scholarly journals Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach

2019 ◽  
Vol 11 (2) ◽  
pp. 479 ◽  
Author(s):  
Shijie Li ◽  
Chunshan Zhou ◽  
Shaojian Wang ◽  
Shuang Gao ◽  
Zhitao Liu
Keyword(s):  
Spatial Heterogeneity ◽  
Urban Form ◽  
Urban Expansion ◽  
Coastal Region ◽  
Policy Implications ◽  
Urban Systems ◽  
Theoretical Understanding ◽  
Chinese Cities ◽  
Shape Irregularity ◽  
Spatially Varying

It is of great significance to investigate the determinants of urban form for shaping sustainable urban form. Previous studies generally assumed the determinants of urban form did not vary across spatial units, without taking spatial heterogeneity into account. In order to advance the theoretical understanding of the determinants of urban form, this study attempted to examine the spatial heterogeneity in the determinants of urban form for 289 Chinese prefecture-level cities using a geographically weighted regression (GWR) method. The results revealed the spatially varying relationship between urban form and its underlying factors. Population growth was found to promote urban expansion in most Chinese cities, and decrease urban compactness in part of the Chinese cities. Cities with larger administrative areas were more likely to have dispersed urban form. Industrialization was demonstrated to have no impact on urban expansion in cities located in the eastern coastal region of China, which constitutes the country’s most developed regions. Local financial revenue was found to accelerate urban expansion and increase urban shape irregularity in many Chines cities. It was found that fixed investment exerted a bidirectional impact on urban expansion. In addition, urban road networks and public transit were also identified as the determinants of urban form for some cities, which supported the complex urban systems (CUS) theory. The policy implications emerging from this study lies in shaping sustainable urban form for China’s decision makers and urban planners.

scholarly journals Spatial Patterns of Urban Expansion in Chinese Cities

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Jing Yao ◽  
Ya Ping Wang ◽  
Xiaoxiang Zhang
Keyword(s):  
Spatial Patterns ◽  
Urban Form ◽  
Urban Expansion ◽  
Urban Land Use ◽  
Policy Implications ◽  
Geographical Information ◽  
Western China ◽  
City Development ◽  
Chinese Cities ◽  
The City

<p><strong>Abstract.</strong> China has experienced high rate urbanization in recent years, with urban population increased from 460 to 750 million and the built-up area of metropolis expanded by almost 60% since 2000. Urban landscape has been dramatically changed by intensified inner-city development and urban sprawl. In recent years, the changes in urban form has transformed from expansion to restructuring. A good understanding of urban expansion and spatial restructuring as a consequence of urbanization has important policy implications, enhancing the knowledge of spatial variations in urban growth in transitional Chinese cities and assisting with sustainable urban and regional planning.</p><p>Using the Landsat satellite images from 1995 to 2015, this research explores urban expansion and its spatial patterns in second-tier Chinese cities, taking Tianjin, Hangzhou and Chengdu as examples, which are the leaders in the urbanization in Northern, Eastern and Western China, respectively. The study area includes the city proper in the three case study cities. Figure 1 shows the expansion of urban area in the three cities over the study time period. By visual inspection, it can be observed that the spatial pattern of urban land use growth varies across the three cities. For example, Tianjin has been largely expanding towards the east, particularly the Tianjin Binhai New Area, which has been rapidly developed into a new city core. The city of Chengdu seems having been expanding toward all directions of the surrounding area, integrated with the adjacent towns into a larger urban agglomeration. Further work will focus on quantitative analysis of the spatial patterns of urban expansion using geographical information system (GIS)-based spatial analytics, as well as the association between urban expansion and socioeconomic changes, with a reflection on the role of national/local policies.</p>

scholarly journals Exploring the Joint Impacts of Natural and Built Environments on PM2.5 Concentrations and Their Spatial Heterogeneity in the Context of High-Density Chinese Cities

2021 ◽  
Vol 13 (21) ◽  
pp. 11775
Author(s):  
Shanyou Duan ◽  
Qian Liu ◽  
Dumei Jiang ◽  
Yulin Jiang ◽  
Yinzhi Lin ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Spatial Heterogeneity ◽  
Urban Form ◽  
Central City ◽  
High Density ◽  
Air Pollutant ◽  
Least Square ◽  
Built Environments ◽  
Chinese Cities

