scholarly journals The Asymmetric Pattern of Population Mobility during the Spring Festival in the Yangtze River Delta Based on Complex Network Analysis: An Empirical Analysis of “Tencent Migration” Big Data

2021 ◽  
Vol 10 (9) ◽  
pp. 582
Author(s):  
Jinping Lin ◽  
Kangmin Wu ◽  
Shan Yang ◽  
Qianqian Liu
Keyword(s):  
Big Data ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
The Yangtze River ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Spatial Asymmetry ◽  
Spring Festival ◽  
Asymmetric Pattern ◽  
The Yangtze River Delta

Population mobility patterns are an important reflection of the future distribution of migrant populations and the evolution trends of urbanization patterns. However, although research based on statistical data can reveal the pattern of population flow, it also shows a time lag. Most of the population flow network research based on location services data has failed to fully discuss the symmetry of directional outflows and inflows in the same place and the two-way symmetrical connections between places. This paper creatively proposes and constructs the concept and analysis framework of population flow asymmetry. We used the Yangtze River Delta (YRD) as a typical case and the results of our analysis reveal the temporal and spatial asymmetry of the population flow using complex network analysis methods based on the Spring Festival (SF) population migration big data. We found that the timing asymmetry manifested in such a way that the closer it was to the festival, the greater the scale and intensity of the population movement. This is a feature of the lack of scale and regional differences within China. The spatial asymmetry was manifested in three aspects, network, node, and link, and the core cities with administrative and economic hierarchical advantages dominated the asymmetric pattern of regional population mobility. In addition, distance and administrative boundaries are factors that cannot be ignored in population movements, and they were implicated in the degree of asymmetry by distance enhancement and administrative boundary blocking. The conclusions of this study can not only provide policy decision-making guidelines for population management and resource allocation in the YRD, but they can also provide a reference value for achieving the goal of regional, high-quality, integrated development. Future research will further the discussion and management of socio-economic attributes in order to develop a more detailed and microscopic understanding of the mechanisms of population mobility patterns.

scholarly journals Research on Network Patterns and Influencing Factors of Population Flow and Migration in the Yangtze River Delta Urban Agglomeration, China

2020 ◽  
Vol 12 (17) ◽  
pp. 6803
Author(s):  
Xuewei Wang ◽  
Shuangli Ding ◽  
Weidong Cao ◽  
Dalong Fan ◽  
Bin Tang
Keyword(s):  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Spring Festival ◽  
And Migration ◽  
Network Patterns ◽  
Daily Period ◽  
The Yangtze River Delta

Through the construction of a population flow and migration relationship matrix, this paper analyzes population flow and migration in the Yangtze River Delta urban agglomeration during the Spring Festival travel rush and daily period. This paper also studies the urban network spatial structure characteristics and the influencing factors from the perspective of inter-provincial population flow and migration. The results show the following: (1) as a central city, Shanghai has a significant siphon effect, with Suzhou, Nanjing, Hangzhou, Ningbo, Wuxi and Changzhou accumulating 86.95% of the incoming population. The Shanghai–Jiangsu cross-border floating population is active and accounts for 40.83% of the total mobility scale in the same period. The population flow and migration network in the Yangtze River Delta urban agglomeration shows obvious hierarchical characteristics. The secondary network relationship during the Spring Festival travel rush is the main migration path, while the first-level network relationship in the daily period is the main flow path. (2) Three indicators, namely, the network density, mean centrality, and control force based on the population flow and migration, consistently show that the Yangtze River Delta urban agglomeration network presents a strong connection state with the formation of a local cluster structure, highlighting that the city tightness in terms of population flow and migration also has dual attributes, which refers to “the restriction of the geographic space effect” and “overcoming the friction of space”. (3) Economic scale, political resources, industrial structure, and the historical basis are important factors influencing the formation of population flows and migration networks. Employment opportunities and labor wages are key guiding factors of the population migration direction, and spatial distance is a conditional factor influencing the formation of population flows and migration networks. The inter-provincial boundary, temporal distance, and transboundary frequency are the decisive factors for the formation of network patterns of population flow and migration.

