Search

Tourism is the pillar industry of many cities, and it is also an important key point to promote urban development and maintain urban vitality. At present, the analysis of urban tourism activity in China can better assist the research of regional economic development and promote the orderly development of regional economy. Many scholars have carried out the analysis in this respect. As a new and growing field, artificial intelligence also plays an important role in urban tourism. With the continuous development of science and technology, and the human intelligence field of human research is also developing. New artificial intelligence products continue to emerge. The workload of most artificial intelligence may exceed the manual workload. In order to continuously update artificial intelligence, individuals effectively combine data mining and artificial intelligence, and combine many knowledge disseminated by the network with artificial intelligence technology to create an advanced knowledge network model. This paper uses the OPTICS-based clustering algorithm to analyze the clustering of photographs on the Flickr website and obtain information about tourism activities in Chinese cities. With the help of visualization software to visualize the experimental data and verify the experimental results introduced in this article, city tourism activities can be recommended to the destination. At present, many scholars have studied the application of improved density clustering algorithm in the field of biology and image analysis, but there are still some gaps in the development of tourism. This paper can make some contributions to the related fields. [ABSTRACT FROM AUTHOR]

As more attention is given to green and sustainable industries, an analysis of the industrial impacts on all aspects of life, including inclusive affluence, is gradually developing. Idle rural residential land is a valuable resource and an important factor in promoting sustainable development. Balanced urban and rural development contributes to inclusive prosperity, so understanding the relationship between industry and the balanced development of urban and rural can significantly impact social development. In China, achieving the balanced development requires narrowing the urban-rural income gap. This paper analyzed the impact of reallocating idle rural residential land on promoting the balanced development. The study found that industry development has a positive impact on the balanced development, with a regression coefficient of 1.478. Regions with higher industry indices in counties had better outcomes regarding the balanced development. When the development of rural industry derived from idle residential land was in good condition, the effect increased by 3.326 percentage. The results showed heterogeneity, with the regression coefficient of industry development on the balanced development in county-level cities being 0.498 larger than in urban areas. In summary, the reallocation of idle residential land can promote sustainable development, increase residents' income, and improve overall regional economic development. The results are applicable to the comprehensive reallocation of rural land resources. [ABSTRACT FROM AUTHOR]

Modern cities require urban compact development to be sustainable. The evaluation of urban compact development may help create more accurate and realistic policies. The spatio-temporal dynamic evolution of urban compact development efficiency and its regional differences in China are examined in this study. This paper analysis uses 282 cities from 2005 to 2021. The unexpected output super-efficiency SBM model measures urban compact development efficiency. In this study, the urban compact development efficiency's spatial and temporal patterns are also examined using kernel density estimation (KDE) and the Theil index (TI). The average efficiency of urban compact development in China has decreased slightly. However, compact efficiency disparities are decreasing. Eastern cities have a relatively stable compact efficiency, while central and western cities vary more. The compact efficiency polarisation has not changed fundamentally. The compact city growth model's spatial agglomeration is poor, limiting its spatial spillover impact. Thus, compact urban development is necessary to speed up planning, facilitate inter-city production factor movement by creating a comprehensive transport network, and maximise co-location benefits with the regional integration strategy. This method will gradually reduce regional urban development disparities and push Chinese cities towards more refined and sustainable compact development. [ABSTRACT FROM AUTHOR]

This paper tests China's three-dimensional intergovernmental competition in terms of land leasing. Using the land-leasing data of China's prefecture-level cities from 2003 to 2019 collected from China Land Market, and with the help of the dynamic spatial Durbin model, we show that in the land-leasing behavior of prefecture-level cities in China, three-dimensional government competition does exist and that the influence coefficient from high to low is the government competition of different periods in the same region, shown as horizontal government competition and vertical government competition, respectively. In particular, China's government competition and regional economic development show a clear correlation. We find obvious heterogeneity: in the eastern region, the government competition for land leasing started earlier and has now begun to transform. However, the three-dimensional government competition in the western region lags behind the national level. Therefore, urban development should emerge from the mindset of blindly focusing on the expansion of urban areas, paying more attention to the guiding role of urban planning in urban development and promoting cities on the path of sustainable development by improving the efficiency of land use. [ABSTRACT FROM AUTHOR]

