佳文速递(4月） | 最新城市发展研究精选(英)

ZHANG Quan, NIE Huijuan, LI Xiaoying

Abstract: Based on the Mixed Logit model, the willingness-to-pay (WTP) for waste mobile phone recycling among college students in Beijing was investigated using a discrete choice experiment method. The research results three aspects of respondents’ choices and WTP. (1) Their choices are positively affected by information security, recycling price, recycling method and payment method, and negatively affected by payment amount. (2) Respondents have the highest WTP for information security (30.04 yuan), followed by the recycling price (5.94 yuan) and payment method (4.41 yuan), and the lowest WTP for recycling models (2.87 yuan). (3) Personal socio-economic characteristics such as gender, annual household income, and the number of mobile phones held by respondents have significant impacts on their recycling WTP. The deeper the respondents' awareness of the environmental protection effect of waste mobile phone recycling, the more enthusiasm they have for the recycling behavior, the higher their participation in recycling, and the higher their WTP for recycling.

Key words: choice experiment method; college students; mixed Logit model; waste mobile phone recycling; willingness to pay

Abstract: The power sector is a critical industry in China's efforts to attain its carbon peaking and carbon neutrality targets. Analyzing the spatio-temporal pattern and influencing factors of the aggregate carbon intensity (ACI) of electricity generation at the city scale is of great significance for refining electricity emission reduction policies and guiding regional collaborative carbon reduction. This study utilizes micro-level data from 21543 power plants with a capacity of 6000 kW or above, in combination with multiple sources of statistical data related to energy, economy, and society, to calculate ACI of electricity generation in China's cities in 2003, 2010, and 2017. Exploratory spatial data analysis, IDA-LMDI decomposition, and STIRPAT modeling are employed to reveal the spatio-temporal patterns and influencing factors. The findings show that: (1) From 2003 to 2017, the ACI of China's electricity generation sector exhibited a notable decline, albeit with a trend of increasing internal differences. Significant spatial differentiation was observed at city scale, with the northeast half of the Bole-Taipei Line maintaining higher levels than the southwest half over an extended period. The degree of spatial agglomeration also increased significantly during this period, with Northeast and North China identified as regions of particular concern in the decline of ACI. (2) The thermal efficiency was the dominant factor in the decline of ACI in the early stage, whereas the electricity generation structure became increasingly influential in the later period. Meanwhile, other power system factors exhibited less influence, though significant spatial differences were observed. (3) The impact of diverse socio-economic determinants on ACI fluctuated over time, engendering modifications in the attributes of the power system through their interactions with the intricate network of power demand, policy, technology, and clean energy expansion opportunities. (4) An inverted U-shaped correlation was observed between ACI and per capita GDP in 2003 and 2010, which transformed into a linear positive association in 2017. This shift can be attributed to the swift emergence of renewable electricity that have challenged the traditional interpretive framework of the Environmental Kuznets Curve hypothesis, which was previously applicable only to thermal power generation. In the future, endeavors aimed at reducing emissions in the electricity sector must comprehensively acknowledge the spatial heterogeneity and sustain attention towards the ramifications of abrupt shifts arising from emerging technologies on the conventional theoretical framework. 

Keywords: aggregate carbon intensity of electricity generation; city scale; Environmental Kuznets Curve hypothesis; spatio-temporal pattern; influencing factor

LIU Haimeng

Study on the relationship between green space and surface heat island evolution in urban built-up areas based on morphology: The case of Xi'an city

WANG Liguo, BAI Yongping, LIANG Jianshe, ZHANG Chunyue, JING Linxiang, DU Yaming, ZOU Jiacheng

Key words：morphological spatial pattern analysis urb，an green space，surface urban heat island，heat island expansion

WEI Wei, ZHANG Yang, HONG Mengyao*, XIA Junnan

WANG Jin, SHEN Yue*

Keywords: built environment; perceived environment; social network; neighborhood interaction; Shanghai

A Method for Spatiotemporal Object Behavior-Driven Interactive Control of Urban Sensing Facilities with Virtual-Reality Integration

