The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China

Liu, Yanfang; Zhang, Xianghui; Pan, Xingyu; Ma, Xiuxin; Tang, Mingyang

doi:10.1016/j.cities.2020.102801

Cited by 126 publications

(65 citation statements)

References 94 publications

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“…At the same time, it should delineate cities where the chemical industry will focus on layout, and formulate optimized plans for subindustry division and industrial chain cooperation [75]. Many explorations have been done in the areas along the Yangtze River [76], and the experience should be summed up in other regions. Second, the Chinese central government should actively guide the transformation and upgrading of weak chemical cities and cultivate new, high-quality chemical cities.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

et al. 2021

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As an economic pillar, major resource consumer, and polluter of cities, the chemical industry determines many cities’ transformation, prosperity, and decay. It is thus a major concern for achieving the UN Sustainable Development Goals. In China, which is at the stage of accelerated industrialization that is varied across regions, the chemical industry has gradually retreated from developed cities, such as Beijing and Shanghai, in the eastern region, and has become the inevitable choice for industrialization of less-developed cities, such as Xi’an, Chengdu, and Chongqing, in the western region. This study took the perspectives of chemical industrial sectors and their spatial differences to understand the changing patterns of the chemical industry and its dominant cities. It identified chemical industrial cities (CICs), examined their spatial-temporal patterns with respect to their industry scale and structure, and accounted for factors influencing the spatial evolution from coastal areas to inland regions. The results show that large CICs were mainly located in coastal port regions with balanced industrial sectors, while small CICs were mainly distributed in inland areas with abundant oil and coal resources and a single dominant industrial sector. The location factors of ports, markets, and technology play important roles in the eastern region, while resource conditions and foreign direct investment promote the chemical industry’s development in the central, western, and northeastern cities. These findings improve the understanding of CICs’ spatial transformation and shed light on the policy-making of chemical industrial development in China and other developing countries.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

et al. 2021

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“…The PCCERR and PUP are consequently the main causes of local carbon emissions. In addition, production factors like population and capital are concentrated in these cities due to the polarizing effect of Chongqing and Chengdu on the economic and social resources of the surrounding areas [ 56 ]. Furthermore, PR and FD consequently have greater impacts on the carbon emissions of these cities, and each city’s influencing factors expresses unique characteristics.…”

Section: Resultsmentioning

confidence: 99%

Random forest analysis of factors affecting urban carbon emissions in cities within the Yangtze River Economic Belt

2021

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China became the country with the largest global carbon emissions in 2007. Cities are regional population and economic centers and are the main sources of carbon emissions. However, factors influencing carbon emissions from cities can vary with geographic location and the development history of the cities, rendering it difficult to explicitly quantify the influence of individual factors on carbon emissions. In this study, random forest (RF) machine learning algorithms were applied to analyze the relationships between factors and carbon emissions in cities using real-world data from Chinese cities. Seventy-three cities in three urban agglomerations within the Yangtze River Economic Belt were evaluated with respect to urban carbon emissions using data from regional energy balance tables for the years 2000, 2007, 2012, and 2017. The RF algorithm was then used to select 16 prototypical cities based on 10 influencing factors that affect urban carbon emissions while considering five primary factors: population, industry, technology levels, consumption, and openness to the outside world. Subsequently, 18 consecutive years of data from 2000 to 2017 were used to construct RFs to investigate the temporal predictability of carbon emission variation in the 16 cities based on regional differences. Results indicated that the RF approach is a practical tool to study the connection between various influencing factors and carbon emissions in the Yangtze River Economic Belt from different perspectives. Furthermore, regional differences among the primary carbon emission influencing factors for each city were clearly observed and were related to urban population characteristics, urbanization level, industrial structures, and degree of openness to the outside world. These factors variably affected different cities, but the results indicate that regional emission reductions have achieved positive results, with overall simulation trends shifting from underestimation to overestimation of emissions.

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“…Interaksi antara kecamatan-kecamatan yang terdapat di kawasan pesisir selatan DIY dengan Kota Yogyakarta sebagai pusat pertumbuhan eksisting diukur menggunakan model gravitasi. Model ini mengukur daya tarik menarik antar kota berdasarkan variabel jarak dan jumlah penduduk pada masing-masing wilayah yang berinteraksi (He et al, 2017;Liu et al, 2020).…”

Section: Analisis Hirarki Wilayahunclassified

Interaksi Wilayah Pusat Pertumbuhan Melalui Pendekatan Skalogram dan Gravitasi di Wilayah Pesisir Daerah Istimewa Yogyakarta

Yusliana

Devi

2020

gdk

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Regional development in Special Region of Yogyakarta is centered on its urban area, namely Kawasan Perkotaan Yogyakarta (KPY/ Yogyakarta Urban Aglomeration Area). This has created regional disparity and other concerns regarding the environmental sustainability in KPY. The new growth center is therefore needed, especially to solve the problem of regional disparity. This research was conducted to identify the district in the south coast of DIY that has the potentiallity to be developed as the new growth center. For this purpose, this research utilizes scalogram analysis combined with the gravity model and demographic analysis. The result shows that Wates District in Kulonprogo Regency has the potentiallity to be developed as the primary growth center in the south coast of DIY. Furthermore, Kretek District in Bantul Regency has the potentiallity to be developed as the secondary growth center. Meanwhile, Saptosari District in Gunungkidul Regency has the potentiallity to be developed as the tertiary growth center. Keywords: grafity, disparity, growth pole, scalogram, regional

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The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China

Cited by 126 publications

References 94 publications

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

Exploring the Classification and Restructuring of Chemical Industrial Cities in China: The Perspectives of Sectoral and Spatial Differences

Random forest analysis of factors affecting urban carbon emissions in cities within the Yangtze River Economic Belt

Interaksi Wilayah Pusat Pertumbuhan Melalui Pendekatan Skalogram dan Gravitasi di Wilayah Pesisir Daerah Istimewa Yogyakarta

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