Urban crimes, as a violation of the law, emerge as serious social issues, threatening the social order and safety. Despite our ongoing efforts, crimes continue rising and the necessity to seek the new plans in the aspect of the measures after the occu...
Urban crimes, as a violation of the law, emerge as serious social issues, threatening the social order and safety. Despite our ongoing efforts, crimes continue rising and the necessity to seek the new plans in the aspect of the measures after the occurrence of crimes. Thus, to make a safe city from crimes, this study will analyze the characteristics of the crimes in the applicable region, and use it for the base data for establishing the direction for urban planning to prevent the crimes, under the assumption that the crime occurrence is relating to the characteristics of the regional.
The scope of this study targets 467 Dongs and 31 police precincts, in Seoul. The dependent variable, used in the analysis, includes Seoul’s 5 major crime rates, and the occurrence rate of murder, robbery, rape, theft, and violent crimes. Independent variables were the urban environmental elements, which were expected to be the causes of crimes, and the variables for demographic, socio-economic, and physical characteristics of the regional were established, based on the precedent studies.
As a result of the examination of the state of crimes in Seoul, it showed significant differences by each police station. Downtown and the subcenter of city with relatively low resident population and relatively high floating population showed high crime rate. Violence showed similar pattern to 5 major crime rates, and murder showed the different patterns of distribution. Robbery and rape showed similar patterns to each other, but it was identified that they were different from other crimes.
To examine more precise breeding grounds for crime and the characteristics of the regional, Hot Spot area was analyzed by applying Gi *(d) value of spatial autocorrelation. As a result of the analysis, it was identified that hot spot area is the area in which the adult entertainments were concentrated and which had high floating population. As a result of the results, it was identified that, with respect to the occurrence of crimes, there existed regional differences, and common regional characteristics appeared in these collective areas. Also, it was identified that these regional differences were caused by spatial autocorrelation propensity, and the spatial dependency and heterogeneity were related to the occurrence of crimes.
Also, to investigate the variables, affecting the crimes the most, a spatial regression analysis was conducted. The variables used for the analysis were established by the spatial data, and it was proved that the spatial regression model, which enhanced the reliability of analysis results, by supplementing the spatial problems, was appropriate in this case.
As a result of spatial regression analysis, the size of effectiveness of crimes can be displayed in the order of “Floating population>Parking>Population density>Parks density>Total Property Tax>Adult entertainment>Residential/Commercial facilities>Residential/Industrial facilities>Low-income population". Considering that the density of parks had (-) relation to all the crimes, within the statistically significant level, it was identified that the park had the effect for reducing the crime rate. In other words, it was identified that the characteristics of the area affection crime rate varied, according to the type of crime.
Based on above results, it was proved that crime factors were caused by the action of the various parts, and the characteristics of the regional were closely related to the crime. Also affected by the crime neighborhoods, areas where the crime occurred concentrate could see that.
The analysis of the urban crimes like this, will be effective for providing the quantitative information required for the urban planning which aims to prevent the crimes.