Since none of the mentioned models could take into consideration the capacity limitation and population imbalance distribution of emergency shelters in the process of locating, some research put forward the solution by dividing the reasonable service scope of emergency facilities based on location selected. [PERSON] et al. [20] and [PERSON] [21] considered service scope, accessibility, and travel distance in order to analyze the service scope of emergency shelters according to the location analysis model in economic geography. [PERSON] et al. proposed a model based on mixed integer linear programming to select the location of temporary evacuation sites [22]. This mathematical model considered the capacity limitations of emergency shelters while determining the location of emergency shelters. Based on the location-configuration model, [PERSON] et al. transformed the scope of facilities services into mathematical programming problems to maximize or minimize the optimal or feasible location [23]. This method was essentially the same as the location model that fails to consider the scale of the site. A number of studies have differentiated the service scope based on spatial analysis performed by ArcGIS software [23; 24; 25]. However, to the best of our knowledge, these methods are still not able to solve the issue of the scale of the emergency shelters by using the number of people to accommodate as evenly distributed, which is certainly inconsistent with real-world conditions. Therefore, the multi-level location models with the service scope analysis may provide a better approach to simulating the people's location choice behavior in practice as well as simulating the actual service scope of each emergency shelter. In this paper, we consider these factors, thus making an important contribution to the literature. Our article mainly focuses on small mountain cities and offers two contributions. Firstly, we put forward the multi-level location models for different grades of emergency shelters in order to minimize the travel and construction costs and to maximize the coverage rate. Secondly, the limitation of site capacity is included in the service scope of emergency shelter. In this paper, in order to define the scope of urban emergency shelter services, we developed a method that determines the service scope of each emergency shelter by weighted spatial scope. The proposed research methods and models are applied to Jianchuan, a typical small mountain city in China. This paper has provided theoretical basis and a benchmark for the optimal layout of emergency shelters in other small mountain cities. Our article takes the spatial layout of emergency shelters in small mountainous cities as the research object. Through the three steps of location, zoning and optimization, the whole process of optimizing layout is realized through: (a) constructing a multi-level location models system suitable for different levels of emergency shelters, applying the models to the actual location selection of the emergency shelter in the Jianchuan county seat, and verifying the scientificity and effectiveness of the construction models; (b) establishing a method suitable for the service scope division of emergency shelters in small mountainous cities, and relying on GIS technology to visualize the results; (c) adjusting the location and quantity of emergency shelters in conjunction with population and urban land use within the scope of emergency shelters.