The advent of the big data era has provided many types of transportation datasets, such as metro smart card data, for studying residents' mobility and understanding how their mobility has been shaped and is shaping the urban space. In this paper, we use metro smart card data from two Chinese metropolises, Shanghai and Shenzhen. Five metro mobility indicators are introduced, and association rules are established to explore the mobility patterns. The proportion of people entering and exiting the station is used to measure the jobs-housing balance. It is found that the average travel distance and duration of Shanghai passengers are higher than those of Shenzhen, and the proportion of metro commuters in Shanghai is higher than that of Shenzhen. The jobs-housing spatial relationship in Shenzhen based on metro travel is more balanced than that in Shanghai. The fundamental reason for the differences between the two cities is the difference in urban morphology. Compared with the monocentric structure of Shanghai, the polycentric structure of Shenzhen results in more scattered travel hotspots and more diverse travel routes, which helps Shenzhen to have a better jobs-housing balance. This paper fills a gap in comparative research among Chinese cities based on transportation big data analysis. The results provide support for planning metro routes, adjusting urban structure and land use to form a more reasonable metro network, and balancing the jobs-housing spatial relationship.

Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry. However, the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis. This paper presents a comprehensive investigation, based on Monte Carlo simulation, into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades. It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations. More than $6\times 10^{7}$ sets of the registrations were simulated, whereas more than 100 registrations with real data were used to verify the results of simulation. The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground, when there is only a box set of spherical targets available. As a result, the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy. The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2. Therefore, the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner, contradicting to the traditional thought. Besides, the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China. In this study, we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives. The results from Local Indicators of Spatial Association (LISA) uncover notable spatial disparities in aging population rates, with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland. The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures, but negatively correlated with economic development, social consumption, and medical facilities. From a local perspective, a Geographically Weighted (GW) correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors. The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging, but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

The population migration in Hubei Province was frequent in history, accompanied by the migration of surnames, so it is important to study their population surnames. We take Xiantao City as an example to explore the isonymic structure of small and medium-sized cities in Hubei. The surname distributions of 223 327 residents registered in 2013 were analyzed in 5 towns and 105 villages of Xiantao. The number of different surnames found was 422. As for surnames, the $\alpha $-value reflects the influence of ethnic composition on the abundance of surnames. The correlation between the isonymic distance and the geographic distance between villages was calculated and indicated that Euclidean distance was weakly correlated with the geographic distance ($r=$0.177$\pm$ 0.012), and the isonymic distance increased with the geographical distance. Furthermore, the dendrogram and PCA built from the matrix of Euclidean distances between villages identified a main surname differentiation between the urban and rural areas.

This study proposes a refined methodology for controlling building heights in heritage areas. In order to protect the visual integrity of the heritage area, buildings should not obstruct the view from important site points and viewpoints to the periphery. By calculating the building height thresholds that buildings should not obscure the view from each viewpoint, the results of which are weighted and superimposed, and the values are extracted to each building unit as a refined building height control guideline. This study takes the Zhoukoudian area as a case study, applies the refined building height control criterion to the Zhoukoudian Site, and relies on this refined criterion to assess the visual integrity of the Zhoukoudian area, so as to realize the scientific planning and monitoring of the Zhoukoudian area. The refined building height control method can be applied to building height planning and visual landscape protection in large heritage areas.

This study utilized census data from Henan Province for the years 2000, 2010, and 2020 to investigate the spatiotemporal evolution of population aging, defined by the proportion of the population aged 65 and above. Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse, the research mapped out the progression and distribution of aging demographics. Furthermore, the study delved into the influencing factors of aging using an optimal parameters-based geographical detector. Results indicate a deepening degree of population aging in Henan Province, transitioning from an adult type to an old type structure. There is a marked positive spatial correlation among counties, with high-value aging areas initially decreasing, then increasing, and notably spreading from the central to the central and southern regions of the province. The center of gravity for population aging, specifically around Changge City and Xuchang City, exhibits a trajectory moving southeast before shifting northwest. Factor detection reveals that in 2000, 2010, and 2020, the elderly dependency ratio predominantly influences the aging trend, with explanatory powers of 88.4%, 87.9%, and 90.9%, respectively. Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province, reaching 97.3%, 97.0%, and 97.4%, respectively.

As the pivotal green space, urban parks play an important role in urban residents' daily activities. Thy can not only bring people physical health, but also can be more likely to elicit positive sentiment to those who visit them. Recently, social media big data has provided new data sources for sentiment analysis. However, there was limited researches that explored the connection between urban parks and individual's sentiments. Therefore, this study firstly employed a pre-trained language model (BERT, Bidirectional Encoder Representations from Transformers) to calculate sentiment scores based on social media data. Secondly, this study analysed the relationship between urban parks and individual's sentiment from both spatial and temporal perspectives. Finally, by utilizing structural equation model (SEM), we identified 13 factors and analyzed its degree of the influence. The research findings are listed as below: ① It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks; ② The urban park type showed an influence on sentiment scores. In this study, higher sentiment scores observed in Eco-parks, comprehensive parks, and historical parks; ③ The urban parks level showed low impact on sentiment scores. With distinctions observed mainly at level-3 and level-4; ④ Compared to internal factors in parks, the external infrastructure surround them exerted more significant impact on sentiment scores. For instance, number of bus and subway stations around urban parks led to higher sentiment scores, while scenic spots and restaurants had inverse result. This study provided a novel method to quantify the services of various urban parks, which can be served as inspiration for similar studies in other cities and countries, enhancing their park planning and management strategies.