The use of spatial analytical techniques to highlight the geography of burglary in Leeds, UK.

Authors : Christopher EZEH

Pages : 129-140

View : 12 | Download : 7

Publication Date : 2021-06-30

Article Type : Research Paper

Abstract :Socio-demographic classification of attributes of burglary was carried out. The aim was to highlight the geography of burglary across Leeds using housing/socio-economic related data. Three hypotheses were formulated: insert ignore into journalissuearticles values(i); the denser the residential areas, the higher the likelihood of it being burglars’ target. insert ignore into journalissuearticles values(ii); The denser the population and activities, the higher the burglary rate. insert ignore into journalissuearticles values(iii); The higher the territory’s level of ethnic heterogeneity, the higher the probability of burglary incidence. The K-means technique was used to analyse the data. The hypotheses were upheld. It reveals that the bulk of burglary occur at central south-western part of Leeds which is the city centre with high business activities, population with high diversity and residences. The limitation of the technique is the inability to handle temporal dimension. To have best output, it should be used together with other techniques.
Keywords : Burglary, K Means, Socio demographic, Geography, Leeds