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

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, et al.

Also available via: Ecological Indicators

A remote sensing-based tree mortality indicator for biodiversity monitoring using multispectral UAV and lidar in the Arctic region, Finland

Katalin Waga, Jaan Rönkkö, Mikko Kukkonen, Anton Kuzmin, Timo Kumpula, Parvez Rana

Deadwood is a recognised ecological indicator for forest biodiversity. Both the UN Convention on Biological Diversity and the EU Biodiversity Strategy 2030 mandates inventorying and reporting deadwood. However, monitoring tree mortality, the source of deadwood, remains challengin…Read more

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.

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

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

Spatiotemporal patterns and driving factors of net carbon intensity in arid cropland systems: An explainable machine learning study in the Hexi corridor

Han Bing, Chunfan Liu