Spatial Pattern Evolution and Optimization of Urban System in the Yangtze River Economic Belt, China, Based on DMSP-OLS Night Light Data

Zhong, Yanfei; Lin, Aiming; Zhou, Zhigao; Chen, Feiyan

doi:10.3390/su10103782

Cited by 22 publications

(16 citation statements)

References 44 publications

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“…As a useful proxy to evaluate economic performance, different from human-produced economic indices, night-time luminosity can be objectively measured and is immune to falsification or misreporting (Chen and Nordhaus, 2011). Among indicators using night-time data, the night light index (e.g., the Night Light Development Index (NLDI) and Night Light Index (NLI) are common proxies of NTE activities (Elvidge et al, 2012; Mellander et al, 2015; Zhong et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Night-time economy vitality index: Framework and evidence

et al. 2021

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This study aims to develop a multi-dimensional night-time economy vitality index (NTEVI) to measure the vitality of night-time economic (NTE) activities in Zhejiang Province, China, covering its 11 cities and 90 counties. Comprising 44 supply and demand indicators of the NTE, the index was composed of an overall index and six major sub-indices that measured the vitality of six typical NTE subsectors, including catering, shopping, recreation, accommodation, touring, and fitness. The NTEVI was calculated using a unique multi-source dataset based on hourly online transaction data from a leading Chinese online-to-offline service platform, monthly night-time electricity consumption data, and official statistics from 2019 to 2020. Robustness and sensitivity analyses were conducted to ensure high credibility of the index results. The findings of this study suggested that the NTEVI was highly and significantly correlated with night light indices, economic indicators, and tourism demand measures. By identifying regional and temporal differences across several service sectors over time at the county, city, and provincial levels, the NTEVI serves as a powerful numerical and visual tool: it offers key information to guide policy formulation, resource allocation, and policy evaluation. In the context of COVID-19, the index analyses also reflect the NTE recovery process in Zhejiang Province. Our findings indicate that it is important for the Chinese government, regional authorities, and enterprises to encourage the NTE as a main driver of economic revitalization.

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Section: Literature Reviewmentioning

confidence: 99%

Night-time economy vitality index: Framework and evidence

et al. 2021

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“…In addition, the indicator’s standards are inconsistent. Studies sometimes use the total light intensity, sometimes use light area or light intensity density [ 33 , 34 ], or even define the light index by combining the light area and light intensity with different formulas [ 25 ]. However, there is no unified explanation or comparison for the indicators.…”

Section: Introductionmentioning

confidence: 99%

The relationship between night-time light and socioeconomic factors in China and India

et al. 2022

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This paper re-examines the relationships between night-time light (NTL) and gross domestic product (GDP), population, road networks, and carbon emissions in China and India. Two treatments are carried out to those factors and NTL, which include simple summation in each administrative region (total data), and summation normalized by region area (density data). A series of univariate regression and multiple regression experiments are conducted in different countries and at different scales, in order to find the changes in the relationship between NTL and every parameter in different situations. Several statistical metrics, such as R2, Mean Relative Error (MRE), multiple regression weight coefficient, and Pearson’s correlation coefficient are given special attention. We found that GDP, as a comprehensive indicator, is more representative of NTL when the administrative region is relatively comprehensive or highly developed. However, when these regions are unbalanced or undeveloped, the representation of GDP becomes weak and other factors can have a more important influence on the multiple regression. Differences in the relationship between NTL and GDP in China and India can also be reflected in some other factors. In many cases, regression after normalization with the administrative area has a higher R2 value than the total regression. But it is highly influenced by a few highly developed regions like Beijing in China or Chandigarh in India. After the scale of the administrative region becomes fragmented, it is necessary to adjust the model to make the regression more meaningful. The relationship between NTL and carbon emissions shows obvious difference between China and India, and among provinces and counties in China, which may be caused by the different electric power generation and transmission in China and India. From these results, we can know how the NTL is reflected by GDP and other factors in different situations, and then we can make some adjustments.

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“…It is in WTO developing country member interior also has certain difference. In addition, the profound development of regional economic integration also poses a certain challenge to the multilateral system [7]. Central America has the highest proportion of trade with its artners, followed by Africa, North America and Europe (where the European figures only include trade with external partners, which rises sharply if intra-european trade is included) [8,9].…”

Section: Introductionmentioning

confidence: 99%

International Trade Strategy Evolution and Pattern Discrimination under the Value Competition Mechanism

Dong¹,

Hao²

2021

BCPBM

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International trade theory generally assumes that trade is carried out in the ideal state of perfect competition market and constant return on scale, but the reality is not so. Every economy will formulate some policies to restrict or encourage trade for the sake of maximizing its own trade interests. With the acceleration of globalization, the industrial division of labor, trade benefits and competitiveness of an economy in the global economy are considered from the perspective of value competition mechanism, and the change and future trend of international trade policy under the value competition mechanism are analyzed starting from the introduction of the concept of value competition mechanism. Starting from the integration of the value competition mechanism, focusing on the increase of the added value of the whole industry, combining the technological progress, industry integration and the transformation of factor input. Value through the extension of competition mechanism and integration, the mainstream trade theory deals with the main factors and system variables into a unified multi-factor panel data model framework for empirical analysis, found on the evolution of international trade strategy and pattern identify differences, including system quality and the cost difference split effectively the technological progress, economic benefit and sustainable development and full employment, to maximize the added value of the whole value competition mechanism, and finally realize the improvement of industry international competitiveness.

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Spatial Pattern Evolution and Optimization of Urban System in the Yangtze River Economic Belt, China, Based on DMSP-OLS Night Light Data

Cited by 22 publications

References 44 publications

Night-time economy vitality index: Framework and evidence

Night-time economy vitality index: Framework and evidence

The relationship between night-time light and socioeconomic factors in China and India

International Trade Strategy Evolution and Pattern Discrimination under the Value Competition Mechanism

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