scholarly journals Spatiotemporal evolution, pattern of diffusion and influencing factors of the COVID‐19 epidemic in Hainan Province, China

2021 ◽  
Author(s):  
Xing Gao ◽  
Gang Li ◽  
Jiaobei Wang ◽  
Tingting Xu
Keyword(s):  
Influencing Factors ◽  
Hainan Province ◽  
Spatiotemporal Evolution ◽  
Evolution Pattern

scholarly journals The Spatiotemporal Evolution Pattern and Influential Factor of Regional Carbon Emission Convergence in China

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Xin Tong
Keyword(s):  
Economic Development ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Influential Factor ◽  
Spatiotemporal Evolution ◽  
Reduction Strategy ◽  
Emission Level ◽  
Evolution Pattern ◽  
Convergence Model

As economic development rapidly progresses in China, a method of carbon emission control that provides reasonable solutions is needed. This paper analyzes the convergence of carbon emission evolutionary characteristics in different regions of China and studies the dynamics of carbon emissions in China based on a convergence model. It was found that the carbon emission levels of each region are prominent in terms of time, and the regional carbon emission level has absolute β characteristics. The regional carbon emission condition β convergences have different convergence paths. Therefore, it is necessary to justify carbon emission reduction in China and put forward an emission reduction strategy.

scholarly journals Spatial difference of multidimensional poverty and its influencing factors in the rural areas of Hainan Province

2020 ◽  
Vol 39 (6) ◽  
pp. 1013-1023
Author(s):  
Jinping ZHANG ◽  
Dan LIN ◽  
Xiangli ZHOU ◽  
Zhenxin YU ◽  
Wei SONG ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Rural Areas ◽  
Multidimensional Poverty ◽  
Hainan Province ◽  
Spatial Difference

scholarly journals Social Media Big Data-Based Research on the Influencing Factors of Insomnia and Spatiotemporal Evolution

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 41516-41529
Author(s):  
Yu Liu ◽  
Qinyao Luo ◽  
Hang Shen ◽  
Sida Zhuang ◽  
Chen Xu ◽  
...  
Keyword(s):  
Social Media ◽  
Big Data ◽  
Influencing Factors ◽  
Spatiotemporal Evolution

scholarly journals Spatiotemporal evolution and diffusion pattern of the COVID-19 epidemic in Hainan Province, China

2020 ◽  
Author(s):  
Xing Gao ◽  
Gang Li ◽  
Jiaobei Wang ◽  
Tingting Xu
Keyword(s):  
High Intensity ◽  
Practical Significance ◽  
Hainan Province ◽  
Spatiotemporal Evolution ◽  
Tourist Destination ◽  
First Case ◽  
Economic Exchanges ◽  
Diffusion Pattern ◽  
And Diffusion

Abstract Within one month after the first case occurred in Hainan Province, the number of confirmed cases increased to 168, and there was no increase in nearly three months. As the southernmost province and a famous tourist destination, its frequent economic exchanges and high-intensity movements may affect the spread of epidemic. Therefore, it is of great theoretical and practical significance to examine the spatiotemporal evolution and diffusion pattern of the COVID-19 epidemic in Hainan Province.

scholarly journals Spatiotemporal Evolution of Lakes under Rapid Urbanization: A Case Study in Wuhan, China

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1171
Author(s):  
Chao Wen ◽  
Qingming Zhan ◽  
De Zhan ◽  
Huang Zhao ◽  
Chen Yang
Keyword(s):  
Influencing Factors ◽  
Lake Restoration ◽  
Spatial Relationship ◽  
Lake Area ◽  
Urban Context ◽  
Spatiotemporal Evolution ◽  
Rapid Urbanization ◽  
Ecological Index ◽  
The Government ◽  
The Impact

The impact of urbanization on lakes in the urban context has aroused continuous attention from the public. However, the long-term evolution of lakes in a certain megacity and the heterogeneity of the spatial relationship between related influencing factors and lake changes are rarely discussed. The evolution of 58 lakes in Wuhan, China from 1990 to 2019 was analyzed from three aspects of lake area, lake landscape, and lakefront ecology, respectively. The Multi-Scale Geographic Weighted Regression model (MGWR) was then used to analyze the impact of related influencing factors on lake area change. The investigation found that the total area of 58 lakes decreased by 15.3%. A worsening trend was found regarding lake landscape with the five landscape indexes of lakes dropping; in contrast, lakefront ecology saw a gradual recovery with variations in the remote sensing ecological index (RSEI) in the lakefront area. The MGWR regression results showed that, on the whole, the increase in Gross Domestic Product (GDP), RSEI in the lakefront area, precipitation, and humidity contributed to lake restoration. The growth of population and the proportion of impervious surface (IS) in the lakefront area had different effects on different lakes. Specifically, the increase in GDP and population in all downtown districts and two suburb districts promoted lake restoration (e.g., Wu Lake), while the increase in population in Jiangxia led to lake loss. The growth of RSEI in lakefront area promoted the restoration of most lakes. A higher proportion of IS in lakefront area normally resulted in more lake loss. However, in some cases, the growth of IS was caused by lake conservation, which contributed to lake restoration (e.g., Tangxun Lake). The study reveals the spatiotemporal evolution of multiple lakes in Wuhan and provides a useful reference for the government to formulate differentiated protection policies.

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