# Applying Real-Time Travel Times to Estimate Fire Service Coverage Rate for High-Rise Buildings
## 1 Introduction  
With the urbanization process, more and more high-rise buildings have appeared around the world [1; 2; 3; 4]. In China, high-buildings contain residential buildings with a height greater than 27 m and non-single-story buildings (containing factories, warehouses, and other civil buildings) with a height greater than 24 m [5]. The number of high-rise buildings in China exceeded 347,000 in 2017 and is still increasing rapidly [6]. These have also led to frequent fires in high-rise buildings. Between 2007 and 2017, there were about 31,000 high-rise building fires in China [6]. The fire risk of high-rise buildings poses a serious threat to urban public safety. To mitigate fire risks, high-rise buildings should be able to obtain efficient and effective fire services. Can high-rise buildings be effectively covered by fire services? The present study was aimed at answering this question. Different types of buildings have different fire risk characteristics (such as structural space, combustible, personnel density, etc. ), and their fire apparatus requirements will be varied [7; 8; 9]. However, fire service coverage was mainly defined by the spatial relationships between fire stations and fire service demand points in previous studies [10; 11; 12; 13]. In previous studies, \"every fire station contained all types of fire apparatus\" seems to have been assumed by default [10; 11; 12; 13]. In fact, due to the constraints of economy and land space, the type and quantity of fire apparatus in a fire station are limited. In response to most fires, multiple types of fire apparatus need to be dispatched from multiple fire stations to the fire scene. If fire apparatus required by a building cannot reach the fire scene in a specific time, it can be considered that the building cannot be effectively covered by fire services. In this study, the spatial-temporal relationships between fire apparatuses and high-rise buildings are used to determine whether high-rise buildings can be effectively covered by fire services. The type, quantity, and location of fire apparatuses in a region were always clearly recorded by the regional fire department. Fire apparatus data can be gathered by the fire department, but the data on fire service demand points (mainly buildings) is very difficult to obtain. With the development of Internet technology, online maps have been widely used in various fields (such as navigation, route planning, traffic planning, urban planning, etc.) [14; 15]. The big data of the point of interest (POI) containing various types of places or facilities are stored in online maps [16; 17]. In previous studies, POI data was always used to identify spatial functions [18; 19; 20; 21]. To the best of our knowledge, few studies have focused on the application of POI data to identify high-rise buildings. In this study, high-rise buildings were identified from POIs. Calculating travel times from fire apparatuses to high-rise buildings is a critical step in determining whether high-rise buildings are effectively covered by fire services. In previous studies, the road network data and fire station data were imported into the geographic information system (GIS), and then the shortest path algorithm was used for network analysis to obtain the fire station service coverage [22; 23]. However, the results calculated with this method may differ significantly from the actual situation, because real-time traffic conditions were not considered. With the rapid renewal of urban road networks, the increasing number of vehicles, and the constantly varied traffic conditions, it is necessary to calculate the travel time of fire truck according to the real-time traffic conditions [24; 25; 26]. Online maps can update traffic conditions in real-time by collecting data from crowdsourcing and transportation departments. This enables online maps to plan routes based on real-time traffic conditions.