scholarly journals Research on Urban and Rural Coordination Development and Its Driving Force Based on the Space-time Evolvement Taking Guangdong Province as an Example

Land ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 253
Author(s):  
Daizhong Tang ◽  
Baorui Li ◽  
Yuan Qiu ◽  
Linlin Zhao
Keyword(s):  
Spatial Data ◽  
Driving Forces ◽  
River Estuary ◽  
Principal Component ◽  
Guangdong Province ◽  
Pearl River Estuary ◽  
Space Time ◽  
Spatial Data Analysis ◽  
New Countryside ◽  
Coordination Development

Based on the background of the change in the urban–rural relationship in Guangdong Province, this paper constructs an analysis framework of urban and rural coordination development. Using the data of 19 administrative units above prefecture level in Guangdong Province, this paper studies the space–time evolution of urban and rural coordination development during 2000–2015 through Principal Component Analysis (PCA) and Exploratory Spatial Data Analysis (ESDA) and explores the influencing factors and driving forces behind it. It is found that there is club convergence in the urban and rural coordination development in Guangdong Province. This kind of convergence is reflected in the findings that the east bank of the Pearl River estuary is the best area for the urban and rural coordination development where Guangzhou, Dongguan, Shenzhen is the core and the level of urban and rural coordination development in the east, west and north of Guangdong Province is relatively low, which also reflects a geographical polarization feature. Based on the analysis of the factors that promote the urban and rural coordination development in the main years of 2000–2015, it can be concluded that location, economic development and urbanization level are the most important driving forces, followed by industrial structure. This research can be used as a decision-making reference for urban and rural coordination development and new countryside construction in China in the New Era.

scholarly journals Smart and IoT-Based Coupling and Coordination Development for Financial and Logistics Industries

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ji-you Li ◽  
Qi-qing Zhou ◽  
Pan-pan Yin
Keyword(s):  
Spatial Data ◽  
Driving Forces ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Spatial Data Analysis ◽  
Theil Index ◽  
Eastern Region ◽  
Coordinated Development ◽  
The Republic ◽  
Total Difference

Based on the panel data, collected through various Internet of Things (IoT) devices, of 31 various provinces and cities in the Republic of China from 2004 to 2019, due to the analysis of mechanism and the significance of coupled and coordinated development, methods like fuzzy comprehensive evaluation, entropy, coupling, and coordination degree model, exploratory spatial data analysis, and Theil index are widely used to analytically evaluate the dynamic coupling development of China’s financial and logistics industries. The analysis of the collected data shows that demand promotion, technological progress, corporate decision-making, and policy stimulus are the driving forces for the coordinated development. In addition, the coordinated development of both industries can achieve a win-win situation. Moreover, during the sample period, the level of coupled and coordinated development has made considerable progress, achieving a transition from moderate to slightly unbalanced level, but overall, it is still at a low level. The level of coupled and coordinated development is showing east-central-west, that is, a three-level declining trend. Guangdong is the province with the highest level, and Qinghai and Ningxia are the provinces with the lowest levels of coupled and coordinated development. The general evolution trend of the total difference in the levels of coupled and coordinated development is declining in fluctuation, and the differences in the eastern region and within the zones are the main reasons for the total difference.

scholarly journals The spatiality and driving forces of population ageing in China

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0243559
Author(s):  
Lianxia Wu ◽  
Zuyu Huang ◽  
Zehan Pan
Keyword(s):  
Economic Development ◽  
Spatial Data ◽  
Census Data ◽  
Local Economic Development ◽  
Driving Forces ◽  
Population Ageing ◽  
Spatial Data Analysis ◽  
Western China ◽  
Practical Significance ◽  
Driving Mechanism

Studying the spatial characteristics of China’s ageing and its influencing factors is of great practical significance because China has the largest elderly population in the world. Using 2000 and 2010 census data, this study explores the degree, pace, and pattern of population ageing and its driving mechanism using exploratory spatial data analysis and the geographically weighed regression model. Between 2000 and 2010, population ageing increased rapidly countrywide; yet, spatial differences between eastern and western China narrowed. The degree of provincial population ageing and its spatiality were determined by natural population growth, migration, and local economic development. Life expectancy and mortality were the primary long-term factors, and GDP per capita was the prime contributor in the early days of economic development; the migration rate was the dominant influence after 2010. China’s overall spatial differentiation of population ageing shifted from a north–south to an east–west division.

scholarly journals Space-Time Analysis of Migrations, Employment, and Housing as A Basis for Municipal Sustainable Urban Planning