YANG Fei, Li Xiang *, CAO Yibing, ZHAO Xinke, WANG Lina, WU Ye

Abstract: In recent years, with the continuous development and rapid iteration of emerging technologies such as mobile communication, big data, the Internet of Things (IoT), Artificial Intelligence (AI), digital twins, and autonomous driving, new smart cities have become a significant frontier in the field of Geographic Information Systems (GIS) applications. Digital twin cities represent a complex integrated technological system that underpins the development of next-generation smart cities. Intelligent, holistic mapping for digital twin cities relies on comprehensive urban sensing, and the interactive control of urban sensing facilities plays a pivotal role in achieving the seamless integration of the physical and digital aspects of digital twin cities, fostering the convergence of entities within the urban environment. Describing spatiotemporal entities of the real world through a spatiotemporal data model, as well as modeling the behavioral capabilities of these entities using spatiotemporal object behavior, represents not only an innovative extension of GIS spatiotemporal data models but also addresses the practical requirements of triadic fusion and interactive analysis of human, machine, and object components with the development of digital twin city. As a crucial facet of urban infrastructure, urban sensing facilities epitomize distinctive spatiotemporal entities. Current research into the interactive control of these facilities is predominantly concentrated within the domains of the IoT, Virtual Reality/Augmented Reality (VR/AR), and GIS. However, these domains often lack research pertaining to interactive control of urban sensing facilities within the GIS-based digital realm. To tackle these issues, a viable approach involves mapping the direct physical control processes of humans over objects in the Internet of Things domain to the realm of GIS. Specifically, this involves using a GIS spatiotemporal data model to abstractly represent urban sensing facilities in the real world as spatiotemporal entities. These entities are then expressed as spatiotemporal objects within a spatial information system. Subsequently, the changes or actions of these facility spatiotemporal entities are uniformly abstracted as the behavioral capabilities of these spatiotemporal facility objects. Ultimately, the interaction control of these sensing facilities by humans is transformed into a process where humans invoke the behavioral capabilities of facility spatiotemporal objects, resulting in specific outcomes. Based on the aforementioned idea, this study employs a multi-granular spatiotemporal object data model to construct behavior capabilities for urban sensing facilities. Building upon this foundation, a spatiotemporal object behavior-driven approach for interactive control of urban sensing facilities with virtual-reality integration is introduced. By constructing a "quintuple" model for interactive control of facility objects, this approach facilitates users in engaging in interactive control through a reciprocal linkage between virtual scenarios and physical facilities. This mechanism effectively translates the process of urban sensing facility interaction control based on direct communication commands into the digital world, providing theoretical and technical support for the intelligent and interactive analytical applications of sensing facilities within digital twin cities. Experimental results substantiate the effectiveness and feasibility of the proposed method for interactive control of urban sensing facilities.

Key words: digital twin city; urban sensing facilities;  spatiotemporal data model; spatiotemporal objects; behavioral capabilities;behavioral components; interactive control

YIN Yanzhong, WU Qunyong *, LIN Han, ZHAO Zhiyuan

Abstract：The effect of "space-time compression" caused by "space flow" breaks the independent allocation of resources between cities and drives the formation of regionally integrated development pattern, and the organizational structure and operation mechanism of the urban network cannot be separated from the inter-city relationship. Based on Baidu migration big data from October 2021 to September 2022, this paper constructs the intercity population flow network for 366 cities in China. At the node level, a population flow surpassing index is proposed to measure urban centrality and explore the spatial clustering characteristics of urban centrality. At the network community level, the monthly intercity population flow pattern and characteristics of 366 cities are analyzed. The results show that: (1) The population flow surpassing index considering flow direction meets the actual needs of intercity population mobility evaluation for measuring urban centrality and can effectively characterize the centrality of cities in the intercity population flow network. Using Baidu Migration big data from January 2023 to April 2023 after the end of the epidemic for comparison, we found that the central impact on national central city is small due to the prevention and control of COVID-19 transmission; (2) Cities in the intercity population flow network exhibit "High-High (HH)" and "Low-Low (LL)" agglomeration characteristics according to their centrality. HH clustering areas are formed in the eastern coastal and central regions, while LL clustering areas are mainly located at the edge of the Qinghai Tibet Plateau, the edge of the three northeastern provinces, and some areas in Hainan Island; (3) The intercity population flow pattern shows different characteristics in different months due to the influence of holidays, COVID-19 transmission, etc., generally in accordance with the first law of geography, and exhibits provincial differentiation characteristics; (4) The finding of urban cohesive subgroups shows that the intercity population flow patterns of Chengdu-Chongqing Urban Agglomeration, Greater Bay Area, Central Plains Urban Agglomeration, Guanzhong Plain Urban Agglomeration, Yangtze River Delta Urban Agglomeration, and other urban clusters are relatively stable, characterized by cross-provincial population flow integration. The Shandong Peninsula Urban Agglomeration and the Beijing-Tianjin-Hebei Urban Agglomeration have close connection in intercity population flow patterns, characterized by cross-urban cluster intercity population flow. The intercity population flow pattern within Zhejiang Province is gradually enhanced, and the urban clusters in middle reaches of Yangtze River and the west bank of the Taiwan Strait haven’t yet formed a stable population flow pattern across provincial borders.