Abstract: Crowdsourcing is a process of acquisition,integration,and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces,such as sensors,devices,vehicles,buildings,and human.Especially,nowadays,no countries,no communities,and no person are immune to urban emergency events.Detection about urban emergency events,e.g.,fires,storms,traffic jams,is of great importance to protect the security of humans.Recently,social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic.The content from social media often includes references to urban emergency events occurring at,or affecting specific locations.In this paper,in order to describe the real time urban emergency event,the crowdsourcing based model was proposed.Firstly,users of social media are set as the target of crowd-sourcing.Secondly,the semantic,spatial and temporal information from the social media are extracted to detect the real time event.Thirdly,a GIS based annotation of the detected urban emergency event is shown.The proposed method was evaluated with extensive case studies based on real urban emergency events.The results show the accuracy and efficiency of the proposed method.

Key words: Crowdsourcing,Urban emergency event,Semantic description,Spatial temporal