# Spatial Distribution Pattern and Influencing Factors of Homestays in Chongqing, China
## 3 Results  
### Spatial Distribution Characteristics of Homestays  
The number of homestays distributed within different administrations in Chongqing varied considerably, with Yuzhong District having the highest number of homestays (525), accounting for 18.07% of the total number of homestays in the city; Zhongxian County had the lowest number of homestays, with only eight, accounting for only 0.28% of the total number of homestays in the city. Most of the districts and counties in Chongqing with a high number of homestays are located in the main city's metropolitan area. HomestayBs offered more high-end services than the general accommodation sector and needed to be supported by a better economic development environment. To further explore the spatial distribution of homestays in Chongqing, a Lorenz curve was plotted to visualize the spatial distribution of the homestays. The mapping process was as follows: firstly, the regional entropy of the number of homestays in each district and county was calculated, i.e., the proportion of the number of homestays in each district and county in the total number of homestays in the city, and they were ranked according to the order of size. Then, the entropy of the location of homestays in each district and county was taken as the horizontal coordinate of the curve, and the cumulative proportion of the number of homestays in each district and county was taken as the vertical coordinate of the curve, which formed the Lorenz curve of the spatial distribution of homestays in Chongqing (Figure 3). As can be observed from the graph, the Lorenz curve is generally characterized by a downward concavity, with the curve increasing at a significantly faster rate after Banan District. The number of homestays in the first 11 districts and counties, including Banan District, accounted for 68.85% of the total number of homestays, while the number of homestays in the next 27 districts and counties only accounted for 31.15% of the total number of homestays, further illustrating the extremely uneven spatial distribution of the number of homestays in Chongqing. In the process of analyzing the kernel density of homestays in Chongqing, because the number of homestays in the central urban area was close to eight times of that in the urban agglomeration of the Three Gorges Reservoir Area in Northeast Chongqing, there was a large gap in the number of homestays, and the analysis effect was poor. Therefore, in the process of analyzing the kernel density of homestays in Chongqing, this paper excluded the homestay points of nine administrative units in the central urban area, and created a kernel density analysis of the homestay points in the other three areas. The analysis results of the resident nucleus density of Chongqing citizens were obtained (Figure 4). From the overall perspective concerning Chongqing, the spatial distribution density of homestays was generally high in the West and low in the East. In addition to the high concentration of homestay distributions in the central urban area, three high-density areas were formed around the central urban area, and there was a trend of concentration and contiguity. The spatial distribution density of the two urban agglomerations in Southeast  
Figure 4: Density of homestay nuclei in Chongqing. Note: Based on the standard map (scale: 1:48 million) with the approval number of GS (2019) 1823 on the standard map service website, the base map was not modified. Figure 3: Lorentz curve of homestay distribution in Chongqing. and Northeast Chongqing was very low, forming a strong contrast with the high-density main urban areas, and the overall distribution was extremely uneven. Locally, except for the central urban area, the high-density centers of homestays were mainly distributed in Wulong District, Qijiang District and Yongchuan District, and there was a trend of agglomerations. Secondly, there were low-density centers in Wanzhou District, Shizhu County, Fengjie County, and Wushan County, but the agglomeration was not obvious.