Geospatial Explainable AI Uncovers Eco-Environmental Effects and Its Driving Mechanisms—Evidence from the Poyang Lake Region, China
Intensified human activities and changes in land-use patterns have led to numerous eco-environmental challenges. A comprehensive understanding of the eco-environmental effects of land-use transitions and their driving mechanisms is essential for developing scientifically sound and sustainable enviro...
Saved in:
| Main Authors: | Mingfei Li, Zehong Zhu, Junye Deng, Jiaxin Zhang, Yunqin Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Land |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-445X/14/7/1361 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Unraveling Street Configuration Impacts on Urban Vibrancy: A GeoXAI Approach
by: Longzhu Xiao, et al.
Published: (2025-07-01) -
Pre Hoc and Co Hoc Explainability: Frameworks for Integrating Interpretability into Machine Learning Training for Enhanced Transparency and Performance
by: Cagla Acun, et al.
Published: (2025-07-01) -
An Efficient Explainability of Deep Models on Medical Images
by: Salim Khiat, et al.
Published: (2025-04-01) -
A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX)
by: Jong-Hwan Jang, et al.
Published: (2025-07-01) -
Landslide susceptibility assessment through multi-model stacking and meta-learning in Poyang County, China
by: Yong Song, et al.
Published: (2024-12-01)