crossrefEcological Indicators2026-08-01Cited by 0

Advancing ecological network resilience early warning in alpine source regions: A machine learning and multi-scale diagnostic framework

Shangbo Li, Yong Chen, Lihua Zhou, Ximing Huang, Jing Shu, Qihan Huang, Yuzhong Yang

Also available via: Ecological Indicators

Related papers

semantic_scholarEcological Indicators2026-08-01

Application of multi-scale deep convolutional neural networks (MDCNN) to susceptibility assessment of rainfall-induced landslides in typical southern hilly areas: A case study of Wanxiu District, Wuzhou City, Guangxi, China

Zhongqian Zhang, Chenting Wang, Jing Gan, Shuangqing Sheng, Yining Zhang, Qingwei Zeng, et al.

View free PDFSource page

semantic_scholarEcological Indicators2026-08-01

Research on the sustainability evolution of cultivated land ecosystems in the North China plain integrating policy scenario simulation and deep learning diagnosis

Xinyu Hu, Yu Zhang, Changyuan Wang, Chun Dong, Lina Wang

View free PDFSource page

semantic_scholarEcological Indicators2026-08-01

Nonlinear attribution and precision governance of urban resilience in Henan: An integrated machine learning and Geographically Weighted Random Forest approach

Dandan Dong, Pan-pan Liu, Guowu Deng, Xinxin Qie, Dan Ralescu, Ersen Miao

View free PDFSource page

semantic_scholarEcological Indicators2026-08-01

Research on attribution and prediction of runoff changes in loess gully areas based on SWAT and machine learning models

Yun Zhao, Enhui Jiang, Bo Qu, Rui Zhang, Chang Liu, Jiaqi Li, et al.

View free PDFSource page

crossrefEcological Indicators2026-08-01

Integrated effects of land-use change and human–environment interactions on habitat quality in the Chengdu–Chongqing urban agglomeration: Insights from explainable machine learning and structural equation modeling

Li Wang, Zhongsheng Chen, Ling Zhang, Xiaoyu Gao, Xinyu Xiong, Shuo Liu

Also available via: Ecological Indicators

crossrefEcological Indicators2026-08-01

Enhancing satellite-based turbidity monitoring in drinking water source lakes using optical classification–guided machine learning

Zhilong Zhao, Shaohua Lei, Xiaoran Gong, Shaoqi Gong, Xiaolan Cai, Shuai Zeng, et al.

Also available via: Ecological Indicators