scholarly journals Ambient PM2.5 Estimates and Variations during COVID-19 Pandemic in the Yangtze River Delta Using Machine Learning and Big Data

2021 ◽  
Vol 13 (8) ◽  
pp. 1423
Author(s):  
Debin Lu ◽  
Wanliu Mao ◽  
Lilin Zheng ◽  
Wu Xiao ◽  
Liang Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Pollution ◽  
Big Data ◽  
Yangtze River ◽  
Regression Models ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yrd ◽  
The Yangtze River Delta

The lockdown of cities in the Yangtze River Delta (YRD) during COVID-19 has provided many natural and typical test sites for estimating the potential of air pollution control and reduction. To evaluate the reduction of PM2.5 concentration in the YRD region by the epidemic lockdown policy, this study employs big data, including PM2.5 observations and 29 independent variables regarding Aerosol Optical Depth (AOD), climate, terrain, population, road density, and Gaode map Point of interesting (POI) data, to build regression models and retrieve spatially continuous distributions of PM2.5 during COVID-19. Simulation accuracy of multiple machine learning regression models, i.e., random forest (RF), support vector regression (SVR), and artificial neural network (ANN) were compared. The results showed that the RF model outperformed the SVR and ANN models in the inversion of PM2.5 in the YRD region, with the model-fitting and cross-validation coefficients of determination R2 reached 0.917 and 0.691, mean absolute error (MAE) values were 1.026 μg m−3 and 2.353 μg m−3, and root mean square error (RMSE) values were 1.413 μg m−3, and 3.144 μg m−3, respectively. PM2.5 concentrations during COVID-19 in 2020 have decreased by 3.61 μg m−3 compared to that during the same period of 2019 in the YRD region. The results of this study provide a cost-effective method of air pollution exposure assessment and help provide insight into the atmospheric changes under strong government controlling strategies.

scholarly journals The Evolution of Industrial Agglomerations and Specialization in the Yangtze River Delta from 1990–2018: An Analysis Based on Firm-Level Big Data

2019 ◽  
Vol 11 (20) ◽  
pp. 5811 ◽  
Author(s):  
Shuju Hu ◽  
Wei Song ◽  
Chenggu Li ◽  
Charlie H. Zhang
Keyword(s):  
Big Data ◽  
Spatial Patterns ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Industrial Agglomeration ◽  
The Yangtze River ◽  
Firm Level ◽  
Spatial Agglomeration ◽  
The Yangtze River Delta

Although industrial agglomeration and specialization have been studied for more than 100 years, it is still a controversial field. In the era of big data, it is of great significance to study industrial agglomeration and regional specialization by using firm-level data. Based on 3,053,024 pieces of firm-level big data, the spatial evolution and spatial patterns of industrial agglomeration and specialization of 9 major industries in the Yangtze River Delta, China were revealed. Results show that: (1) the degree of industrial agglomeration is highly related to industrial attributes; industries which are directly related to production tend to be geographically concentrated, while industries that serve for production tend to be spatially dispersed; (2) the evolution characteristics and trajectories of industrial agglomeration vary by industries: wholesale and retail trade and real estate are becoming more spatially dispersed; information industries, leasing and commercial services, scientific research and polytechnic services, as well as finance are experiencing continuous spatial agglomeration; construction and manufacturing show a tendency of transfer from spatial agglomeration to spatial dispersion; (3) since 1990, most industries in the Yangtze River Delta have formed distinct spatial patterns of industrial specialization. Most core cities have experienced obvious deindustrialization processes; and high-end industries are clustering to the three biggest core cities of Shanghai, Nanjing, and Hangzhou.

scholarly journals Urban Spatial Interaction Analysis Using Inter-City Transport Big Data: A Case Study of the Yangtze River Delta Urban Agglomeration of China

2018 ◽  
Vol 10 (12) ◽  
pp. 4459 ◽  
Author(s):  
Ji Han ◽  
Jiabin Liu
Keyword(s):  
Big Data ◽  
Yangtze River ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
The Yangtze River Delta

