Xin Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Xin Liu has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Ran Xiao
School of Civil and Environmental Engineering, Hunan University of Technology, Zhuzhou 412000, China
1 shared publication - Shijie Tang
Shanghai Academy of Fine Arts, Shanghai University, Shanghai 200444, China
1 shared publication - Shixiong Xie
School of Civil and Environmental Engineering, Hunan University of Technology, Zhuzhou 412000, China
1 shared publication - Suifeng Zhang
School of Civil and Environmental Engineering, Hunan University of Technology, Zhuzhou 412000, China
1 shared publication - Yu Chen
School of Architecture and Urban Planning, Hunan City University, Yiyang 413000, China
1 shared publication
Latest Publications
- Open Access
- 5 July 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (13) , 6832
Landscape Ecological Risks to Rural Landscape and Planning Implications: A Case Spatio-Temporal Analysis in Xiangxi Autonomous Prefecture of SW China
Maintaining regional landscape ecological stability and enhancing rural landscape ecosystem services are critical research priorities. This study selected Xiangxi Autonomous Prefecture (XXAP), a representative mountainous region in Southwestern (SW) China, as the case study area. This study aims to construct a rural landscape ecological risk (RLER) evaluation index system based on five-period remote sensing data (2000–2020), analyze the spatio-temporal characteristics of RLER, and provide a scientific basis for landscape ecological management and rural spatial governance. The results show that the RLERI exhibited a balanced multi-ring development trend, decreasing slightly from 0.295 in 2000 to 0.282 in 2020, suggesting a slight alleviation of overall risk. Medium-risk areas of the RLERI consistently accounted for the largest proportion (over 37%). Notably, the share of high-risk areas remained relatively stable, fluctuating narrowly between 7.98% and 8.73%. Meanwhile, high-risk areas of the landscape disturbance degree (LDD) expanded markedly from 1.87% to 10.28%. Correspondingly, high-risk areas of the landscape fragility degree (LFD) also increased significantly, rising from 0.93% to 2.8%. Spatially, RLER displayed significantly positive spatial autocorrelation, with high–high (H-H) clusters concentrated in the central-southern part and low–low (L-L) clusters distributed in the northern and southern margins, indicating pronounced spatial differentiation. In conclusion, this study provides a transferable framework for ecological risk assessment in mountainous regions. Furthermore, it underscores the importance of optimizing landscape patterns in ecologically fragile areas, strengthening ecological risk management, and mitigating ecological risks in rural settings.
- 5 July 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (13) , 6832
Open AccessLandscape Ecological Risks to Rural Landscape and Planning Implications: A Case Spatio-Temporal Analysis in Xiangxi Autonomous Prefecture of SW China
Maintaining regional landscape ecological stability and enhancing rural landscape ecosystem services are critical research priorities. This study selected Xiangxi Autonomous Prefecture (XXAP), a representative mountainous region in Southwestern (SW) China, as the case study area. This study aims to construct a rural landscape ecological risk (RLER) evaluation index system based on five-period remote sensing data (2000–2020), analyze the spatio-temporal characteristics of RLER, and provide a scientific basis for landscape ecological management and rural spatial governance. The results show that the RLERI exhibited a balanced multi-ring development trend, decreasing slightly from 0.295 in 2000 to 0.282 in 2020, suggesting a slight alleviation of overall risk. Medium-risk areas of the RLERI consistently accounted for the largest proportion (over 37%). Notably, the share of high-risk areas remained relatively stable, fluctuating narrowly between 7.98% and 8.73%. Meanwhile, high-risk areas of the landscape disturbance degree (LDD) expanded markedly from 1.87% to 10.28%. Correspondingly, high-risk areas of the landscape fragility degree (LFD) also increased significantly, rising from 0.93% to 2.8%. Spatially, RLER displayed significantly positive spatial autocorrelation, with high–high (H-H) clusters concentrated in the central-southern part and low–low (L-L) clusters distributed in the northern and southern margins, indicating pronounced spatial differentiation. In conclusion, this study provides a transferable framework for ecological risk assessment in mountainous regions. Furthermore, it underscores the importance of optimizing landscape patterns in ecologically fragile areas, strengthening ecological risk management, and mitigating ecological risks in rural settings.