Green development is a significant concept that cannot be ignored in contemporary society. However, in the context of China's transition from high-speed growth to high-quality development, the complex impact of urban development has brought great challenges to the urban green environment. In this paper, the impact of urban development on green development efficiency (GDE) was studied. First and foremost, a Super-SBM model was introduced to measure the GDE of 41 cities in the Yangtze River Delta during 2009–2018. Moreover, a Tobit model was used to analyze the correlation between four urban development factors, including economic development and GDE. According to the results, the mean GDE of the Yangtze River Delta is 0.824, and the GDE in most cities there has shown a fluctuating growth trend in this decade. By comparison, the GDEs of coastal cities and cities in the southeast of the Yangtze River Delta were generally higher than those of cities in the north, indicating that the green development is geographically unbalanced, and there is spatial heterogeneity in the area studied. The study's results also suggest that the urban economic development, innovation level, and government planning play a significant role in stimulating urban green development, and that the expansion of urban construction area hinders the improvement of GDE. [ABSTRACT FROM AUTHOR]

The development statuses of cities are intimately associated with their spatial scales. Multiscale trajectories of cities are lenses through which can be discerned the pattern and tendency of regional development. In this paper, using comparisons of demographic and economic development, geographic detectors, and hierarchical logistic regressions, we examine the evolutionary characteristics and influential factors of multiscale urban development in Jilin Province, China. The findings show that alongside the "top-down" transformations of the spatial scales, the typologies of urban development tend to diversify. Economic and political factors played key roles in the divergence of growth and shrinkage of prefecture-level, while natural and social factors had strong effects on the divergence between growth and shrinkage of county-level cities and small towns. Moreover, urban development has demonstrated scale connection: towns under the jurisdictions of absolutely growing county-level cities are likely to be subjected to smart shrinkage; towns under the jurisdictions of smartly growing county-level cities are prone to potential shrinkage; towns under the jurisdictions of absolutely shrinking county-level cities are at risk of absolute shrinkage. Our findings recommend that regional policies take multiscale spaces into account to capture regularity of regional development. [ABSTRACT FROM AUTHOR]

With globalization and informatization, cross-border areas have become increasingly critical interactive spaces, experiencing rapid development and extensive changes in residents' cross-border travel, constantly changing the spatial patterns of neighboring cities. However, existing studies lack in-depth discussions of the new spatiotemporal characteristics of human activities, spatial pattern evolution, and the driving factors behind them. Therefore, taking the Guangzhou-Foshan metropolitan area as a case, this paper focus on the analysis of the cross-city travel of residents in these border areas in 2019, and investigated the evolution of spatial patterns and the driving forces in the border area during 1985–2020. We found that, instead of the previous one-way attraction pattern caused by the spread of residence, a large number of cross-city trips for leisure and entertainment purposes emerged, and the one-way unbalanced flow, "Foshan to Guangzhou", changed to two-way circulation. We also explore the scenario in which the travel behavior of urban dwellers in these two cities considerably interacts with the effect of urban structure to produce the observed mobility patterns. Second, we determined the spatial pattern of the Guangzhou-Foshan region from 1985 to 2020 to be on of spreading expansion, with Liwan District as the central core, connecting to several sub-centers. The cross-border area in the Guangzhou-Foshan region represented a compact, extremely high degree of integration and a well-matched functional space. Third, driven by the forces stemming from the planning guidelines and the improving transportation network construction in the border area, the growth points of the two cities continued to expand toward the borderline regarding integrated development, while the growth axis was mainly in the direction of the city border, urban arterial roads, and subway lines. We concluded with development suggestions for increasing travel interactions and optimizing spatial patterns to build a common vision of the whole Guangzhou-Foshan pattern of integration. [ABSTRACT FROM AUTHOR]

