16 citations as recorded by crossref.

1. Multi‐criteria decision analysis integrated with GIS to determine land suitability for cultivation and best harvest time of vine H. Amin et al.
2. Remote sensing of biogeophysical variables at the Cape Bounty Arctic Watershed Observatory, Melville Island, Nunavut, Canada P. Treitz et al.
3. 多年冻土过渡带研究进展与展望 D. Luo et al.
4. Deep learning algorithms based landslide vulnerability modeling in highly landslide prone areas of Tamil Nadu, India S. Saha et al.
5. Evaluating of Quantitative Geomorphometric Parameters Efficiency in Increasing the Accuracy of Landslide Sensitivity Maps (Case Study: Fereydoun Shahr Basin, Isfahan Province) a. arabameri et al.
6. Multi-scale site evaluation of a relict active layer detachment in a High Arctic landscape M. Paquette et al.
7. Determining prone areas to gully erosion and the impact of land use change on it by using multiple-criteria decision-making algorithm in arid and semi-arid regions M. Mokarram & A. Zarei
8. Machine learning-based mapping of fog water harvesting potential in Pithoragarh, Uttarakhand: Evaluating climate scenarios and geospatial influences C. Singha et al.
9. Robustness of Optimized Decision Tree-Based Machine Learning Models to Map Gully Erosion Vulnerability H. Eloudi et al.
10. Machine learning-based predictions of current and future susceptibility to retrogressive thaw slumps across the Northern Hemisphere J. Luo et al.
11. Investigation of water quality and its spatial distribution in the Kor River basin, Fars province, Iran M. Mokarram et al.
12. Effects of permafrost stability changes on vegetation dynamics in the middle part of the Greater Khingan Mountains J. Sun et al.
13. GIS-based Gully Erosion Susceptibility Evaluation Using Frequency Ratio, Cosine Amplitude and Logistic Regression Ensembled with fuzzy logic in Hinglo River Basin, India J. Roy & D. Saha
14. Machine learning-based thermokarst landslide susceptibility modeling across the permafrost region on the Qinghai-Tibet Plateau G. Yin et al.
15. Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm A. Arabameri et al.
16. Machine Learning-Based Gully Erosion Susceptibility Mapping: A Case Study of Eastern India S. Saha et al.