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 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 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 How Do Spatial Patterns Impact Regulation of Water-Related Ecosystem Services? Insights from a New Town Development in the Yangtze River Delta, China

2019 ◽  
Vol 11 (7) ◽  
pp. 2010 ◽  
Author(s):  
Jieqiong Wang ◽  
Siqing Chen ◽  
Min Wang
Keyword(s):  
Ecosystem Services ◽  
Spatial Patterns ◽  
Ecosystem Service ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
New Town ◽  
Ecological Resources ◽  
The Yangtze River Delta

Scientists have made efforts to improve the efficiency and effectiveness of ecosystem service valuation and mapping; yet little actual implementation of new ecosystem service knowledge has been delivered in practice. We explored this gap by developing a spatially explicit and semi-qualitative evaluation approach to clarify how the spatial patterns of new town developments impact three types of water-related regulating ecosystem services, namely water flow regulation, flooding mitigation, and water quality regulation. Based on peer-reviewed publications, we identified key indicators with spatial characteristics that practitioners care about and have control of. We investigated the case of Lingang, a satellite city of Shanghai in the Yangtze River Delta, and found that (1) 85.30% of the pre-urban East Lingang with native marshlands performed better holistically while 93.06% of the post-urban East Lingang using the man-made lakeside model performed poorly; (2) 82.47% of the double grids model at West Lingang performed poorly in pre-urban time, while some major waterways were improved by the Hydrological Planning; and (3) a major weakness in the planning process was the ignorance in conserving pre-urban ecological resources, preventing the provision of ecosystem services. Finally, four urban design principles of both large-scale land use considerations and finer-scale design implications were proposed.

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.

Sign in / Sign up

Export Citation Format

Share Document