scholarly journals Spatiotemporal Evolution Patterns and Driving Factors of Synergistic Development of Culture, Sports, and Tourism Industries: The Case Study of China

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ji Li ◽  
Jiangtao Xia ◽  
Yifan Zuo ◽  
Jiabao Cui ◽  
Qihang Qiu ◽  
...  
Keyword(s):  
Spatial Autocorrelation ◽  
Driving Factors ◽  
Western China ◽  
Eastern Region ◽  
Industrial Evolution ◽  
Factors Affecting ◽  
Coordination Model ◽  
Driving Mechanisms ◽  
Pulling Force ◽  
Global And Local

Synergistic development of the culture, sports, and tourism industries is an emerging trend in China, providing new formats for industrial evolution and fresh momentum for industrial upgrading. Therefore, building a robust framework to evaluate the synergistic development is relevant to China’s economic and social development. This study used a coupling coordination model to calculate the coupling coordination degree of the three industries, for 31 provinces in China from 2013 to 2017. Subsequently, it employed spatial autocorrelation techniques and GeoDetector to identify factors affecting the synergistic development from global and local perspectives before discussing the driving mechanisms. The results showed that (1) the synergistic development of the three industries was generally stable with a slight imbalance. (2) The development level varied across regions. The general spatial pattern was low in northeastern and western China, stable and average in the central region, and high in the eastern region. (3) The synergistic development has a prominent “proximity dependence” effect reflected by a notable spatial agglomeration feature and positive spatial autocorrelation trend and (4) twenty-one indicators of six driving factors (industrial pulling force, population supporting force, consumer purchasing power, transportation pushing force, resource attraction force, and economic driving force) affected the synergistic development.

scholarly journals Unbalanced Development Characteristics and Driving Mechanisms of Regional Urban Spatial form: A Case Study of Jiangsu Province, China

2021 ◽  
Vol 13 (6) ◽  
pp. 3121
Author(s):  
Guoping Xiong ◽  
Xin Cao ◽  
Nicholas A. S. Hamm ◽  
Tao Lin ◽  
Guoqin Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Regional Development ◽  
Driving Factors ◽  
Spatial Expansion ◽  
Spatial Form ◽  
Coordinated Development ◽  
Urbanization Level ◽  
Driving Mechanisms ◽  
Urbanization Development ◽  
Southern Jiangsu

Unbalanced regional development is widespread, and the imbalance of regional development in developing countries with rapid urbanization is increasingly apparent. This threatens the sustainable development of the region. Promoting the coordinated development of the region has become a hot spot of scientific research and a major practical need. Taking 99 counties of Jiangsu Province China, a typical coastal plain region, as the basic research unit, this paper explores the unbalanced development characteristics of the regional urban spatial form using three indicators: urban spatial expansion size, development intensity, and distribution aggregation degree. Then, their driving mechanisms were evaluated using spatial autocorrelation analysis, Pearson correlation analysis, linear regression, and geographically weighted regression. Our results found that the areas with larger urban spatial expansion size and development intensity were mainly concentrated in southern Jiangsu, where there was a positive spatial correlation between them. We found no agglomeration phenomenon in urban spatial distribution aggregation degree. From the perspective of driving factors: economics was the main driving factor of urban spatial expansion size; urbanization level and urbanization quality were the main driving factors of urban spatial development intensity. Natural landform and urbanization level are the main driving factors of urban spatial distribution aggregation degree. Finally, we discussed the optimization strategy of regional coordinated development. The quality of urbanization development and regional integration should be promoted in Southern Jiangsu. The level of urbanization development should be improved relying on rapid transportation to develop along the axis in central Jiangsu. The economic size should be increased, focusing on the expansion of the urban agglomeration in northern Jiangsu. This study will enrich the perspective of research on the characteristics and mechanisms of regional urban spatial imbalance, and helps to optimize and regulate the imbalance of regional urban development from multiple perspectives.

scholarly journals Mapping and Evaluating Human Pressure Changes in the Qilian Mountains

2021 ◽  
Vol 13 (12) ◽  
pp. 2400
Author(s):  
Quntao Duan ◽  
Lihui Luo ◽  
Wenzhi Zhao ◽  
Yanli Zhuang ◽  
Fang Liu
Keyword(s):  
Human Activities ◽  
Qilian Mountains ◽  
Western China ◽  
Eastern Region ◽  
Human Pressure ◽  
Activity Intensity ◽  
Human Footprint ◽  
Illegal Activities ◽  
The Qilian Mountains ◽  
The Impact