Key cities represent the strongest competitiveness level of each province and city. At present, the problem of unbalanced development level of key cities in China is more prominent. Improving urban competitiveness has become an urgent problem for urban governments. In order to study the competitiveness of 35 key cities in China, this paper formulates a total of 27 indicators from the five levels of economic development, social undertakings, public infrastructure, ecological environment and technological innovation, and uses measurement software to draw the advantages and disadvantages of relevant urban development. The results show that the top cities in the comprehensive competitiveness of 35 key cities in China include Beijing, Shanghai, Shenzhen and Guangzhou, and the differences among key cities are more prominent in all dimensions. The relative level of competitiveness development of key cities corresponds to the level of regional economic development and technological innovation to a certain extent. [ABSTRACT FROM AUTHOR]

Since the 21st century, the world has increasingly focused on the issue of sustainable development, and the green transformation issues have become a new hot topic worldwide. Green and low-carbon transformation has become an international consensus. Urban agglomerations are important connections between urban development and regional coordination, as well as important spatial carriers for economic activities. They are not only the main source of carbon emissions, but also the main battlefield for energy conservation and emission reduction. As an important field for carbon reduction, the green transformation of cities is crucial for achieving the "dual carbon" goals. This article focuses on 48 cities in the three most mature and influential urban agglomerations in China from 2011 to 2019, namely, the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the Pearl River Delta urban agglomeration. The three-stage DEA model and Malmquist index model are used to measure the green transformation efficiency of the three urban agglomerations from both dynamic and static perspectives, and a Tobit regression model is constructed to explore the influencing factors of green transformation efficiency in urban agglomerations. Research has found that: 1) From a static perspective, the overall efficiency of green transformation in the three major urban agglomerations is at a high level, but from a temporal perspective, it shows a downward trend. The Pearl River Delta urban agglomeration is known for its green development, with the highest average efficiency of green transformation, followed by the Yangtze River Delta urban agglomeration. The Beijing-Tianjin-Hebei urban agglomeration has the lowest level of green transformation; 2) From a dynamic perspective, technological progress is the main driving factor for improving the efficiency of green transformation in the three major urban agglomerations. Therefore, the government should pay special attention to the progressiveness of technology when formulating relevant policies to promote urban green transformation; 3) From the perspective of spatiotemporal differences, there are significant differences in the spatiotemporal characteristics of green transformation among the three major urban agglomerations, and there are significant differences in green transformation strategies among different urban agglomerations. Eliminating environmental factors and random interference is necessary for accurately measuring the efficiency of green transformation in urban agglomerations; 4) From the perspective of influencing factors, factors such as industrial structure upgrading, green innovation level, and environmental regulation intensity jointly affect the efficiency of green transformation in urban agglomerations. Based on this, we should pay attention to the differences between urban agglomerations and implement policies tailored to local conditions; Strengthen the network system of urban agglomerations and avoid conflicts between cities; Encourage green technology innovation, accelerate industrial structure upgrading, and so on. This article focuses on the issue of green transformation in urban agglomerations, and conducts research from three perspectives: efficiency measurement, influencing factors, and implementation mechanisms. A relatively systematic theoretical framework for green transformation in urban agglomerations is formed, and an evaluation index system for green transformation efficiency in urban agglomerations is constructed and optimized. The composition mechanism of the five dimensional evaluation system for transformation efficiency is analyzed, and the bottleneck and breakthrough direction of the three major urban agglomerations in China in the development process are grasped. It has a good demonstration effect on the green transformation of other urban agglomerations. [ABSTRACT FROM AUTHOR]

As a new idea of urban risk management, building resilient cities with the ability to resist, eliminate, and adapt to uncertain risks is of great importance to mitigate risk impacts and promote sustainable urban development. Based on the adaptive cycle model and the characteristics of an urban system, this study analyzes the resilience levels of cities, urban agglomerations, and provinces and their adaptive stages. The results show that (1) the comprehensive resilience of cities in the five provinces of northwest China is on the rise and that the differences between cities are gradually narrowing. The development stages of the urban adaptive cycle can be divided into six stages: the rapid exploitation stage, exploitation-conservation stage, stable conservation stage, conservation-release stage, development reorganization stage, and reorganization-exploitation stage. (2) The spatial distribution of the comprehensive resilience of urban agglomerations is "high in the southeast and low in the northwest," and the development stage of the adaptive cycle is consistent with its central city or central region. (3) The level of resilience varies greatly among provinces, and the development stage of the adaptive cycle is equivalent to the average level of all cities in the province and is closely related to their respective development forces and urban problems. These findings can provide reference for policymakers to formulate scientific resilience building strategies to achieve regional sustainable development. [ABSTRACT FROM AUTHOR]

