The high-speed economic growth of mega city-regions in China has been characterized by rapid urbanization accompanied by a series of environmental issues ranging from widespread soil contamination to groundwater depletion. This article begins with an analysis of the interaction between urbanization and the ecological system and reviews existing frameworks for analyzing urban and ecological systems. By taking the Beijing-Tianjin-Hebei region as an example, the article introduces a conceptual framework to analyze mega city-regions and forecast possible interactions between urbanization and eco-environment by applying simulation model. The proposed framework and its components can provide guidance to identify the impacts of urbanization and external forces such as globalization on eco-environment by integrating the internal and external factors, synthesize the complex components of mega city-regions in databases, understand and diagnose the casual relationship between urban policies and ecological consequences.

This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. First, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. Finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities. With the continuous development of information technology, the Internet data have not only objectively recorded all kinds of spatial information, but also performed the subjective evaluation of public places in the city. Previous study on urban computing and big data has mostly been explored by interdisciplinary studies in the field of computer professionals; however, it is often difficult for them to take into consideration of urban planning. This article takes exploratory improvement based on existing technology application. Specifically, the research tries to obtain open source data of public facilities through data mining, not only to evaluate the public facilities from objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of public facilities. Research overviewOn the study of public facilities evaluation, scholars used objective data by various models, mainly focusing on assessment and measurement of the accessibility and fairness (Chen 2012;Han and Lu 2012;Yang and Xu 2015). In other studies, the ecological and economic factors were introduced into the space evaluation of public facilities, and the suitability of the layout of urban

The impact of built environment features on tourists’ walking behaviors has received growing attention. Although many researchers have observed the effects of micro-scale factors, the impact of culture-related factors on walking behaviors has been frequently overlooked. Therefore, it is vital to synthesize those micro-scale variables to develop a more holistic picture, and incorporating a cultural perspective is an imperative for the preservation and vitality enhancement of historic streets. In our study, a micro-scale built environment (MiBE) variable system was constructed to capture the features of historic streets, and 109 visitors were tracked in Wudaoying Hutong to record their walking-stopping behaviors. The results revealed four primary components affecting walking-stopping behaviors, among which transparency was the most influential factor, followed by the transitional space between streets and buildings, contributing to 49.8% and 21.6%, respectively. Notably, the non-negligible impact of two culture-related factors, including the contrast between Chinese and Western styles and traditional Chinese features, was also revealed, contributing to 28.6% of the total observed activities. We further compared four different types of micro-scale factors of the built environment and the corresponding walking-stopping behaviors, providing both scientific and theoretical reflections for preserving and renewing historic streets.

Rapid urbanization in China has been accompanied by spatial inefficiency in patterns of human activity, of which ‘ghost towns’ are the most visible result. In this study, we measure the density and diversity of human activity in the built environment and relate this to various explanatory factors. Using the Pearl River Delta (PRD) as an empirical case, our research demonstrates the distribution of human activity by multi-source data and then explores its dynamics within these areas. This empirical study is comprised of two parts. The first part explores location information regarding human activity in urbanized areas and shows density and diversity. Regression models are applied to explore how density and diversity are affected by urban scale, morphology and by a city’s administrative level. Results indicate that: 1) cities with smaller populations are more likely to be faced with lower density and diversity, but they derive greater marginal benefits from improving land use efficiency; 2) the compactness of the layout of urban land, an index reflecting the plane shapes of the built environment, is highly correlated with density and diversity in built-up areas; and 3) the administrative importance of a city has a significant and positive impact on the density of human activity, but no obvious influence on its diversity.

Urban agglomeration is an essential spatial support for the urbanization strategies of emerging economies, including China, especially in the era of mediatization. From a hybrid space perspective, this paper invites TikTok cross-city check-in records to empirically investigate the vertical and flattened distribution characteristics of check-in networks of China’s three major urban agglomerations by the hierarchical property, community scale, and node centrality. The result shows that (1) average check-in flow in the Yangtze River Delta, Beijing-Tianjin-Hebei, and Pearl River Delta network decreases in descending order, forming a Z-shaped, single-point radial, and N-shaped structure, respectively. (2) All three urban agglomerations exhibit a nexus community structure with the regional high-flow cities as the core and the surrounding cities as the coordinator. (3) Geographically proximate or recreation-resource cities have a high degree of hybrid spatial accessibility, highlighting their nexus role. Finally, the article further discusses the flattened evolutionary structure of the check-in network and proposes policy recommendations for optimizing check-in networks at both the digital and geospatial levels. The study gains from the lack of network relationship perspective in the study of location-based social media and provides a novel research method and theoretical support for urban agglomeration integration in the context of urban mediatization.