Abstract
This study examines the impact of the precision of address geocoding on the estimated density of crime locations in a
large urban area of Japan. The data consist of two separate sets of the same Penal Code offenses known to the police that
occurred during a nine-month period of April 1, 2001 through December 31, 2001 in the central 23 wards of Tokyo. These
two data sets are derived from older and newer recording system of the Tokyo Metropolitan Police Department (TMPD),
which revised its crime reporting system in that year so that more precise location information than the previous years
could be recorded. Each of these data sets was address-geocoded onto a large-scale digital map, using our hierarchical
address-geocoding schema, and was examined how such differences in the precision of address information and the
resulting differences in address-geocoded incidence locations affect the patterns in kernel density maps.
An analysis using 11,096 pairs of incidences of residential burglary (each pair consists of the same incidents geocoded
using older and newer address information, respectively) indicates that the kernel density estimation with a cell size of
25 25 m and a bandwidth of 500 m may work quite well in absorbing the poorer precision of geocoded locations based on
data from older recording system, whereas in several areas where older recording system resulted in very poor precision
level, the inaccuracy of incident locations may produce artifactitious and potentially misleading patterns in kernel density
maps.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Crime; Residential burglary; Address geocoding; Kernel density estimation
AbstractThis study examines the impact of the precision of address geocoding on the estimated density of crime locations in alarge urban area of Japan. The data consist of two separate sets of the same Penal Code offenses known to the police thatoccurred during a nine-month period of April 1, 2001 through December 31, 2001 in the central 23 wards of Tokyo. Thesetwo data sets are derived from older and newer recording system of the Tokyo Metropolitan Police Department (TMPD),which revised its crime reporting system in that year so that more precise location information than the previous yearscould be recorded. Each of these data sets was address-geocoded onto a large-scale digital map, using our hierarchicaladdress-geocoding schema, and was examined how such differences in the precision of address information and theresulting differences in address-geocoded incidence locations affect the patterns in kernel density maps.An analysis using 11,096 pairs of incidences of residential burglary (each pair consists of the same incidents geocodedusing older and newer address information, respectively) indicates that the kernel density estimation with a cell size of25 25 m and a bandwidth of 500 m may work quite well in absorbing the poorer precision of geocoded locations based ondata from older recording system, whereas in several areas where older recording system resulted in very poor precisionlevel, the inaccuracy of incident locations may produce artifactitious and potentially misleading patterns in kernel densitymaps.r 2006 Elsevier Ltd. All rights reserved.Keywords: Crime; Residential burglary; Address geocoding; Kernel density estimation
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