梦晓 刘

Dr. 梦晓 刘

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2021 in Spatial Statistics
Verified
Journal Article
Closed access
梦刘梦晓 刘
梦晓 刘
SHShan Hu
Shan Hu
YGYong Ge
Yong Ge
GHGerard B.M. Heuvelink
Gerard B.M. Heuvelink
ZRZhoupeng Ren
Zhoupeng Ren
XHXiaoran Huang
Xiaoran Huang

27 October 2023 in AMBIO
Verified
Journal Article
Closed access
PDF file
RXRui Xiao
Rui Xiao
HHHaiguang Hao
Haiguang Hao
HZHuiyuan Zhang
Huiyuan Zhang
YLYujie Liu
Yujie Liu
梦刘梦晓 刘
梦晓 刘

Verified
Journal Article
Open access
PDF file
梦刘梦晓 刘
梦晓 刘
Yong GeYong Ge
Yong Ge
SHShan Hu
Shan Hu
HHHaiguang Hao
Haiguang Hao
Recognizing the spatial effects of regional poverty is essential for achieving sustainable poverty alleviation. This study investigates these spatial effects and their determinants across three distinct administrative levels within Hubei Province, China. To analyze the spatial patterns and heterogeneity of multi-scale regional poverty, we employed various spatial analysis techniques, including the global and local Moran’s I statistics, the Lineman, Merenda, and Gold (LMG) method, as well as Multiscale Geographically Weighted Regression (MGWR). We found that: (1) Regional poverty exhibits significant spatial dependence across various scales, with a higher level of spatial dependence observed at higher administrative levels. (2) The spatial distribution of poverty is primarily influenced by geographical factors, encompassing first-, second-, and third-nature geographical elements. Notably, first-nature geographical factors make substantial contributions, accounting for 36.99%, 42.23%, and 23.79% at the county, township, and village levels, respectively. (3) The influence of geographical factors varies with scale. Global effects of various factors may transcend scales or remain confined to specific scales, while the local impacts of different factors also exhibit variations across scales. These results underscore the necessity for collaborative efforts among government entities at different levels with the anti-poverty measures tailored to local contexts.

7 February 2022 in Spatial Statistics
Verified
Journal Article
Closed access
梦刘梦晓 刘
梦晓 刘
YGYong Ge
Yong Ge
SHShan Hu
Shan Hu
ASAlfred Stein
Alfred Stein
ZRZhoupeng Ren
Zhoupeng Ren

24 July 2015 in Atmosphere
Verified
Journal Article
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MHMaogui Hu
Maogui Hu
JWJianghao Wang
Jianghao Wang
Yong GeYong Ge
Yong Ge
梦刘梦晓 刘
梦晓 刘
SLShaomin Liu
Shaomin Liu
Tongren XuTongren Xu
Tongren Xu
Sensible heat flux (H) plays an important role in characterizations of land surface water and heat balance. There are various types of H measurement methods that depend on observation scale, from local-area-scale eddy covariance (EC) to regional-scale large aperture scintillometer (LAS) and remote sensing (RS) products. However, methods of converting one H scale to another to validate RS products are still open for question. A previous area-to-area regression kriging-based scaling method performed well in converting EC-scale H to LAS-scale H. However, the method does not consider the path-weighting function in the EC- to LAS-scale kriging with the regression residue, which inevitably brought about a bias estimation. In this study, a weighted area-to-area regression kriging (WATA RK) model is proposed to convert EC-scale H to LAS-scale H. It involves path-weighting functions of EC and LAS source areas in both regression and area kriging stages. Results show that WATA RK outperforms traditional methods in most cases, improving estimation accuracy. The method is considered to provide an efficient validation of RS H flux products.

29 March 2021 in BMC Public Health
Verified
Journal Article
Open access
PDF file
Yong GeYong Ge
Yong Ge
WZWenbin Zhang
Wenbin Zhang
JWJianghao Wang
Jianghao Wang
梦刘梦晓 刘
梦晓 刘
ZRZhoupeng Ren
Zhoupeng Ren
ZTZhaoxing Tian
Zhaoxing Tian
Background: The effect of the COVID-19 outbreak has led policymakers around the world to attempt transmission control. However, lockdown and shutdown interventions have caused new social problems and designating policy resumption for infection control when reopening society remains a crucial issue. We investigated the effects of different resumption strategies on COVID-19 transmission using a modeling study setting.Methods: We employed a susceptible-exposed-infectious-removed model to simulate COVID-19 outbreaks under five reopening strategies based on China’s business resumption progress. The effect of each strategy was evaluated using the peak values of the epidemic curves vis-à-vis confirmed active cases and cumulative cases. Two-sample t-test was performed in order to affirm that the pick values in different scenarios are different.Results: We found that a hierarchy-based reopen strategy performed best when current epidemic prevention measures were maintained save for lockdown, reducing the peak number of active cases and cumulative cases by 50 and 44%, respectively. However, the modeled effect of each strategy decreased when the current intervention was lifted somewhat. Additional attention should be given to regions with significant numbers of migrants, as the potential risk of COVID-19 outbreaks amid society reopening is intrinsically high.Conclusions: Business resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases.