A graded index for evaluating precipitation heterogeneity in China

Liu, Yonglin; Jun-ping, Yan; Cen, Min; Fang, Qunsheng; Liu, Zhengyao; Li, Yingjie

doi:10.1007/s11442-016-1292-1

Cited by 9 publications

(2 citation statements)

References 10 publications

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“…We speculated that this result was related to the uneven spatio-temporal distribution of precipitation in the aforementioned areas. Such variation can easily lead to heavy precipitation and flooding or drought, which not only directly cause economic losses but also have a considerable negative effect on economic productivity and people's lives (Liu et al, 2015).…”

Section: Figure 7 Spatial Distribution Of Regression Coefficients Of ...mentioning

confidence: 99%

Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China

Yin

Zhang

et al. 2022

J. Geogr. Sci.

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Accelerating economic growth in formerly destitute areas and narrowing the economic gap with other regions are essential tasks for poverty alleviation in China after 2020. In this study, the spatio-temporal characteristics of economic growth in 14 formerly destitute areas of China were identified. Moreover, the spatial heterogeneity of various influencing factors was analyzed using a geographically weighted regression model. The results were as follows: (1) The economic level of the formerly destitute areas was low, but their economies grew rapidly after 2011, with annual per capita GDP growth of 10.54% until 2018, higher than the national average of 9.14%. Western and southern counties grew faster economically than central and northern counties. (2) The impact of various factors on the economic growth of counties exhibited clear spatial heterogeneity. The influences of secondary industry growth and level of financial development on economic growth were mainly positive, whereas the effects of initial economic level and market location were mainly negative. (3) Six economic growth driving modes were identified for the 14 contiguous destitute areas, among which the secondary industry-driven mode was the most common. The study can serve as a scientific reference for differentiating regional policies.

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Section: Figure 7 Spatial Distribution Of Regression Coefficients Of ...mentioning

confidence: 99%

Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China

Yin

Zhang

et al. 2022

J. Geogr. Sci.

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“…First, according to a range of parameters, mathematical statistics were used to determine the cumulative percentage. Then, the coefficient of variation (CV) was calculated to compare the degree of dispersion and data stability for different dimensions or different means [21]. Among these, the greater the CV value is, the greater the degree of dispersion will be, namely, the greater the volatility of the data.…”

Section: Parameter Calculationmentioning

confidence: 99%

Morphometry of lunette dunes in the Tirari Desert, South Australia

2018

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Morphometry and formation processes are key research problems in the study of aeolian sandy landforms. Based on morphometric parameters inferred from satellite images and the calculation of the drift potential (DP), we examined general characteristics of lunette dunes in the Tirari Desert, South Australia, along with their morphometry and formation processes to determine how this landform type initially formed and its relationship to surrounding linear dune distribution. Results show that the morphometric parameters of lunette dunes and connective lake systems exhibit moderate correlations. It suggests that the morphology of these dunes is controlled by the lakes. Spatially, the lunette dunes present regular arrangement, and the strike of their alignment are approximately in accordance with the linear dunes. The calculated DP implies that the lunette dunes developed under a low-wind-energy environment, which is a wind regime similar to that required for the formation of the surrounding linear dunes. Even though, the resultant DP demonstrates that the summer wind should be responsible for the growth of the lunette dunes. However, accompanied with the repeated drying of lakes and even its disappearance during the dune development process, it not only contributes to the development of lunette dunes but also promotes their transformation to linear dunes.

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