A Long-Term Analysis of Spatiotemporal
Change and Driving Factors on Poyang Lake
during 1987-2019

Zhu, Lin; Xing, Huaqiao; Dong-yang, Hou; Feng, Yongyu; Yang, Fengshuo; Qiu, Peiyuan

doi:10.15244/pjoes/131056

Cited by 3 publications

(4 citation statements)

References 25 publications

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“…Under the technological advantage, enterprises can utilize digital technology to develop products and drive their participation in emergency response, such as the emergency material supply chain big data management platform of China JD Logistics and the intelligent epidemic prevention black technology matrix created by SAIC GM Wuling. In order to understand the main driving factors affecting the changes in the water body of Poyang Lake, Zhu et al ( 41 ) analyzed the spatiotemporal changes of the four seasons of Poyang Lake through 124 remote sensing images, and found that both human and natural factors are the main driving factors affecting the changes in the water body of the lake. It can be seen that the results of the study are similar to those of experts such as Zhu et al ( 41 ).…”

Section: Discussionmentioning

confidence: 99%

“…In order to understand the main driving factors affecting the changes in the water body of Poyang Lake, Zhu et al ( 41 ) analyzed the spatiotemporal changes of the four seasons of Poyang Lake through 124 remote sensing images, and found that both human and natural factors are the main driving factors affecting the changes in the water body of the lake. It can be seen that the results of the study are similar to those of experts such as Zhu et al ( 41 ). In addition, the western region of China has the highest level of PHE, with the strongest seasonal intensity index from 2013 to August 2022.…”

Section: Discussionmentioning

confidence: 99%

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Drivers and collaborative governance of public health emergency response in the context of digital city

Chen,

2024

Front. Public Health

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IntroductionWith the frequent occurrence of public health events, the government inevitably makes many mistakes in emergency management. In modern emergency management, it is particularly important to promote the diversification of emergency management subjects and improve the government’s emergency management ability.MethodsIn order to make up for the deficiency of government’s participation in public health emergency management, this paper analyzes the driving factors and driving effects of enterprises’ participation in public health emergency response under the background of digital city. A fully explained structural model is used to analyze the relationship between the different drivers. In addition, the spatial and temporal distribution characteristics of public health events were analyzed through spatial auto-correlation. On this basis, the government cooperative governance strategy is discussed.Results and discussionThe results show that in the context of digital cities, there are 14 driving factors for enterprises to participate in public health emergency response. The most important factors are the company’s own development needs, relative technical advantages and so on. The driving efficiency is mainly concentrated in three aspects: psychology, resources and structure. Public health events have periodicity in time distribution and regional differences in spatial distribution. The significance of this study is to help the government improve the emergency management ability from different angles.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Drivers and collaborative governance of public health emergency response in the context of digital city

Chen,

2024

Front. Public Health

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“…Correlation analysis involves the breakdown of the association among two or more variables, usually to analyze whether the trends in two or more sets of data are consistent [25][26][27]. SPSS25 software was used to explore which factors were associated with the NPP value.…”

Section: Correlation Analysismentioning

confidence: 99%

Spatiotemporal Distribution of Carbon Sink Indicators—NPP and Its Driving Analysis in Ordos City, China

Zhu

Sun

et al. 2023

Applied Sciences

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Ordos City is an important energy supply city for Chinese provinces and cities, providing a secure energy supply for China while also generating corresponding environmental pollution. Examining the spatiotemporal patterns of net primary productivity (NPP) in Ordos City and its driving factors is relevant to the realization of the carbon emission policy in Inner Mongolia. This study was undertaken to analyze NPP and its driving factors in Ordos City from 2000 to 2019 using NPP data, CO2 spatial grid data, meteorological data and statistical yearbook data accordingly. The NPP in Ordos City increased significantly from 2000 to 2019, mainly showing low values of NPP in the northwest and high values in the southeast. The usable grassland area and annual mean precipitation had a significant positive correlation with NPP, whereas the other factors had a more significant negative correlation. The usable grassland area had the largest influence on NPP, and fixed asset investment had the smallest influence on NPP. The total NPP–anthropogenic factor regression model and the mean NPP–natural factor regression model constructed allow for the prediction of NPP. Anthropogenic carbon emissions, population growth and usable grassland area were the main causes of NPP changes. Planting and protecting green plants and scientific and effective energy extraction plans are measures that enhance the degree of carbon sequestration in Ordos City.

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“…Spatial correlation analysis was carried out between NPP and land cover to calculate correlation coefficients and clarify their association. The Pearson correlation coefficient was used to measure whether the two datasets lie on top of a line and to measure the linear relationship between the fixed distance variables [41][42][43]. Sig is an abbreviation for statistical significance [44].…”

Section: Spatial Correlation Analysismentioning

confidence: 99%

Analysis of Changes in Vegetation Carbon Storage and Net Primary Productivity as Influenced by Land-Cover Change in Inner Mongolia, China

et al. 2023

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Exploring the influence of vegetation carbon stocks over land-cover change and the relationship between land-cover change and net primary production (NPP) is of great practical importance for achieving China’s carbon neutrality target. Therefore, this paper analyses the spatio-temporal distribution of land-cover change and NPP change in Inner Mongolia from 2000 to 2020 and explores the vegetation carbon stock change caused by land-cover change, the relationship between land cover and NPP, and the relationship between land-cover change and NPP change. The results show that the main land-cover change in Inner Mongolia during 2000–2020 was the conversion from other land-cover types to grassland, with the conversion of bare land to grassland from 2000 to 2010 covering an area of 20,634.87 km2. During the period of 2000–2020, the high values of NPP were mainly located in northeastern Inner Mongolia, and the low values were mainly distributed in southwestern Inner Mongolia. The total carbon storage changes in vegetation affected by land-cover change during 2000–2010 and 2010–2020 were 10,736,986.11 t and 3,894,272.41 t. The mean values of NPP for different land covers were, in descending order, forest > cultivated land > wetland > grassland > artificial surfaces > shrubland > water bodies > bare land. Between 2000 and 2010, the change in land-cover type to water bodies was the main cause of the decrease in NPP, and the increase in NPP was mainly due to the conversion of other land-cover types to cultivated land, forest, and grassland. The implementation of appropriate conservation and management measures (e.g., the construction of forest and grass ecological protection), planting, and the protection of high-vegetation carbon storage plants and other means can improve the level of vegetation carbon sequestration and protect the ecological environment of Inner Mongolia.

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A Long-Term Analysis of Spatiotemporal Change and Driving Factors on Poyang Lake during 1987-2019

Cited by 3 publications

References 25 publications

Drivers and collaborative governance of public health emergency response in the context of digital city

Drivers and collaborative governance of public health emergency response in the context of digital city

Spatiotemporal Distribution of Carbon Sink Indicators—NPP and Its Driving Analysis in Ordos City, China

Analysis of Changes in Vegetation Carbon Storage and Net Primary Productivity as Influenced by Land-Cover Change in Inner Mongolia, China

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