Does urban agglomeration affect innovation convergence: evidence from China

2021 ◽  
pp. 1-16
Author(s):  
Jie Tang ◽  
Wenyue Cui
Keyword(s):  
Urban Agglomeration

Urban Agglomeration and CEO Pay

2008 ◽  
Author(s):  
Bill B. Francis ◽  
Kose John ◽  
Iftekhar Hasan ◽  
Maya Waisman
Keyword(s):  
Urban Agglomeration ◽  
Ceo Pay

scholarly journals The Spatio-Temporal Analysis of Urban-Rural Coordinated Development and Its Driving Forces in Yangtze River Delta

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 495
Author(s):  
Daizhong Tang ◽  
Mengyuan Mao ◽  
Jiangang Shi ◽  
Wenwen Hua
Keyword(s):  
Influencing Factors ◽  
Yangtze River ◽  
Driving Forces ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
System Level ◽  
Actual State ◽  
Coordinated Development ◽  
Urban Rural

This paper conducts an analytical study on the urban-rural coordinated development (URCD) in the Yangtze River Delta urban agglomeration (YRDUA), and uses data from 2000–2015 of 27 central cities to study the spatial and temporal evolution patterns of URCD and to discover the influencing factors and driving forces behind it through PCA, ESDA and spatial regression models. It reveals that URCD of the YRDUA shows an obvious club convergence phenomenon during the research duration. The regions with high-level URCD gather mainly in the central part of the urban agglomeration, while the remaining regions mostly have low-level URCD, reflecting the regional aggregation phenomenon of spatial divergence. At the same time, we split URCD into efficiency and equity: urban-rural efficient development (URED) also exhibits similar spatiotemporal evolution patterns, but the patterns of urban-rural balanced development (URBD) show some variability. Finally, by analyzing the driving forces in major years during 2000–2015, it can be concluded that: (i) In recent years, influencing factors such as government financial input and consumption no longer play the main driving role. (ii) Influencing factors such as industrialization degree, fixed asset investment and foreign investment even limit URCD in some years. The above results also show that the government should redesign at the system level to give full play to the contributing factors depending on the actual state of development in different regions and promote the coordinated development of urban and rural areas. The results of this study show that the idea of measuring URCD from two dimensions of efficiency and equity is practical and feasible, and the spatial econometric model can reveal the spatial distribution heterogeneity and time evolution characteristics of regional development, which can provide useful insights for urban-rural integration development of other countries and regions.

scholarly journals The Gradient Effect on the Relationship between the Underlying Factor and Land Surface Temperature in Large Urbanized Region

Land ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Yixu Wang ◽  
Mingxue Xu ◽  
Jun Li ◽  
Nan Jiang ◽  
Dongchuan Wang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landscape Planning ◽  
Potential Gradient ◽  
Surface Characteristics ◽  
Ordinary Least Squares ◽  
Urban Agglomeration ◽  
Spatial Gradient ◽  
Gradient Effect

Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

scholarly journals Planning of a Cargo Control Post within an Urban Agglomeration

2021 ◽  
Vol 666 (5) ◽  
pp. 052078
Author(s):  
A Shevtsova ◽  
A N Novikov ◽  
A V Stetsenko ◽  
V V Panyushktn
Keyword(s):  
Urban Agglomeration ◽  
Control Post

scholarly journals Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review

2020 ◽  
Vol 13 (1) ◽  
pp. 285
Author(s):  
Huanhuan Hua ◽  
Amare Wondirad
Keyword(s):  
Sustainable Development ◽  
Urban Tourism ◽  
Urban Agglomeration ◽  
Future Research ◽  
Tourism Destination ◽  
Research Fields ◽  
Research Themes ◽  
Research Architecture ◽  
Critical Literature

This study analyzes tourism network in urban agglomerated destinations and puts forth implications for future sustainable development through a critical and extensive review of related literature. First of all, with a bibliometric analysis of 2670 selected articles from three research fields of urban tourism, urban agglomeration tourism and tourism destination network, we analyzed their respective research themes and classified them accordingly. Then, the study further investigates the role of tourism network in urban agglomerated destinations by identifying the differences and connections between urban agglomeration tourism and urban tourism. Finally, a basic architecture is established for the study of tourism networks in urban agglomerated destinations context. Study findings highlight that urban agglomeration tourism emphasizes the interconnectivity and social network relationships. However, research on the destination network of urban agglomerations is limited, especially from the tourism development perspectives. Therefore, the evolution process, structural effects, determinants and dynamic mechanisms of the tourism network in urban agglomerated destination are among the opportunities for future research. Moreover, the research architecture shows that the network relationship emerges as a new direction for the study of urban agglomeration system to better integrate and harness destinations’ resources and thereby promote sustainable development in urban agglomerated areas.

