Fig 1.
Calculation diagram of effective service area of public sports facilities.
Table 1.
Gini coefficient classification table.
Fig 2.
Research model.
Table 2.
Time and distance corresponding to different modes for moving.
Table 3.
Service radius and evaluation standard of public sports facilities at all levels.
Fig 3.
Spatial distribution of effective service coverage range and service level of sports facilities in Hangzhou: (A) Spatial distribution of effective service scope and service level of public sports facilities at province(city)-level; (B) Spatial distribution of effective service scope and service level of public sports facilities at District-level; (C) Spatial distribution of effective service scope and service level of public sports facilities at Subdistrict-level; (D) Spatial distribution and rings distribution of overall effective service scope and service level of public sports facilities. Source: Created by the author based on the base map of Hangzhou which comes from the National Platform for Common Geospatial Information Services (https://www.tianditu.gov.cn/).
Fig 4.
Service level disparity of public sports among each district.
Overall service level (darker green column) represents the sum of each subdistrict service level in each district; Average service level (lighter green column) represents the average of the sum of the service levels of each subdistrict in each district; The line represents the median of service level in each district.
Fig 5.
Lorenz curve of resource allocation of public sports facilities.
Table 4.
Cumulative list of the proportion of permanent residents having access to public sports facilities resources.
Fig 6.
Spatial distribution pattern of per capita public sports facilities resources based on location entropy allocation.
Table 5.
The number and proportion of spatial units of location entropy.
Fig 7.
Regional distribution map of each level of location entropy.
(A) Areas with extremely low location entropy (less than 0.5); (B) Areas with low location entropy (0.5–0.8); (C) Areas with medium location entropy (0.8–1.2); (D) Areas with high location entropy (1.2–2.0); (E) Areas with extremely high location entropy (greater than 2.0). Source: Created by the author based on the base map of Hangzhou which comes from the National Platform for Common Geospatial Information Services (https://www.tianditu.gov.cn/).
Fig 8.
Distribution pattern of location entropy in each district.
(A) Distribution pattern of location entropy in Shangcheng District; (B) Distribution pattern of location entropy in Xiacheng district; (C) Distribution pattern of location entropy in Gongshu District; (D) Distribution pattern of location entropy in Bingjing District; (E) Distribution pattern of location entropy in Jianggan District; (f) Distribution pattern of location entropy in Xihu District. Source: Created by the author based on the base map of Hangzhou which comes from the National Platform for Common Geospatial Information Services (https://www.tianditu.gov.cn/).