2020 ◽  
Vol 12 (6) ◽  
pp. 2473
Author(s):  
Patricia Abelairas-Etxebarria ◽  
Inma Astorkiza
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Spatial Data ◽  
Local Level ◽  
Housing Prices ◽  
Space Time ◽  
Sustainable Land Use ◽  
Spatial Data Analysis ◽  
Spatial Homogeneity ◽  
Land Use Policies

A close relationship exists between population, the housing market and the level of employment at the local level. On the one hand, the housing market is influenced by local planning decisions and, on the other hand, that market is a significant factor in population and economic dynamization. Although there are studies on these variables, it is not common to include their spatial perspective by introducing Geographic Information System (GIS) tools in the analysis. The aim of this study is to analyse space-time associations among the variables migrations, housing prices, and employment prior to and during the economic crisis, in order to adapt sustainable land use policies to be used by land use planning authorities. Bivariate Exploratory Spatial Data Analysis (bivariate ESDA) has been used for this purpose. As our main results demonstrate, spatial positive autocorrelation was found between the variables employment in a village before the crisis and housing prices in neighbouring municipalities during it, indicating that people move to live in areas close to their workplace, but not necessarily to the same municipality. The analysis also shows spatial homogeneity of the variable housing prices, accompanied by temporal stability. The results indicate the need to implement sustainable control land use policies, not at the municipality level but at the county level.

scholarly journals Identifying the Driving Factors of Food Nitrogen Footprint in China, 2000–2018: Econometric Analysis of Provincial Spatial Panel Data by the STIRPAT Model

2021 ◽  
Vol 13 (11) ◽  
pp. 6147
Author(s):  
Chun Liu ◽  
Gui-Hua Nie
Keyword(s):  
Panel Data ◽  
Spatial Data ◽  
Driving Forces ◽  
Early Stage ◽  
Spillover Effect ◽  
Spatial Data Analysis ◽  
Ekc Hypothesis ◽  
Stirpat Model ◽  
Spatial Panel Data ◽  
Per Capita

This paper studies the EKC hypothesis and STIRPAT model. Based on the panel data of carbon emission intensity and other influencing factors of 30 provinces in China from 2000 to 2018, the spatial effect of per capita food nitrogen footprint (FNF) and the effect of different socio-economic factors in China were studied by using exploratory spatial data analysis and fixed effect spatial Durbin model for the first time. The results show that: (1) there is a spatial agglomeration effect and a positive spatial dependence relationship in China’s provincial per capita FNF (FNFP), which verifies that the relationship between China’s FNF and economy is in the early stage of EKC hypothesis curve. (2) The driving forces of China’s FNF were explored, including Engel’s coefficient of urban households (ECU), population density (PDEN), urbanization, nitrogen use efficiency (NUE) and technology. (3) The results show that there is a significant spatial spillover effect of FNFP. The ECU and NUE can reduce the regional FNFP, and can slow down the FNFP of surrounding provinces. (4) Policy makers need to formulate food nitrogen emission reduction policies from the food demand side, food consumption side and regional level.

Dynamics of photosynthetic picoplankton in a subtropical estuary and adjacent shelf waters

2009 ◽  
Vol 90 (7) ◽  
pp. 1319-1329 ◽  
Author(s):  
D. Lin ◽  
A. Zhu ◽  
Z. Xu ◽  
L. Huang ◽  
H. Fang
Keyword(s):  
Environmental Factors ◽  
River Estuary ◽  
Principal Component ◽  
Pearl River Estuary ◽  
Nutrient Concentrations ◽  
Dominant Group ◽  
Average Cell ◽  
Suspended Sediment Concentrations ◽  
The Pearl River ◽  
Photosynthetic Picoplankton

Dynamics ofSynechococcus(Syn),Prochlorococcus(Pro) and picoeukaryotes (Euk) was studied at 92 stations in the Pearl River Estuary and adjacent shelf waters in the winter of 2006 using flow cytometry. The average cell abundance of photosynthetic picoplankon (Pico) was 104cells/ml. Picoeukaryotes was the dominant group in the inner estuary whereProwas absent.Synechococcuswas dominant in the coastal and open waters. The proportion ofProwas higher in the open than in the coastal waters. The change of Pico community structure from the inner estuary to the open waters is related to the changes in hydrochemical dynamics. The vertical variations in the abundance and community composition of Pico were not significant. The abundances ofProandSynwere positively correlated with temperature, salinity and pH, whereas they were negatively correlated with dissolved oxygen (DO), suspended sediment concentrations (SSC) and nutrients (nitrogen, phosphorus and silicon) concentrations. But the correlations between %Euk (as of total pico) and these environmental factors were opposite to those between the abundance of prokaryotic cells (ProandSyn) and the environmental factors. %Euk had significant negative correlations with temperature, salinity and pH, and positive correlations with DO, SSC and nutrients. There were differences in the niches between prokaryotic cells and picoeukaryotes.ProchlorococcusandSynwere dominant in the warm waters with high salinity, low SSC and low nutrient concentrations, while %Euk was higher in the cold waters with low salinity, high SSC and high nutrient concentrations. Results of principal component analysis and regression analysis indicated that the relationship between the abundances of Pico and the environmental factors was a compound function (y = b0(b1)x), and that between the abundances ofPro,Synor %Euk and the environmental factors was a linear function.

