New Spatial Strategy in China: Major Function Zoning of Beijing-Tianjin Metropolitan Area with Perspective from Ecological Economics

He, Jinliao; Zong, Yongqiang; Gebhardt, Hans

doi:10.1061/(asce)up.1943-5444.0000081

Cited by 8 publications

(4 citation statements)

References 23 publications

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“…By 2008 (Figure 5c), all the cities in the YRD had formed network agglomeration capabilities. Among them, the top five cities with agglomeration capacity are Wuxi (1,972), Suzhou (1,736), Hangzhou (1,428), Nanjing (1,352) and Ningbo (1,312). Notably, Shanghai's network agglomeration capacity is only 1/22 of the network radiation capacity, which has strong asymmetry.…”

Section: ) Urban Network Agglomeration Capacitymentioning

confidence: 99%

The Characteristics and Modes of Urban Network Evolution in the Yangtze River Delta in China from 1990 to 2017

et al. 2021

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Section: ) Urban Network Agglomeration Capacitymentioning

confidence: 99%

The Characteristics and Modes of Urban Network Evolution in the Yangtze River Delta in China from 1990 to 2017

et al. 2021

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“…Almost simultaneous with what has happened to urban forms, significant changes have taken place in the breadth and depth of regional integration. Starting with the elimination of trade barriers among countries in the East Asian region [29], regional integration has progressed by emphasizing shrinking the gaps in countries' internal development [30], which is particularly the case for China [31,32]. Its spatial carriers mainly include metropolitan areas, urban agglomerations, megaregions, and other urban spatial organizations.…”

Section: Integrative Process In the Cyrmmentioning

confidence: 99%

Development of Economic Integration in the Central Yangtze River Megaregion from the Perspective of Urban Network Evolution

2019

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Megaregions are the new engines of global and regional economic growth, and they often are considered a principal urbanization platform in China. To understand megaregional processes’ responses to China’s regional policies, this study focused on two aspects of integration development in the Central Yangtze River megaregion between 2000 and 2014: The internal collaborative networks using enterprises’ headquarters-branch locations as a proxy measurement and the role of regional transportation in the integration networks. Based on a three-step network analysis, the Central Yangtze River megaregion was increasingly similar to a polycentric urban system with Wuhan, Changsha, and Nanchang as the dominant service cities, and there were some indications of a preliminary urban network formation. However, integration development remained a government-led administrative process with administrative boundaries that significantly influenced the network structure. A panel regression analysis further suggested that transportation accessibility to the three central cities was the key determinant of network participation for the peripheral cities compared to economic performance. This work contributes to the debate on the hierarchical-administrative properties of China’s megaregions and transportation implications of the economic integration process.

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“…According to the study, identification requires thoroughly examining an interconnected regional ecosystem. The research could help to advance theory and the approach in China's cities and elsewhere [15,16]. The process model and steps for feasibility study using GEE presented by [17] are shown in Figure 2.…”

Section: Introductionmentioning

confidence: 99%

Digital and Geographical Feature Detection by Machine Learning Techniques Using Google Earth Engine for CPEC Traffic Management

Mazhar

Sun

Alsallakh

et al. 2022

Wireless Communications and Mobile Computing

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The center of human settlements is in the cities, which must have high-quality habitats for their inhabitants. Many megachallenges of urbanization, population development, global advancement, environmental destruction, traffic management, and climate change must be addressed. This study is aimed at understanding how to maintain balanced land development in rapidly urbanizing towns to solve this challenge and mobility issues. Climate and weather forecasts, land cover, environmental indices, nonoptical and optical wavelengths, water history, and air quality are only some of the datasets available on Google Earth Engine, a publicly usable data repository. Machine learning techniques, i.e., random forest (RF), support vector machine (SVM), and classification and regression tree (CART), are used to monitor spatial-temporal change regarding water, vegetation, and urbanization for Pakistan from 2013 to 2021 using Landsat 8. The detection of urban land suitability concerning multiple metrics such as ecological response variables, environmental tension, socio-economic development potential, and natural resource potential is also found. Dataset features were classified as bands in the Google Earth Engine. Moreover, for 2020 and 2021, classification results showing the change in water, vegetation, and urbanization are also represented concerning China Pakistan Economic Corridor (CPEC) highway and the railway track to monitor and control traffic and its management.

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New Spatial Strategy in China: Major Function Zoning of Beijing-Tianjin Metropolitan Area with Perspective from Ecological Economics

Cited by 8 publications

References 23 publications

The Characteristics and Modes of Urban Network Evolution in the Yangtze River Delta in China from 1990 to 2017

The Characteristics and Modes of Urban Network Evolution in the Yangtze River Delta in China from 1990 to 2017

Development of Economic Integration in the Central Yangtze River Megaregion from the Perspective of Urban Network Evolution

Digital and Geographical Feature Detection by Machine Learning Techniques Using Google Earth Engine for CPEC Traffic Management

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