Accurately identifying the boundary of urban clusters is a crucial aspect of studying the development of urban agglomerations. This process is essential for comprehending and optimizing smart and compact urban development. Existing studies often rely on a single category of data, which can result in coarse identification boundaries, insufficient detail accuracy, and slight discrepancies between the coverage and the actual conditions. To accurately identify the extent of urban clusters, this study proposes and compares the results of three methods for identifying dense urban areas of three major agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area. The study then integrates the results of these methods to obtain a more effective identification approach. The social economic method involved extracting a density threshold based on the fused nuclear density of socio-economic vitality data, including population, GDP, and POI, while the remote sensing method evaluated feature indices based on remote sensing images, including the density index, continuity index, gradient index, and development index. The traffic network method utilizes land transportation networks and travelling speeds to identify the minimum cost path and delineate the boundary by 20–30 min isochronous circles. The results obtained from the three methods were combined, and hotspots were identified using GIS overlay analysis and spatial autocorrelation analysis. This method integrates the multi-layered information from the previous three methods, which more comprehensively reflects the characteristics and morphology of urban clusters. Finally, the accuracy of each identification result is verified and compared. The results reveal that the average overall accuracy (OA) of the three areas delineated by the first three methods are 57.49%, 30.88%, and 33.74%, respectively. Furthermore, the average Kappa coefficients of these areas are 0.4795, 0.2609, and 0.2770, respectively. After performing data fusion, the resulting average overall accuracy (OA) was 85.34%, and the average Kappa coefficient was 0.7394. These findings suggest that the data fusion method can effectively delineate dense urban areas with greater accuracy than the previous three methods. Additionally, this method can accurately reflect the scope of urban clusters by depicting their overall boundary contour and the distribution of internal details in a more scientific manner. The study proposes a feasible method and path for the identification of urban clusters. It can serve as a starting point for formulating spatial planning policies for urban agglomerations, aiding in precise and scientific control of boundary growth. This can promote the rational allocation of resources and optimization of spatial structure by providing a reliable reference for the optimization of urban agglomeration space and the development of regional spatial policies. [ABSTRACT FROM AUTHOR]

Improving carbon emission efficiency is the most direct and effective way to reduce pollution. Leading the construction of a resource-saving and environment-friendly society is an important goal of the coordinated development of urban agglomerations in the middle reaches of the Yangtze River. However, there is no systematic evidence to prove whether this policy can improve carbon emission efficiency. Taking 31 cities in the urban agglomeration in the middle reaches of the Yangtze River as the research area, we aimed to use the index decomposition method, the super-efficiency slack-based model, and the difference-in-difference model to examine the effect of policies on improving carbon efficiency. The results show that (1) regional coordinated development policies have a significant effect on improving the carbon emission efficiency of urban agglomerations, and there is an obvious imbalance in carbon emission efficiency among cities. (2) The impact of regional coordinated development policies on urban carbon emission efficiency is heterogeneous. We have grouped 31 cities according to their centrality, industrial transfer characteristics, and urban cluster characteristics. Policies have heterogeneous effects on cities with different functions and positioning. (3) Policy effects have opposite effects on urban carbon emission efficiency through urbanization rate and population density, while the effect of urban greening rate is not significant. The research results can provide a reference for China's urban agglomeration to achieve sustainable development and promote the construction of low-carbon cities. [ABSTRACT FROM AUTHOR]

The article presents abstracts on land use planning topics, including "Historical Amnesia: New Urbanism and the City of Tomorrow," "More Than Sector Theory: Homer Hoyt's Contributions to Planning Knowledge" and "Methodology for the Survival Analysis of Urban Building Stocks."