A better understanding of the urban spatial interaction is important for optimizing the spatial structure and layout of urban agglomeration (UA). We develop a crawler program to compile online big data for urban spatial interaction analysis. Differing from the previous studies, vectorial, realistic, and high spatiotemporal resolution inter-city, bus-passenger-flow big data instead of statistical and modeled data are used for urban spatial interaction analysis. The Yangtze River Delta (YRD) is selected as a case study region to test the big data approach and to gain insights into the cities’ interaction in China’s largest UA. The results testified the superiorities of the big-data method over the traditional gravity model, confirmed some phenomena discussed or mentioned in the literature and regional plans regarding the urban interaction in YRD, derived policy implications for enhancing the sustainability of UA, and suggested some potentials for improving the limitations of the big-data method.

scholarly journals Current Status and Temporal Trend of Potentially Toxic Elements Pollution in Agricultural Soil in the Yangtze River Delta Region: A Meta-Analysis

2021 ◽  
Vol 18 (3) ◽  
pp. 1033
Author(s):  
Shufeng She ◽  
Bifeng Hu ◽  
Xianglin Zhang ◽  
Shuai Shao ◽  
Yefeng Jiang ◽  
...  
Keyword(s):  
Yangtze River ◽  
Agricultural Soil ◽  
Toxic Elements ◽  
Temporal Trend ◽  
Meta Analysis ◽  
Yangtze River Delta ◽  
Potentially Toxic Elements ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

Potentially toxic elements (PTEs) pollution in the agricultural soil of China, especially in developed regions such as the Yangtze River Delta (YRD) in eastern China, has received increasing attention. However, there are few studies on the long-term assessment of soil pollution by PTEs over large regions. Therefore, in this study, a meta-analysis was conducted to evaluate the current state and temporal trend of PTEs pollution in the agricultural land of the Yangtze River Delta. Based on a review of 118 studies published between 1993 and 2020, the average concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni were found to be 0.25 mg kg−1, 0.14 mg kg−1, 8.14 mg kg−1, 32.32 mg kg−1, 68.84 mg kg−1, 32.58 mg kg−1, 92.35 mg kg−1, and 29.30 mg kg−1, respectively. Among these elements, only Cd and Hg showed significant accumulation compared with their background values. The eastern Yangtze River Delta showed a relatively high ecological risk due to intensive industrial activities. The contents of Cd, Pb, and Zn in soil showed an increasing trend from 1993 to 2000 and then showed a decreasing trend. The results obtained from this study will provide guidance for the prevention and control of soil pollution in the Yangtze River Delta.

scholarly journals The Evolution of the Interactive Relationship between Urbanization and Land-Use Transition: A Case Study of the Yangtze River Delta

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 804
Author(s):  
Bo Niu ◽  
Dazhuan Ge ◽  
Rui Yan ◽  
Yingyi Ma ◽  
Dongqi Sun ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Socioeconomic Factor ◽  
The Yangtze River ◽  
Land Use Transition ◽  
The Yangtze River Delta ◽  
Interaction Relationship

In recent years, the impact of land-use systems on global climate change has become increasingly significant, and land-use change has become a hot issue of concern to academics, both within China and abroad. Urbanization, as an important socioeconomic factor, plays a vital role in promoting land-use transition, which also shows a significant spatial dependence on urbanization. This paper constructs a theoretical framework for the interaction relationship between urbanization and land-use transition, taking the Yangtze River Delta as an example, and measures the level of urbanization from the perspective of population urbanization, economic urbanization and social urbanization, while also evaluating the level of land-use morphologies from the perspective of dominant and recessive morphologies of land-use. We construct a PVAR model and coupled coordination model based on the calculated indexes for empirical analysis. The results show that the relationship between urbanization and land-use transition is not a simple linear relationship, but tends to be complex with the process of urbanization, and reasonable urbanization and land-use morphologies will promote further benign coupling in the system. By analyzing the interaction relationship between urbanization and land-use transition, this study enriches the study of land-use change and provides new pathways for thinking about how to promote high-quality urbanization.

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