Utilizing the Gaode Open API for Evaluating Fire- Fighting Facility Planning

Big data has been widely used in urban planning and architecture in recent years. However, data collecting techniques limit its broader use. As a result, a lot of work has been done to precisely identify and address urban problems through the mining of legally accessible open-source internet data, which has progressively gained popularity among urban scholars. In light of this, using Nanjing as an example, this study uses the Gaode OPEN API to build urban real-time traffic circles and assess the layout of firefighting facilities. In order to extract the average vehicle speed of all roads within a certain time frame and to automatically collect real-time traffic data in the study region, a batch processing model is first developed based on the Gaode OPEN API. It was discovered that the speed causes Nanjing City to be divided into multiple different zones. After that, a case study is carried out to build an urban real-time traffic circle based on the current firefighting facilities using the Python programming language and Arcgis software. After further analysis, it is found that the current planning for firefighting facilities exhibits a notable regional difference between the urban centre and the suburbs. Traffic speed, station density, and road network density all influence the service coverage area of fire stations. This study offers a comprehensive approach for gathering and analysing Gaode data, mining its spatiotemporal properties, and using it in planning evaluation procedures. This strategy highlights the benefits of streaming data features and distributed big data processing, efficiently uses the real-time nature of big data in emergency facility planning, and is expected to expand ideas for data collection.