Air pollution in China has attracted wide interest from the public and academic communities. PM2.5 is the primary air pollutant across China. PM2.5 mainly comes from human activities, and the natural environment and urban built environment affect its distribution and diffusion. In contrast to American and European cities, Chinese cities are much denser, and studies on the relationships between urban form and air quality in high-density Chinese cities are still limited. In this paper, we used the ordinary least square (OLS) and geographical weighted regression (GWR) models, selected an already high-density city, Shenzhen, as the study area, and explored the effects of the natural and built environments on air pollution. The results showed that temperature always had a positive influence on PM2.5 and wind speed had a varied impact on PM2.5 within the city. Based on the natural factors analysis, the paper found that an increase in the floor area ratio (FAR) and road density may have caused the increase in the PM2.5 concentration in the central city. In terms of land use mix, land use policies should be adopted separately in the central city and suburban areas. Finally, in terms of spatial heterogeneity, the GWR models achieved much better performances than the global multivariate regression models, with lower AICc and RMSE values and higher adjusted R2 values, ultimately explaining 60% of the variance across different city areas. The results indicated that policies and interventions should be more targeted to improve the air environment and reduce personal exposure according to the spatial geographical context.

scholarly journals Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China’s Megacities

2018 ◽  
Vol 15 (8) ◽  
pp. 1565 ◽  
Author(s):  
Chunshan Zhou ◽  
Shijie Li ◽  
Shaojian Wang
Keyword(s):  
Air Pollution ◽  
Developing Countries ◽  
Urban Form ◽  
Urban Expansion ◽  
Pollution Index ◽  
Clean Energy ◽  
Developed Countries ◽  
Series Data ◽  
Air Pollution Index ◽  
Shape Irregularity

Urban form is increasingly being identified as an important determinant of air pollution in developed countries. However, the effect of urban form on air pollution in developing countries has not been adequately addressed in the literature to date, which points to an evident omission in current literature. In order to fill this gap, this study was designed to estimate the impacts of urban form on air pollution for a panel made up of China’s five most rapidly developing megacities (Beijing, Tianjin, Shanghai, Chongqing, and Guangzhou) using time series data from 2000 to 2012. Using the official Air Pollution Index (API) data, this study developed three quantitative indicators: mean air pollution index (MAPI), air pollution ratio (APR), and continuous air pollution ratio (CAPR), to evaluate air pollution levels. Moreover, seven landscape metrics were calculated for the assessment of urban form based on three aspects (urban size, urban shape irregularity, and urban fragmentation) using remote sensing data. Panel data models were subsequently employed to quantify the links between urban form and air pollution. The empirical results demonstrate that urban expansion surprisingly helps to reduce air pollution. The substitution of clean energy for dirty energy that results from urbanization in China offers a possible explanation for this finding. Furthermore, urban shape irregularity positively correlated with the number of days with polluted air conditions, a result could be explained in terms of the influence of urban geometry on traffic congestion in Chinese cities. In addition, a negative association was identified between urban fragmentation and the number of continuous days of air pollution, indicating that polycentric urban forms should be adopted in order to shorten continuous pollution processes. If serious about achieving the meaningful alleviation of air pollution, decision makers and urban planners should take urban form into account when developing sustainable cities in developing countries like China.

scholarly journals What is beyond the edges? Gated communities and their role in China’s desire for harmonious cities

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Badiaa Hamama ◽  
Jian Liu
Keyword(s):  
Economic Growth ◽  
Real Estate ◽  
Urban Form ◽  
Gated Communities ◽  
Urban Fabric ◽  
Chinese Cities ◽  
The Matrix ◽  
Process Of Urbanization ◽  
New Urbanization

Abstract During the rapid process of urbanization in post-reform China, cities assumed the role of a catalyst for economic growth and quantitative construction. In this context, territorially bounded and well delimited urban cells, globally known as ‘gated communities’, xiaoqu, continued to define the very essence of Chinese cities becoming the most attractive urban form for city planners, real estate developers, and citizens alike. Considering the guidelines in China’s National New Urbanization Plan (2014–2020), focusing on the promotion of humanistic and harmonious cities, in addition to the directive of 2016 by China’s Central Urban Work Conference to open up the gates and ban the construction of new enclosed residential compounds, this paper raises the following questions: As the matrix of the Chinese urban fabric, what would be the role of the gated communities in China’s desire for a human-qualitative urbanism? And How to rethink the gated communities to meet the new urban challenges? Seeking alternative perspectives, this paper looks at the gated communities beyond the apparent limits they seem to represent, considering them not simply as the ‘cancer’ of Chinese cities, rather the container of the primary ingredients to reshape the urban fabric dominated by the gate.

scholarly journals Random Parameters and Spatial Heterogeneity using Rchoice in R

REGION ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 1-19
Author(s):  
Mauricio Sarrias
Keyword(s):  
Spatial Heterogeneity ◽  
Random Parameters ◽  
Varying Coefficients ◽  
Micro Level ◽  
Modeling Strategy ◽  
Spatially Varying ◽  
Geographical Space

This study focus on models with spatially varying coefficients using simulations.  As shown by Sarrias (2019), this modeling strategy is intended to complement the existing approaches by using variables at micro level and by adding flexibility and realism to the potential domain of the coefficient on the geographical space. Spatial heterogeneity is modelled by allowing the parameters associated with each observed variable to vary “randomly” across space according to some distribution. To show the main advantages of this modeling strategy, the Rchoice package in R is used.