Human activities have dramatically changed ecosystems. As an irreplaceable ecological barrier in western China, the Qilian Mountains (QLM) provide various ecosystem services for humans. To evaluate the changes in the intensity of human activities in the QLM and their impact on the ecosystem, the human footprint (HF) method was used to conduct a spatial dataset of human activity intensity. In our study, the NDVI was used to characterize the growth of vegetation, and six categories of human pressures were employed to create the HF map in the QLM for 2000–2015 at a 1-km scale. The results showed that the mean NDVI during the growing season showed a significant increasing trend over the entire QLM in the period 2000–2015, while the NDVI showed a significant declining trend of more than 70% concentrated in Qinghai. Human pressure throughout the QLM occurred at a low level during 2000–2015, being greater in the eastern region than the western region, while the Qinghai area had greater human pressure than the Gansu area. Due to the improvement in traffic facilities, tourism, overgrazing, and other illegal activities, grasslands, shrublands, forests, wetlands, and bare land were the vegetation types most affected by human activities (in decreasing order). As the core area of the QLM, the Qilian Mountains National Nature Reserve (NR) has effectively reduced the impact of human activities. However, due to the existence of many ecological historical debts caused by unreasonable management in the past, the national park established in 2017 is facing great challenges to achieve its goals. These data and results will provide reference and guidance for future protection and restoration of the QLM ecosystem.

scholarly journals Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1056
Author(s):  
Yu Chen ◽  
Mengke Zhu ◽  
Qian Zhou ◽  
Yurong Qiao
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spatial Data ◽  
Central Area ◽  
Urban System ◽  
Entropy Method ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Eastern Region ◽  
Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

Driving factors affecting investment risk in international infrastructure construction focusing on Southeastern Asia

2019 ◽  
pp. 626-633
Author(s):  
Ting Yuan ◽  
Pengcheng Xiang ◽  
Qianman Zhang ◽  
Zhaoying Ye ◽  
Jianbin Zhang
Keyword(s):  
Driving Factors ◽  
Investment Risk ◽  
Factors Affecting

scholarly journals Spatial-Temporal Divergence and Driving Mechanisms of Urban-Rural Sustainable Development: An Empirical Study Based on Provincial Panel Data in China

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1027
Author(s):  
Chao Wei ◽  
Zuo Zhang ◽  
Sheng Ye ◽  
Mengxi Hong ◽  
Wenwen Wang
Keyword(s):  
Sustainable Development ◽  
Driving Factors ◽  
Practical Significance ◽  
Chinese Society ◽  
Strong Positive Correlation ◽  
Driving Mechanisms ◽  
Rural Revitalization ◽  
Urban Rural ◽  
Coordination Degree ◽  
New Urbanization

China’s long-standing urban-rural dichotomy has led to a widening gap between urban and rural areas, posing a huge challenge to the sustainable development of Chinese society. This paper adopted the subjective-objective weighting method, coupled coordination degree model, and geographically weighted regression model to conduct urban-rural sustainable development research on 31 provincial administrative regions in China and discussed their spatial-temporal divergence and driving mechanisms during 2007–2018. The results showed that (1) the quality of both rural revitalization and new urbanization improved during the study period, and the gap between them showed a trend of increasing after fluctuations. Both of them had significant spatial and temporal divergence characteristics. (2) The urban-rural coupling coordination degree in China continued to increase during the study period and showed an overall pattern of “high in the east-west and low in the north and southwest”. The changes of relative development type indicated that new urbanization had far surpassed rural revitalization during the study period. (3) The coefficients of driving factors varied significantly in space, showing a hierarchical band distribution. Seven of the eight driving factors showed a strong positive correlation in the vast majority of regions. The results and suggestions of this research can further promote the organic combination of rural revitalization and new urbanization strategy, which is of great practical significance for narrowing the urban-rural gap and realizing sustainable urban-rural development. Likewise, it can be a reference for other developing countries around the world.

scholarly journals Spatiotemporal Differentiation of the School-Age Migrant Population in Liaoning Province, China, and Its Driving Factors

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1036
Author(s):  
Wenwen Xu ◽  
Chunrui Song ◽  
Dongqi Sun ◽  
Baochu Yu
Keyword(s):  
Spatial Autocorrelation ◽  
Hot Spot ◽  
Driving Factors ◽  
Liaoning Province ◽  
Teaching Staff ◽  
School Age ◽  
Migrant Population ◽  
Spot Area ◽  
Quality Of Teaching

This study analyzed the spatiotemporal distribution and driving factors of the floating school-age population in Liaoning Province, China from 2008 to 2020 using county-level statistical education data combined with spatial autocorrelation and the multiscale geographically weighted regression model. The major findings are as follows. From 2008 to 2020, the distribution of the school-age migrant population exhibited obvious spatial imbalance characteristics both in terms of the number and proportion of school-age migrants. Specifically, the school-age migrant population was concentrated in the municipal districts of large and medium-sized cities and continued to increase over time in the suburbs of large and medium-sized cities. Over the past 12 years, the distribution of the school-age migrant population in Liaoning Province exhibited significant spatial autocorrelation. From the number of school-age migrants, the cold and hot spot area expanded. Conversely, from the proportion of school-age migrants, the cold and hot spot area decreased gradually, whereas the cold spot area became more diffuse. Regarding the driving factors, the quantity and quality of teaching staff, the quality of teaching equipment and conditions, and the quality of the education environment played a role in promoting or restraining the differentiation of the school-age migrant population in Liaoning Province. Moreover, the degree of influence of the driving factors exhibited substantial spatial differences.

