Spatio–Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory

Fan, Yong; Guo, Ruifeng; He, Zhongshi; Li, Minmin; He, Bin; Yang, Hao; Wen, Nu

doi:10.3390/e21010020

Cited by 11 publications

(5 citation statements)

References 37 publications

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“…The gravity model is used to construct the spatial network of the urban system. Taking into account the relationship between potential and actual economic ties and the fact that there is no equivalence between the two cities, the gravity model is expressed by the GDP and population of the city [14]. Based on the social network analysis theory, the gravity model was established to analyze the characteristics of the logistics network of the Yangtze River Delta urban agglomeration [15].…”

Section: Introductionmentioning

confidence: 99%

Coordinated Development of Urban Agglomeration in Central Shanxi

Cao

Zhang

et al. 2022

Sustainability

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Central Shanxi is one of the nine urban agglomerations proposed in China’s latest national planning, which has great development potential and represents a major opportunity for Shanxi Province to rise in central China. How to determine the existing problems and promote better-coordinated development is the goal of this article. Therefore, an improved gravity model, industrial structure similarity coefficient and population–economic growth elasticity method were used to analyze and study the coordinated development of urban agglomerations in central Shanxi from the perspectives of economy, industry and population–economy. The research conclusion is that there are three problems: a low level of coordinated economic development, strong dependence on coal resources, and uncoordinated population development and economic growth. Therefore, this paper discusses and puts forward the main strategies for the government to strengthen economic planning, improve the level of economic development, optimize and upgrade the industrial structure, end dependence on coal resources and strengthen regional ties, and improve the level of population and economy coordination so that the urban agglomeration in central Shanxi becomes the growth pole and important support point of regional economic and social development.

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Section: Introductionmentioning

confidence: 99%

Coordinated Development of Urban Agglomeration in Central Shanxi

Cao

Zhang

et al. 2022

Sustainability

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“…The mean annual precipitation and temperature are approximately 883 mm and 11-16 • C, respectively [37]. The HRB is densely populated with 611 people/km 2 [38] and has experienced a high rate of population growth in recent decades. The utilization rate of land is very high; cropland accounts for the largest proportion of the total area (Figure 1b).…”

Section: Study Areamentioning

confidence: 99%

“…The HRB is an important grain, cotton, and oilseed production region in China [39], resulting in high land utilization. The industries mainly consist of coal, power, and light textile industries, The HRB is densely populated with 611 people/km 2 [38] and has experienced a high rate of population growth in recent decades. The utilization rate of land is very high; cropland accounts for the largest proportion of the total area (Figure 1b).…”

Section: Study Areamentioning

confidence: 99%

Ecological Safety Assessment and Analysis of Regional Spatiotemporal Differences Based on Earth Observation Satellite Data in Support of SDGs: The Case of the Huaihe River Basin

Sang

Wang

et al. 2021

Remote Sensing

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Terrestrial ecosystems provide a variety of benefits for human life and production, and are a key link for achieving sustainable development goals (SDGs). The basin ecosystem is one type of terrestrial ecosystem. Ecological security (ES) assessments are an important component of the overall strategy to achieve regional sustainable development. The Huaihe River Basin (HRB) has the common characteristics of most basins, such as high population density, a rapidly developing economy, and many environmental problems. This study constructed an ES evaluation system by applying a pressure-state-response framework as an assessment method for the sustainable development of basins. Taking the HRB as an example, this study determined the ES status of the region from 2001 to 2019 and analyzed crucial factors for any variation observed by combining remote sensing and climate data, relevant policies, and spatial information technology. The results highlight the importance of reserves and the negative impact of urban expansion on ES. Additionally, the enactment of policies had a positive impact on ES, whereas precipitation had a negative effect on ES in most areas of the HRB. Based on these results, the government should strengthen the protection of forests, grasslands, and wetlands and improve water conservation facilities. This study provides guidance for the subsequent economic development, environmental protection, and the achievements of SDG 15 in the HRB.

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“…Formulation of policies and measures for coordinated urban development requires study of not only the spatial pattern of passenger traffic linkages between cities but also the factors that influence the spatial pattern of passenger traffic. Traditional research has analyzed the relationship between the spatial pattern of urban connections and factors such as population size, economy, and urban administrative level [17][18][19]. As a source of objective and high-precision data, nighttime light remote sensing data has received widespread attention from scholars [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow

et al. 2019

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Investigating regional connections and their influencing factors from the perspective of "flow" space is one of the foundations of promoting regional development. In this article, the data we used includes actual highway passenger flow data, National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light remote sensing data, and socioeconomic data. We analyzed the spatial distribution pattern, connection intensity and spatial autocorrelation of highway passenger flow in Chongqing during the working day, weekend and May Day and revealed the influencing factors by means of a geographic detector. Three key conclusions resulted from this research. First, highway passenger flow in Chongqing districts exhibits spatial agglomeration that is clearly higher in western Chongqing than in eastern Chongqing and forms an obviously dual-core "star" structure, with the main urban area and Wanzhou serving as the core. Second, a factor detector notes that the nighttime light area index (0.9251, 0.9512, 0.9541) has the strongest explanatory power for the spatial differentiation of passenger traffic in Chongqing districts, which is the key factor. Third, interaction detection shows that the interaction between the two factors displays an enhancement effect at different times. The nighttime light area index shows the strongest explanatory power under the synergy of tourist attractions, which are 0.9850, 0.9903 and 0.9908. But the per capita GDP and highway mileage have the most obvious enhancement effect after interaction (0.9544, 0.9661, 0.9652). Therefore, in future planning and development, we should pay attention to cooperation and exchanges between districts and use the nighttime light area index as an important reference factor to provide a scientific basis for the construction of public transport and economic construction in Chongqing.

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Spatio–Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory

Cited by 11 publications

References 37 publications

Coordinated Development of Urban Agglomeration in Central Shanxi

Coordinated Development of Urban Agglomeration in Central Shanxi

Ecological Safety Assessment and Analysis of Regional Spatiotemporal Differences Based on Earth Observation Satellite Data in Support of SDGs: The Case of the Huaihe River Basin

Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow

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