## 2 Materials and Methods  
### Data Source and Methods  
For a long time, the reliability and accuracy of studies on the assessment and decision support of urban facility service capacity mainly depended on two aspects: one is the appliable assessment method; the other is the accurate data support [36; 37]. They are interlinked and mutually constrained [38] and influenced by the spatial scale, element attributes, and target export at the same time [39]. At the spatial scale above the municipal area, it is more convenient to obtain social statistics. However, it is difficult to obtain geographical location data at large scales due to the lack of data types. On the other hand, it is easy to obtain geographical location data below the street and community spatial scale, but it is not easy to obtain social statistics. In terms of content, geographical location data only contains information such as name and location, lacking more comprehensive attribute information. According to the classification information, public toilet facilities were classified into dependent public toilets and independent public toilets to supplement the attribute information, including sanitary conditions and business hours, and expand the service capacity evaluation data set of public toilet facilities. Correspondingly, for the two target needs of public toilet facilities' balance and spatial pattern, an evaluation system of the service capacity of public toilet facilities is formed by integrating multiple data sources and analyzing the distribution pattern and model construction. Therefore, with the support of multi-source data, this paper selects the street community-level scale to evaluate the service capacity of public toilet facilities from two target outlets: resource balance and spatial service model. Based on the support of POI big data, combined with social statistics and survey data, this study constructed a multi-source data correction and fusion system for facility service capacity evaluation. The POI data of public toilets in 2008 and 2018 were obtained from the AMap platform ([[https://ditu.amap.com/](https://ditu.amap.com/)]([https://ditu.amap.com/](https://ditu.amap.com/)) (accessed on 1 December 2018), following the AMap API POI classification rules. AMap company (Beijing, China) is a leading provider of digital map content, navigation, and location services in China. By applying the key to the company's platform, crawler technology can be used to obtain a certain amount of POI data provided by AMap. The data type codes were 200,300-200,304, with the type of \"public facility--public toilet--public restroom; public facility--public toilet--men's restroom; public facility--public restroom--female restroom; public facility--public restroom--disabled restroom/accessible restroom; public facility--public restroom--baby care room/lactation room\". The POI data of public toilets include name, latitude and longitude, address, and administrative unit code. After data pre-processing such as coordinate conversion, data cleaning, and cross-checking, one hundred and sixty-five POI data of public toilets in 2008 and one thousand six hundred and fifty-five POI data in 2018 were obtained. Regarding resource balance measurement, the data of population and area at the scale of street and community level administrative units were obtained from the social statistical yearbook. For the dependent public toilets, the POI address information contains a large building as the basis, combined with the time of data acquisition and the existing state of the survey site, eliminating some survey sites, due to bankruptcy, decoration, and other factors, the final list of shopping malls in the city where survey data can be obtained. For independent public toilets, considering the amount of data and the distribution range, we selected 10 parks with the highest concentration of independent public toilets as the actual survey sites based on the regional aggregation. Moreover, the study area is divided into different grids based on road and community information.