, Golden Rock, Airport, Ariyamangalam and Woraiyur police stations belong to medium
category; and Palakkarai, Gandhi Market and Srirangam police stations belong to low category (Map 5). \
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CONCLUSION
Factor analysis was also conducted on major crimes with demographic parameters in
Tiruchirappalli city to determine the factors that represent the data best. It confirms four components for
major crimes such as Heinous Crimes and Total Population-I, Sex Ratio and Felony-II, Occupation and
Literacy-III, Murder for Gain-IV. Woraiyur and Fort police stations have associated withthe components
of Heinous Crimes and Total Population&Sex Ratio and Felonyand police stations of Sessions Court,
Edamalaipattipudur, Thillainagar and Government Hospital have associated with Murder for Gain
component. The occurrences of crimes such as robbery, theft and dacoity have been of great concern,
particularly in Srirangam range.
It reveals that the crime rate is marked more in highly populated areas with high sex ratio, literacy
ratio and work participation rate mainly in the police stations of K.K. Nagar, Woraiyur, Cantonment and
Srirangam. High demographic parameters recorded the maximum crime occurrences in residential,
commercial, market and temple areas of Chinnakammala Street, Nadu Street of Varaganeri, Gandhi
Market, Melapudur, Pudur four road, near Bishop Heber college, Senthaneepruram, Throwpathi Amman
Kovil Street, Beema Nagar,Thennur high road, Chaittram bus stand, railway station and suburban
railroad, Tharanallur, Ammamandapam, Sakthi Nagar near T.V. Kovil, Old bus stand Sirrangam,
Ponnagar, Karumandapam, Ponmalaipatti, BSNL tower office, P&T Colony-Mannarpuram, in front of
Kareem Kutty shop-TVS Tollgate and Kajamalai Colony.
The study reveals that the police force and the number of stations in the city (14) have not grown
in proportion to the growing population, inhabited areas and the number of occurrences of various crimes.
Therefore, it is suggested that the number of police stations and their force to be increased in proportion
to the population along with high-end security system in the northern part of the city of Srirangam range
especially in Woraiyur, the central part of Gandhi Market in Fort range and southwest of Cantonment in
Cantonment range.
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ACKNOWLEDGEMENT
We express our sincere thanks to Tiruchirappalli city Commissioner of Police for providing
necessary data for this study.
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