11 citations as recorded by crossref.

1. Predicting dominant terrestrial biomes at a global scale using machine learning algorithms, climate variable indices, and extreme event indices H. Sato & C. Xu https://doi.org/10.1371/journal.pone.0324107
2. Dominant Species-Physiognomy-Ecological (DSPE) System for the Classification of Plant Ecological Communities from Remote Sensing Images R. Sharma https://doi.org/10.3390/ecologies3030025
3. Studies of arctic–boreal ecosystem function and biogeochemical cycles in the ArCS II terrestrial program H. Kobayashi et al. https://doi.org/10.1016/j.polar.2025.101164
4. Multi-model assessment of potential natural vegetation to support ecological restoration M. Ci et al. https://doi.org/10.1016/j.jenvman.2024.121934
5. Wood species classification using prototypical networks: a few shot learning model M. Diviya & M. Subramanian https://doi.org/10.1007/s13196-025-00366-5
6. Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning D. Han et al. https://doi.org/10.5194/gmd-16-5895-2023
7. Amazon dieback beyond the 21st century under high-emission scenarios by Earth System models I. Melnikova et al. https://doi.org/10.1038/s43247-025-02606-5
8. Climate classification systems for validating Earth System Models A. Navarro & F. Tapiador https://doi.org/10.1088/2752-5295/ad6632
9. Global Metrics for Terrestrial Biodiversity N. Burgess et al. https://doi.org/10.1146/annurev-environ-121522-045106
10. Compilation of cutting load spectrum for CNC lathe based on DBN-BP prediction model G. Li et al. https://doi.org/10.1177/09544062221141332
11. Predictive modeling of diverse factors impacting regional soil erosion degree with machine learning S. Hou et al. https://doi.org/10.1007/s12145-024-01329-z