Huan LIU

Dr. Huan LIU


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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1 February 2025 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
YYYongsheng Yang
Yongsheng Yang
HLHuan LIU
Huan LIU
AMAli Mostafavi
Ali Mostafavi
HTHirokazu Tatano
Hirokazu Tatano

14 July 2022 in Frontiers in Environmental Science
Verified
Journal Article
Open access
Chunguang HuChunguang Hu
Chunguang Hu
ZWZiyi Wang
Ziyi Wang
WLWenzhong Li
Wenzhong Li
HLHuan LIU
Huan LIU
DSDongqi Sun
Dongqi Sun
Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

17 October 2022 in International Journal of Disaster Risk Reduction
Verified
Journal Article
Closed access
HLHuan LIU
Huan LIU
HTHirokazu Tatano
Hirokazu Tatano
YKYoshio Kajitani
Yoshio Kajitani
YYYongsheng Yang
Yongsheng Yang

18 June 2023 in Sustainable Cities and Society
Verified
Journal Article
Closed access
YYYongsheng Yang
Yongsheng Yang
HLHuan LIU
Huan LIU
SZShaobo Zhong
Shaobo Zhong
KLKai Liu
Kai Liu
MWMing Wang
Ming Wang
QHQuanyi Huang
Quanyi Huang

4 February 2023 in International Journal of Disaster Risk Reduction
Verified
Journal Article
Closed access
HLHuan LIU
Huan LIU
HTHirokazu Tatano
Hirokazu Tatano
SSSubhajyoti Samaddar
Subhajyoti Samaddar

1 May 2021 in Earthquake Spectra
Verified
Journal Article
Closed access
PDF file
HLHuan LIU
Huan LIU
HTHirokazu Tatano
Hirokazu Tatano
YKYoshio Kajitani
Yoshio Kajitani