Research On Spatio-temporal Cluster Distribution Characteristics Of Emergency Medical Services Calls For Traffic Accident:a Case Study In Urban Areas Of Taiyuan

This study uses specific locations of EMS calls,and methods of point pattern surface pattern analysis,to detect overall spatial clustering feature among EMS traffic accident locations of EMS responses in a six-District;EMS region in Taiyuan City.China.The purpose of this study is to clarify the spatial distributed characteristics of the traffic accidents involved EMS traffic accident data in Taiyuan city.The focus is on the characteristics of traffic accidents.Using statistical methods such as Mean Center,Standard Deviational Ellipse,and Ripley's K function,the influence factors were analyzed and extracted.In addition,combining the strengths of that independent spatial clustering analysis methods,namely,the Global Moran's Index for finding the spatial autocorrelation roughly,as well as the LISA and Hot Spot' Analysis algorithm and so on,the NNS approach to identify high-risk TA clustering areas.The Global Moran's Index of TA event locations were 0.191224,with a Zscore of 3.111647,indicating significance spatial autocorrelation phenomenon of TA locations in Taiyuan city,LISA and NNS Analysis covers more towns(urban areas),the High-High area reaching statistical standards obtained.In addition,Hierarchy cluster and KDE used to study the spatial distributed characteristics of the traffic accidents in urban areas as an example.There is great benefit using the combination of NNS and KDE,namely,KDE will show a smooth curve,and NNS could indicate to the edge of the hot spots in the accident.And hotspot data visualization?In the last part of the paper,The models based on the space-time.scanStatistic were tested.the analysis of this paper were implemented at county/district level.In addition,the fantastic figure visualization could express the results more directly and vividly and seemed to be more convenient for performer.Based on the EMS-prone hot zone generated by the Anselin's Local Moran`s I and Nearest Neighbor Hierarchical Spatial Clustering.Targeting EMS calls' past history of the accident,Emergency Medical Service System units may adopt information technology as an intervention in order to increase the probability of eyewitnesses and prioritize the dispatch of emergency aid resources into the hot zone,thereby enhancing traumas' patient survival rates.