scholarly journals Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

2021 ◽  
Vol 18 (5) ◽  
pp. 2222
Author(s):  
Jin-Wei Yan ◽  
Fei Tao ◽  
Shuai-Qian Zhang ◽  
Shuang Lin ◽  
Tong Zhou
Keyword(s):  
Geographically Weighted Regression ◽  
Yangtze River ◽  
National Level ◽  
National Development ◽  
Urban Agglomeration ◽  
Spatiotemporal Distribution ◽  
Weighted Regression ◽  
Series Data ◽  
The Yangtze River ◽  
Urban Agglomerations

As part of one of the five major national development strategies, the Yangtze River Economic Belt (YREB), including the three national-level urban agglomerations (the Cheng-Yu urban agglomeration (CY-UA), the Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and the Yangtze River Delta urban agglomeration (YRD-UA)), plays an important role in China’s urban development and economic construction. However, the rapid economic growth of the past decades has caused frequent regional air pollution incidents, as indicated by high levels of fine particulate matter (PM2.5). Therefore, a driving force factor analysis based on the PM2.5 of the whole area would provide more information. This paper focuses on the three urban agglomerations in the YREB and uses exploratory data analysis and geostatistics methods to describe the spatiotemporal distribution patterns of air quality based on long-term PM2.5 series data from 2015 to 2018. First, the main driving factor of the spatial stratified heterogeneity of PM2.5 was determined through the Geodetector model, and then the influence mechanism of the factors with strong explanatory power was extrapolated using the Multiscale Geographically Weighted Regression (MGWR) models. The results showed that the number of enterprises, social public vehicles, total precipitation, wind speed, and green coverage in the built-up area had the most significant impacts on the distribution of PM2.5. The regression by MGWR was found to be more efficient than that by traditional Geographically Weighted Regression (GWR), further showing that the main factors varied significantly among the three urban agglomerations in affecting the special and temporal features.

scholarly journals Source Apportionment and Health Risk Assessment of Metal Elements in PM2.5 in Central Liaoning’s Urban Agglomeration

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 667
Author(s):  
Qingyuan Guo ◽  
Liming Li ◽  
Xueyan Zhao ◽  
Baohui Yin ◽  
Yingying Liu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Health Risk Assessment ◽  
Coal Combustion ◽  
Urban Agglomeration ◽  
Liaoning Province ◽  
Soil Dust ◽  
Traffic Emission ◽  
Metal Elements ◽  
Adults And Children

To better understand the source and health risk of metal elements in PM2.5, a field study was conducted from May to December 2018 in the central region of the Liaoning province, China, including the cities of Shenyang, Anshan, Fushun, Benxi, Yingkou, Liaoyang, and Tieling. 24 metal elements (Na, K, V, Cr, Mn, Co, Ni, Cu, Zn, As, Mo, Cd, Sn, Sb, Pb, Bi, Al, Sr, Mg, Ti, Ca, Fe, Ba, and Si) in PM2.5 were measured by ICP-MS and ICP-OES. They presented obvious seasonal variations, with the highest levels in winter and lowest in summer for all seven cities. The sum of 24 elements were ranged from to in these cities. The element mass concentration ratio was the highest in Yingkou in the spring (26.15%), and the lowest in Tieling in winter (3.63%). The highest values of elements in PM2.5 were mostly found in Anshan and Fushun among the studied cities. Positive matrix factorization (PMF) modelling revealed that coal combustion, industry, traffic emission, soil dust, biomass burning, and road dust were the main sources of measured elements in all cities except for Yingkou. In Yingkou, the primary sources were identified as coal combustion, metal smelting, traffic emission, soil dust, and sea salt. Health risk assessment suggested that Mn had non-carcinogenic risks for both adults and children. As for Cr, As, and Cd, there was carcinogenic risks for adults and children in most cities. This study provides a clearer understanding of the regional pollution status of industrial urban agglomeration.

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