## 4 Discussion  
To intuitively show the differences in the SARSF-RA values, we constructed a four-quadrant map and collected a photo of the facade from some typical communities, as shown in Figure 7, which was expected to be more intuitive in terms of explaining the coordination between ASFC-RA and PDC-RA. The value of ASFC-RA was the highest, but the value of PDC-RA was in the middle in HuaHuiYuan; thus, it obtained a high degree of rationality. The value of ASFC-RA and the value of PDC-RA was the highest in Versailles Estate, indicating it was highly reasonable. In LiRen Garden#1, the value of ASFC-RA was lower, but the PDC-RA was the highest. Thus, it was less generous. In LiRen Garden#2, the value of ASFC-RA was the lowest, and the PDC-RA value was lower. Thus, LiRen Garden#2 obtained the most moderate degree of reasonableness. However, near the origin, the interrupted locating communities located in the fourth quadrant in Figure 7, including FuRunHuaYuan#1 and FuAnHuaYuan#3, had well-situated reasonableness, and the values of ASFC-RA and PDC-RA were more coordinated. This paper studied the level of the service facilities and the actual population distribution in urban residential areas; additionally, the method used quickly, freely, and accurately obtained the relevant residential areas and auxiliary data for evaluation through open network data. Based on the population carrying capacity level in residential areas and the supply level of service resources, we constructed an indicator system of the comprehensive service level in residential areas, and we calculated the reasonableness of the service facilities in each district by the entropy weight method. The conclusionsare as follows: (1) Internet open data provide new verification data for service facilities rationality research at the micro scale, which has practical value for the evaluation of urban detailed planning and design. (2) It is found that the overall service resource supply level in the experimental area is higher in the northwest and lower in the southeast, and the communities with high and low levels show a robust spatial agglomeration phenomenon. The distribution of services in five major types also shows noticeable spatial agglomeration. This conclusion can help the government understand regional dominance; additionally, the population carrying capacity of the old community was generally higher than that of the new community, and the population carrying capacity near the community with a top service resource supply level was usually higher. This research has made significant progress in the application of big data, but the incompleteness of the data acquisition still limits it, and there are some shortcomings. The following points are worth further improvement and development: (1) The experimental area could be expanded to the whole city, and the scope of the experimental area can be enlarged in the later stage to obtain more stable law. (2) The number and scale of the service facilities are two important indicators for measuring the supply of the service facilities. Due to the lack of scale data, this study has certain limitations. It would also be worthwhile to study the method for supplementing the scale data to POI through other Internet datasets. (3) The spatial subdivision method of Tencent LBS data can improve to template-based GIS computation, such as a geometric algebra approach [35; 36; 37; 38; 39; 40; 41]. In this paper, the model provides a new and feasible Internet big data idea for the effective verification of residential area planning, which can be effectively applied to the evaluation of the service facilities in the micro-space residential areas. Additionally, the results can serve as a reference for city planning and decisions that support multi-source Internet data under a new trend. **Author Contributions:** For research articles with several authors, a short paragraph specifying their individual contributions must be provided. Conceptualization, X.Z. and J.H. ; Methodology, X.Z. ; Software, X.Z. and C.H.