Estimating model for urban carrying capacity on bike-sharing

As the demand for bike-sharing has been increasing,the oversupply problem of bike-sharing has occurred,which leads to the waste of resources and disturbance of the urban environment.In order to regulate the supply volume of bike-sharing reasonably,an estimating model was proposed to quantify the urban carrying capacity(UCC)for bike-sharing through the demand data.In this way,the maximum supply volume of bike-sharing that a city can accommodate can be obtained.The UCC on bike-sharing is reflected in the road network carrying capacity(RNCC)and parking facilities’carrying capacity(PFCC).The space-time consumption method and density-based spatial clustering of application with noise(DBSCAN)algorithm were used to explore the RNCC and PFCC for bike-sharing.Combined with the users’demand,the urban load ratio on bike-sharing can be evaluated to judge whether the UCC can meet users’demand,so that the supply volume of bike-sharing and distribution of the related facilities can be adjusted accordingly.The application of the model was carried out by estimating the UCC and load ratio of each traffic analysis zone in Nanjing,China.Compared with the field survey data,the effect of the proposed algorithm was verified.

Spatial and Temporal Differences of Urban Land Comprehensive Carrying Capacity in Guangxi

The comprehensive carrying capacity of urban land can reflect the re- source level, economic scale, social development and environmental pressure of ur- ban land carrying. The assessment indicator system of urban land comprehensive carrying capacity was constructed from the 4 aspects of resource, economy, society, environment, and principal component analysis and cluster analysis were used to evaluate the urban land comprehensive carrying capacity of Guangxi and the 14 cities in 2005-2014, and analyzed its spatial and temporal characteristics as well as the driving forces, with the aim to provide references for improving the urban land comprehensive carrying capacity. The results showed that, the overall urban land comprehensive carrying capacity in Guangxi increased in 2005-2014, and there were significant differences in the land comprehensive carrying capacities among the cities in Guangxi in 2005-2014, in which Liuzhou, Guilin, Nanning belonged to the regions with the highest carrying capacity, while Beihai, Yulin, Wutong belonged to the regions with high carrying capacity, and the carrying capacities of the other cities changed with the changes of time. The economic development degree was an important factor influencing urban land comprehensive carrying capacity, but could not directly represent the urban land comprehensive carrying capacity level.

Evaluating Beijing’s human carrying capacity from the perspective of water resource constraints

As the demands on limited water resources intensify, concerns are being raised about the human carrying capacity of these resources. However, few researchers have studied the carrying capacity of regional water resources. Beijing, the second-largest city in China, faces a critical water shortage that will limit the city’s future development. We developed a method to quantify the carrying capacity of Beijing’s water resources by considering water-use structures based on the proportions of water used for agricultural, industrial, and domestic purposes. We defined a reference structure as 45：22：33 （% of total, respectively）, an optimized structure as 40：20：40, and an ideal structure as 50：15：35. We also considered four domestic water quotas： 55, 75, 95, and 115 m 3 /（person·yr）. The urban carrying capacity of 10–12 million was closest to Beijing’s actual 2003 population for all three water-use structures with urban domestic water use of 75 m 3 /（person·yr）. However, after accounting for our underlying assumptions, the adjusted carrying capacity is closer to 5–6 million. Thus, Beijing’s population in 2003 was almost twice the adjusted carrying capacity. Based on this result, we discussed the ecological and environmental problems created by Beijing’s excessive population and propose measures to mitigate these problems.