scholarly journals Research on Trend of Nutrients and its Response to Human Activities in the Pearl River Estuary

2020 ◽  
Vol 145 ◽  
pp. 02081
Author(s):  
Yingxian Long ◽  
Qiang Sun ◽  
Kun Yang
Keyword(s):  
Human Activities ◽  
Inorganic Nitrogen ◽  
River Estuary ◽  
Principal Component ◽  
Pearl River Estuary ◽  
Pearl River ◽  
Wastewater Discharge ◽  
Industrial Output ◽  
The Pearl River Estuary ◽  
The Pearl River

This is a research on the change of nutrients and its structure in the Pearl River Estuary by the principal component analysis (PCA) according to the data and materials on water quality observation in the last 30 years around the Pearl River Estuary. Results showed that inorganic nitrogen (DIN) presented an obvious increase trend in the last 30 years, while phosphate and silicate presented an outstanding decrease trend in this area by the influence of human activities. The average N/P ratio increased by 1.44 times, the Si/N ratio decreased by 66.8%, the Si/P ratio decreased by 18.5%, and the structure of nutrients changed significantly. According to the results of PCA, the first two principal components (PC) were extracted. PC1 was associated with GDP, population, industrial output value and wastewater discharge, which explained 80.9% of the variance. PC2 was characterized by cultivated land area, which explained 14.6% of the variance. It indicates that the change of nutrients content and structure in the Pearl River Estuary was closely related to economic development and industrial pollution discharge, and the effect of the change of land use and land cover on the change of nutrients should not be ignored.

scholarly journals Study on the Level and Type Identification of Rural Development in Wuhan City’s New Urban Districts

2020 ◽  
Vol 9 (3) ◽  
pp. 172 ◽  
Author(s):  
Liang Jiang ◽  
Jing Luo ◽  
Chunyan Zhang ◽  
Lingling Tian ◽  
Qingqing Liu ◽  
...  
Keyword(s):  
Rural Development ◽  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Socioeconomic Development ◽  
Spatial Differentiation ◽  
Principal Component ◽  
Spatial Data Analysis ◽  
Balanced Development ◽  
Urban Districts

A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing countries. Taking Wuhan as the case study, this paper developed an index system including rural settlement, land, industry and human settlement environment for evaluating the level of rural development. Then, using the exploratory spatial data analysis, the principal component analysis and the cluster analysis, this paper analyzes the spatial differentiation and correlation and categorizes the types of rural development. The results are as follows. (1) The spatial differentiation of the level of rural development in Wuhan City’s new urban districts is obvious and the areas with a high level of rural development are mainly distributed at the intersection of the new and central urban areas and gradually decrease outward. (2) There is a significant spatial agglomeration of the developed rural areas and the structure of the spatial change in these areas resembles a certain continuity, specifically a circle of “central heat surrounding cold”. (3) Rural development in the new urban areas can be divided into the following five types: the ecological leisure type, the traditional farming type, the balanced development type, the industrial-and-agricultural mixed type and the industrial promotion type. The corresponding development path is proposed in combination with different types of rural development to provide a theoretical basis and decision-making reference for rural revitalization.

Description of Lecane yatseni sp. n. (Rotifera: Monogononta: Lecanidae) from China

Biologia ◽  
2010 ◽  
Vol 65 (3) ◽  
Author(s):  
Nan Wei ◽  
Runlin Xu
Keyword(s):  
River Estuary ◽  
Guangdong Province ◽  
Pearl River Estuary ◽  
Pearl River ◽  
Artificial Lake ◽  
The Pearl River Estuary ◽  
Qi’Ao Island ◽  
The Pearl River

AbstractLecane yatseni sp. n., collected from the littoral of an artificial lake on Qi’ao island of the Pearl River estuary, Guangdong province, south of China, is described and figured. It is closely related to one of the commonest species of the genus, Lecane luna, resembling Lecane papuana, but distinguished by the presence of inwardly curved aculeated anterolateral spines and broad-based spine-formed projections close to the middle of the ventral head aperture margin.

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