Analysis of the temporal and spatial evolution characteristics and influencing factors of China’s herbivorous animal husbandry industry

Han, Chengji; Wang, Guogang; Zhang, Yongxiang; Song, Lili; Zhu, Lizhi

doi:10.1371/journal.pone.0237827

Cited by 20 publications

(15 citation statements)

References 24 publications

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“…The standard deviation ellipse can be used to quantify this trend of distribution [ 35 ]. The major semi-axis of the standard deviation ellipse represents the direction of the data distribution, and the minor semi-axis represents the range of the data distribution [ 36 ]. The larger the difference between the long and short semi-axis values (the greater the flatness), the more obvious the directionality of the data.…”

Section: Implement and Resultsmentioning

confidence: 99%

Measuring of the COVID-19 Based on Time-Geography

Yin

Huang

Ying

et al. 2021

IJERPH

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At the end of 2019, the COVID-19 pandemic began to emerge on a global scale, including China, and left deep traces on all societies. The spread of this virus shows remarkable temporal and spatial characteristics. Therefore, analyzing and visualizing the characteristics of the COVID-19 pandemic are relevant to the current pressing need and have realistic significance. In this article, we constructed a new model based on time-geography to analyze the movement pattern of COVID-19 in Hebei Province. The results show that as time changed COVID-19 presented an obvious dynamic distribution in space. It gradually migrated from the southwest region of Hebei Province to the northeast region. The factors affecting the moving patterns may be the migration and flow of population between and within the province, the economic development level and the development of road traffic of each city. It can be divided into three stages in terms of time. The first stage is the gradual spread of the epidemic, the second is the full spread of the epidemic, and the third is the time and again of the epidemic. Finally, we can verify the accuracy of the model through the standard deviation ellipse and location entropy.

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Section: Implement and Resultsmentioning

confidence: 99%

Measuring of the COVID-19 Based on Time-Geography

Yin

Huang

Ying

et al. 2021

IJERPH

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“…Temporal autocorrelation analyses (used in time-series analysis), by contrast, seeks to identify the degree to which a value at any point in a time series is influenced by the value of the variable in past times over some lag interval (i.e., a measure of “memory” in the time series). Spatial autocorrelation is static and is not by itself designed to address temporal trends, although spatial autocorrelations of different time periods are sometimes compared (e.g., Han et al, 2020). Temporal autocorrelation, while incorporating temporality, does not address spatial correlations between multiple series or measure variability through time.…”

Section: Time-iterative Moran Index (Timi): a New Approach To Time Se...mentioning

confidence: 99%

Human Paleodemography and Paleoecology of the North Pacific Rim from the Mid to Late Holocene

et al. 2022

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Using 14 proxy human population time series from around the North Pacific (Alaska, Hokkaido and the Kuril Islands), we evaluate the possibility that the North Pacific climate and marine ecosystem includes a millennial-scale regime shift cycle affecting subsistence and migration. We develop both visual and statistical methods for addressing questions about relative population growth and movement in the past. We introduce and explore the use of a Time Iterative Moran I (TIMI) spatial autocorrelation method to compare time series trends quantitatively – a method that could prove useful in other paleoecological analyses. Results reveal considerable population dynamism around the North Pacific in the last 5000 years and strengthen a previously reported inverse correlation between Northeast and Northwest Pacific proxy population indices. Visual and TIMI analyses suggest multiple, overlapping explanations for the variability, including the potential that oscillating ecological regime shifts affect the North Pacific basin. These results provide an opening for coordinated research to unpack the interrelated social, cultural and environmental dynamics around the subarctic and arctic North Pacific at different spatial and temporal scales by international teams of archaeologists, historians, paleoecologists, paleoceanographers, paleoclimatologists, modelers and data management specialists.

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“…The standard deviational ellipse (SDE) is one of the classical spatial statistical methods (Lefever 1926) and can accurately reveal the spatial distribution characteristics and evolution of geographical elements by calculating the parameters of centrality, coordinates, azimuth, major axis and minor axis, area, oblateness, etc. It has been widely used to quantitatively describe the spatial distribution characteristics and spatiotemporal evolution of social and economic elements (Tian et al 2019;Muhammad et al 2019;Lu et al 2020;Huang et al 2021) and natural geographical elements (Han et al 2020;Yuan et al 2020;Chen et al 2021). The parameters of SDE are calculated as follows (Du et al 2019;Yuan et al 2020;Chen et al 2021):…”

Section: Standard Deviational Ellipsementioning

confidence: 99%

Green water resource utilization efficiency in urban agglomerations: measurement, spatiotemporal variations and influencing factors

hu¹,

La²,

Yuan³

2021

Preprint

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Green development is the coordinated development of the economy, society and environment and has become a mainstream development model. This paper evaluates the green water resource utilization efficiency (GWRUE) of 38 regions in the four-city area in central China during 2010–2019 using a super-slacks-based measure (super-SBM) DEA model considering unexpected output. Then, the spatiotemporal variations in GWRUE are analyzed by the standard deviational ellipse method, and the geographical detector method is employed to reveal the dominant impacts and interaction impacts on GWRUE spatiotemporal variations. The results show that (1) from 2010 to 2019, the GWRUE in the four-city area in central China was low, and the difference among regions was obvious, showing a downward trend. (2) From 2010 to 2019, the spatial gravity center of GWRUE experienced a change process from northeast to southwest, and its moving speed showed a “waveform” rising trend. Moreover, the SDE range of each characteristic time point showed a decreasing trend, indicating that the spatial variations in GWRUE tended to be agglomerated. (3) From 2010 to 2019, the influence of each factor on the spatial variations in GWRUE was different each year. In addition, the two-way interactions between different influencing factors were mainly manifested as bivariate enhancement relationships and nonlinear enhancement relationships and were especially affected by multiple factors that produce a nonlinear enhancement interaction. This study can provide a practical basis for realizing water ecological civilization construction and high-quality development in the four-city area in central China.

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Analysis of the temporal and spatial evolution characteristics and influencing factors of China’s herbivorous animal husbandry industry

Cited by 20 publications

References 24 publications

Measuring of the COVID-19 Based on Time-Geography

Measuring of the COVID-19 Based on Time-Geography

Human Paleodemography and Paleoecology of the North Pacific Rim from the Mid to Late Holocene

Green water resource utilization efficiency in urban agglomerations: measurement, spatiotemporal variations and influencing factors

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