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Some possibilities of spatial analysis of crimes in police work
- Source :
- Nauka, bezbednost, policija
- Publication Year :
- 2015
-
Abstract
- Crime does not occur randomly. It tends to concentrate at particular places for reasons that can be explained in relation to victim and offender interaction and the opportunities that exist to commit crime. If the police knew where crime is concentrated (where are the hotspots) resources could be directed in order to take proactive actions. In order to identify hotspots, spatial distributions of crimes should be examined. Patterns in data must be identified, and underlying (spatial) processes must be understood in order to be effective in crime prevention. This could be achieved using spatial analysis techniques. In cases where spatial distribution is not complex and visually overwhelming the simple 'eyeball method' should be sufficient. But in cases where spatial distribution of a large number of crimes (events) is present, the spatial statistics is needed. Spatial statistics help cut through some of the subjectivity to get more directly at spatial patterns, trends, processes, and relationships. Today, the most commercial GIS solutions already have more or less developed statistical capabilities. In cases where built-in GIS statistical capabilities are not sufficient to satisfy particular research need, they must be supplemented by specialized statistical software. An example of the usage of spatial statistics is shown on the practical example using commercial robberies dataset in one of Belgrade's municipalities. The crime distribution is assessed using centro graphic measures (mean center, center of minimum distance, standard deviation ellipse). Centro graphic measures allows us to visualize a complex spatial trend, how quickly the mean center moves, and where it moves, is there changes in dispersion and/or orientation of the crime distribution etc., providing valuable information about the spatial processes promoting this crime shifts. The level of clustering was assessed calculating nearest neighbor index and finally clusters (i.e. hotspots) were identified usi<br />Skup svih krivičnih dela na nekom geoprostoru formira određenu geoprostornu distribuciju. Ona nije slučajna već je u velikoj meri uslovljena karakteristikama geoprostora na kojem se manifestuje. Vršenje krivičnih dela podrazumeva postojanje pogodnih prilika, pri čemu niti su prilike podjednako distribuirane u geoprpostoru, niti su konstantne u vremenu. Tako su neki geoprostori ugroženi vršenjem krivičnih dela, dok su drugi manje ili više bezbedni. Ako bi policija poznavala ugrožena područja i objekte, mogla bi na te prostore da usmeri raspoložive resurse i da efikasnije proaktivno deluje. Odgovor na pitanje kakve su karakteristike geoprostorne distribucije krivičnih dela, gde se grupišu lokacije krivičnih dela (žarišta) i kakvi su odnosi geoprostorne distribucije krivičnih dela i drugih činilaca okruženja, moguće je dobiti vršenjem geoprostornih analiza. U radu se ukazuje na pojam i značaj geoprostorne analize, specifičnosti metoda statistike koje se koriste u radu sa geoprostornim podacima i na praktičnom primeru analize geoprostorne distribucije krivičnih dela pokazuju neke od njenih mogućnosti u policijskom radu.
Details
- Database :
- OAIster
- Journal :
- Nauka, bezbednost, policija
- Notes :
- Nauka, bezbednost, policija
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1091020296
- Document Type :
- Electronic Resource