Spatial Evolution of Producer Service Sectors and Its Influencing Factors in Cities: A Case Study of Hangzhou, China

Wu, Yizhou; Fan, Peilei; You, Heyuan

doi:10.3390/su10040975

Cited by 11 publications

(13 citation statements)

References 62 publications

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“…Results show that Hangzhou's producer service sector is still mainly concentrated in the central business district (CBD). However, a distinct trend of diffusion to suburban areas was observed, which formed several secondary clusters on the periphery of the city [21].…”

Section: How To Promote Socio-economic Sustainability In the Smart VImentioning

confidence: 99%

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

2018

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Abstract:Research on smart cities matures and new interdisciplinary approaches to the study of smart cities are proposed. At the same time, problems pertinent to communities inhabiting rural areas tend to be addressed, as if by the way, i.e., as a part of discussions in neighboring fields of research, be it environmental studies, sociology, or agriculture. Arguably, the concept of 'the village' has been largely absent in the academic debate, even if rural areas and countryside communities have been a subject of concern for robust policy frameworks, such as the European Union's Cohesion Policy and Common Agricultural Policy. As a result, when advances in sophisticated information and communication technology (ICT) led to the emergence of a rich body of research on smart cities, the application and usability of ICT in the context of a village remained underdiscussed in the literature. Through this Special Issue, and the Editors' earlier research on this topic, the Editors hope that the idea of the 'smart village' will be introduced into the debate. Against this backdrop, the objective of this opening review is three-fold: (i) to outline the conceptual boundaries of the term smart village, (ii) to highlight the thrust of the challenge inherent in smart villages research, and (iii) to shed light on the smart village research agenda as it unfolds. The relevance and validity of these claims are supported by references to research submitted to the Special Issue titled "Sustainable Smart Cities and Smart Villages Research".

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Section: How To Promote Socio-economic Sustainability In the Smart VImentioning

confidence: 99%

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

2018

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“…When recording the sample plots, the steps for determining their geographic coordinates are as follows. (1) The precise four-parcel information is mainly obtained from the information of land bidding, auction, and publicity published on the official website of the Hangzhou Land and Resources Bureau (Figure 2). The location is initially determined in conjunction with Baidu Map.…”

Section: Site Characteristicsmentioning

confidence: 99%

“…Upon its establishment, a city may be viewed as a collection of residential, commercial, industrial, and other multi-functional spaces [1]. Various types of urban land have different roles in urban economy and life, carrying different functions of urban system operations [2].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Non-Stationarity and Its Influencing Factors of Commercial Land Price: A Case Study of Hangzhou, China

Garang

et al. 2021

Land

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Investigating the characteristics and mechanisms of the spatial and temporal variations of commercial land prices and its major subdivisions has great theoretical and practical significance in the study of urban economy and its spatial refinement management. Unlike general commodity prices, land prices are influenced by geographical location and tend to fluctuate over time. However, most scholars have not explored the influence mechanism of commercial land prices in both time and space. To help bridge this gap, this study takes the sample commercial land prices in the main urban area of Hangzhou from 2006 to 2015 as the empirical research object and investigates the spatiotemporal evolution mechanism of urban commercial land prices through a comparative analysis of the multiple regression analysis (MRA) with ordinary least squares (OLS), the geographically weighted regression (GWR), the temporally weighted regression (TWR), and the geographically and temporally weighted regression (GTWR) models. Results indicate that the land prices of land for financial facilities (Commercial Land Category 1) and commercial-business land (Commercial Land Category 2) in Hangzhou show different spatial and temporal evolutions and are influenced by the common factors of residential land price level (PL), maturity of living services (EN), and plot ratio (FRO) in the district. Meanwhile the main difference between the two influencing factors is the significant difference in sensitivity to locational centrality and industrial structure. Furthermore, we find that the spatial and temporal evolution of commercial land prices has three main mechanism: location selection, point-axis evolution, and function-promoting. Our findings will provide guidelines for scientifically guiding the coordinated development of urban land price and industrial economy and realizing the fine management and allocation of urban spatial resources.

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“…And during the rapid urbanization process, the urban environment had a more and more negative impact on the surrounding areas (Han et al 2015b). On the other hand, the polycentric urban development, accompanied by consistent growth of population, caused tight environmental stress in the outskirts of the city centres (Sun et al 2012, Han et al 2015a, Wu et al 2018, Sun and Lv 2020. Lin et al found that the decline rate of PM 2.5 in most urban areas was higher than that in other areas .…”

Section: Introductionmentioning

confidence: 99%

The rationality of PM2.5 monitoring sites’ locations based on exposure level across eastern China

Yan

Shi

Yang

2022

Environ. Res. Commun.

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Due to the heterogeneity of PM2.5 and population distribution, the representativeness of existing monitoring sites is questionable when the monitored data were used to assess the population exposure. By comparing the PM2.5 concentration from a satellite-based dataset named the China High Air Pollutants (CHAP), population and exposure level in urban areas with monitoring stations (UWS) and without monitoring stations (UNS), we discussed the rationality of the current spatial coverage of monitoring stations in eastern China. Through an analysis of air pollution in all urban areas of 256 prefectural-level municipalities in eastern China, we found that the average PM2.5 concentration in UNS in 2015 and 2018 were 52.26 μg/m3 and 41.32 μg/m3, respectively, which were slightly lower than that in UWS (52.98 μg/m3 and 41.48 μg/m3). About 12.1% of the prefectural-level municipalities had higher exposure levels in certain UNS than those in UWS. With the faster growth of UNS population, the gap between exposure levels of UNS and UWS were narrowing. Hence, currently prevalent administration-based principle of site location selection might have higher risk of missing the non-capital urban areas with relatively higher PM2.5 exposure level in the future.

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Spatial Evolution of Producer Service Sectors and Its Influencing Factors in Cities: A Case Study of Hangzhou, China

Cited by 11 publications

References 62 publications

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

Spatio-Temporal Non-Stationarity and Its Influencing Factors of Commercial Land Price: A Case Study of Hangzhou, China

The rationality of PM2.5 monitoring sites’ locations based on exposure level across eastern China

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