Sustainability Factors Affecting the Implementation of Design for Dis-assembly and Re-manufacturing Principles in Automobile Sector Using ISM

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Life Span ◽  
Driving Factors ◽  
Structural Modelling ◽  
Factors Affecting ◽  
Interpretive Structural Modelling ◽  
Modelling Analysis ◽  
The World ◽  
Useful Life ◽  
To Come ◽  
Law Making

With the automobile sector pacing the tracks among their competitors to lead the market and adopting eco-friendly technologies, a much economic and vital field of making use of the manufactured product beyond its useful life span is widely neglected. This paper throws light on the necessity for implementing and highlights the various reasons for which these guidelines have not come to the attention of the responsible organizations including law making agencies, automobile manufacturers and as well the consumers. An interpretive structural modelling analysis is made to point out ten driving factors in consultation with various experts from the relevant fields and the results provide guidance to how far the idea of design for dis-assembly and re-manufacturing has sought the world for the sustainability of the automobile manufacturers in the industry, for the days to come.

Incorporating spatial autocorrelation and settlement type segregation to improve the performance of an urban growth model

2019 ◽  
Vol 47 (7) ◽  
pp. 1184-1200 ◽  
Author(s):  
Chao Xu ◽  
Didit O Pribadi ◽  
Dagmar Haase ◽  
Stephan Pauleit
Keyword(s):  
Logistic Regression ◽  
Markov Chain ◽  
Spatial Autocorrelation ◽  
Urban Growth ◽  
Driving Factors ◽  
Autologistic Regression ◽  
Cellular Automata Model ◽  
Urban Growth Model ◽  
Ordinary Logistic Regression ◽  
Settlement Growth

As rapid urbanization and population growth have become global issues, urban growth modeling has become an essential tool for decision-makers to understand how urban growth works in overall dense environments and to assess the sustainability of current urban forms. However, in urban growth models (particularly when incorporating quantitative approaches to include driving factors of urban growth), spatial autocorrelation may influence the overall model performance. In this paper, an empirical study was conducted in the region of Munich, and an integrated urban growth model was tested to explain current urban growth. The modeling contributes to advances in the state of the art by combining a range of driving factors using autologistic regression with a transition probability matrix from the Markov chain method in a cellular automata model simulation. The autologistic regression employed here addresses the impact of spatial autocorrelation compared to ordinary logistic regression. Furthermore, this study compared modeling of overall settlement growth with modeling high- and low-density settlement types separately. Incorporating spatial dependency into the model through application of autologistic regression showed improvements when compared to the ordinary logistic regression model. The Kappa indexes were higher when separately modeling the two types of settlement density compared to modeling overall settlement growth since the driving factors of settlement growth of different densities might be different. From an urban planning perspective, this novel autologistic regression-Markov chain-based cellular automata model is a powerful tool that offers an opportunity for planners and government authorities to gain a more precise understanding of the different urban growth processes that might occur in an urban region similar to the one tested here. It should allow for a better assessment of the potential costs, benefits, and risks of corresponding planning strategies.

scholarly journals Rural Households’ Poverty and Relocation and Settlement: Evidence from Western China

2019 ◽  
Vol 16 (14) ◽  
pp. 2609 ◽  
Author(s):  
Wei Liu ◽  
Jie Xu ◽  
Jie Li ◽  
Shuzhuo Li
Keyword(s):  
Logistic Model ◽  
Rural Households ◽  
Western China ◽  
Multinomial Logistic Model ◽  
Factors Affecting ◽  
Chronic Poverty ◽  
Southern Shaanxi ◽  
Transient Poverty

Based on survey data collected from five counties across southern Shaanxi, China, the present study employs a multinomial logistic model to explore the main factors related to the type of poverty of rural households, particularly focusing on the role of relocation time, reason for relocation, and type of relocation. The results showed that three types of poverty, “voluntary poverty”, “transient poverty”, and “chronic poverty”, are distinguished by combining income and consumption criteria. Moreover, relocation and settlement programs contribute to a certain degree to these three kinds of poverty, and the effects vary according to the relocation characteristics. Specifically, those relocated long-term were more likely to be trapped in “voluntary poverty” and “chronic poverty”, whereas those relocated short-term were less likely to fall into “voluntary poverty” and “transient poverty”. The poverty alleviation and disaster-related resettlers were less likely to be trapped in “chronic poverty”, whereas centralized resettlers were less likely to be trapped in “voluntary poverty” and “chronic poverty”. Additionally, demographic characteristics, capital endowment variables, and geographical features are all important factors affecting rural households’ type of poverty. This study can serve as a reference for further resettlement practice in China and other developing countries.

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