scholarly journals Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China

2022 ◽  
Vol 11 (1) ◽  
pp. 67
Author(s):  
Meijie Chen ◽  
Yumin Chen ◽  
John P. Wilson ◽  
Huangyuan Tan ◽  
Tianyou Chu
Keyword(s):  
Risk Factors ◽  
Health Risk ◽  
Spatial Heterogeneity ◽  
Influencing Factors ◽  
Mainland China ◽  
Spatial Filtering ◽  
Varying Coefficient Model ◽  
Health Risk Factors ◽  
Eigenvector Spatial Filtering ◽  
Spatially Varying

The COVID-19 pandemic has led to many deaths and economic disruptions across the world. Several studies have examined the effect of corresponding health risk factors in different places, but the problem of spatial heterogeneity has not been adequately addressed. The purpose of this paper was to explore how selected health risk factors are related to the pandemic infection rate within different study extents and to reveal the spatial varying characteristics of certain health risk factors. An eigenvector spatial filtering-based spatially varying coefficient model (ESF-SVC) was developed to find out how the influence of selected health risk factors varies across space and time. The ESF-SVC was able to take good control of over-fitting problems compared with ordinary least square (OLS), eigenvector spatial filtering (ESF) and geographically weighted regression (GWR) models, with a higher adjusted R2 and lower cross validation RMSE. The impact of health risk factors varied as the study extent changed: In Hubei province, only population density and wind speed showed significant spatially constant impact; while in mainland China, other factors including migration score, building density, temperature and altitude showed significant spatially varying impact. The influence of migration score was less contributive and less significant in cities around Wuhan than cities further away, while altitude showed a stronger contribution to the decrease of infection rates in high altitude cities. The temperature showed mixed correlation as time passed, with positive and negative coefficients at 2.42 °C and 8.17 °C, respectively. This study could provide a feasible path to improve the model fit by considering the problem of spatial autocorrelation and heterogeneity that exists in COVID-19 modeling. The yielding ESF-SVC coefficients could also provide an intuitive method for discovering the different impacts of influencing factors across space in large study areas. It is hoped that these findings improve public and governmental awareness of potential health risks and therefore influence epidemic control strategies.

Models, Methods, and Metrics to Measure Socioeconomic Resilience

2018 ◽  
pp. 346-367
Author(s):  
Carlos Gonçalves
Keyword(s):  
Social Structure ◽  
Case Studies ◽  
Urban Form ◽  
Urban Systems ◽  
Economic Base ◽  
Urban Resilience ◽  
Regional Context ◽  
The Social ◽  
Indicator Matrix ◽  
Selection Of

This chapter aims to discuss concepts and methods to measure the landscape resilience of urban systems and test the indicators framework in the Portuguese regional context. The objective is to measure the performance and the direction of the urban changes in different phenomena, as well as to evaluate the level of urban systems preparation for a desired and undesired change adaptability. The approach to these issues is analyzed in the literature, dividing the aforementioned analysis into the resilience of the economic base, of the social structure, and of the urban form. In brief, the chapter meets three objectives: firstly, defining the framework of principles more commonly associated with urban resilience; secondly, providing a selection of indicators that embodies the different proposals of measurement; and thirdly, applying the indicator matrix to two Portuguese case studies (Caldas da Rainha and Évora urban systems).

scholarly journals Integrating Life Cycle Assessment into the Framework of Environmental Impact Assessment for Urban Systems: Framework and Case Study of Masdar City, Abu Dhabi

Environments ◽  
2019 ◽  
Vol 6 (9) ◽  
pp. 105
Author(s):  
Kavya Madhu ◽  
Stefan Pauliuk
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Urban Expansion ◽  
Desert Ecosystem ◽  
Abu Dhabi ◽  
Urban Systems ◽  
Analysis Tool

Planning urban expansion under the interconnected Sustainable Development Goals requires a systemic analysis of its environmental impacts. The benefits of integrating the widely used system analysis tool life cycle assessment (LCA) into the planning process tool environmental impact assessment (EIA) are described in the literature. However, not many applications of such an integration have been conducted. The aim of this study is to refine the framework for integrating LCA into the process of EIA and to apply this framework to an example of urban expansion: Masdar City in Abu Dhabi. The integrated framework builds on the complementarity between the scope and assessment steps of the tools and assesses the impacts for the areas of protection: human health, ecosystem, and resources. The framework is then applied to the vehicles, buildings, and infrastructure in the city’s first development phase (DP1). Major environmental stressors include the loss of existing desert ecosystem and the utilization of non-renewable sources of energy at various development stages of DP1. Substituting natural gas-based electricity with solar power could potentially save 46% of current carbon emissions. To mitigate the land transformation impacts, construction of “close-to-nature” artificial habitats, and increased use of low-carbon fuels is suggested.

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