A method based on spatial analyst to detect hot spot of urban component management events

Abstract

Rapid growth of urban public facilities increased the important impact on urban component management in case number and hotspot space distribution. Many urban component management events such as huddle of wastes and illegal ads have been frequently hot issues. To support the government decision, methods and flows based on spatial analyst are put forward to explore the hot spot of urban component management event. Illegal ads event is taken as case study. The event's spatial correlation is decided by using exploratory spatial data analysis and Global Moran's I. Ripley's K is used to explore its spatial distribution pattern, which provides the basis for urban management events data mining. To identify the spatial border of hot spots, the spatial hot spot analysis is employed. Finally, the overlay spatial analyst between hot spot and business area layer and/or residential building layer is used to validate the feasibility and rationality of the hot spot analysis. It is concluded that illegal ads event has obvious spatial clustering and coincides exactly with the existing business area and places where population flows more frequently. According to the result, the urban management administrators can make decision more conveniently and reasonably. Comparing with time series analysis methods, this method has advantage in space information, good visualization and dynamic monitor which are useful for government decision.