An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques.

MLA

Gholami, Hamid, et al. “An Assessment of Global Land Susceptibility to Wind Erosion Based on Deep-Active Learning Modelling and Interpretation Techniques.” Scientific Reports, vol. 14, no. 1, Aug. 2024, pp. 1–16. EBSCOhost, https://doi.org/10.1038/s41598-024-70125-y.

APA

Gholami, H., Mohammadifar, A., Song, Y., Li, Y., Rahmani, P., Kaskaoutis, D. G., Panagos, P., & Borrelli, P. (2024). An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques. Scientific Reports, 14(1), 1–16. https://doi.org/10.1038/s41598-024-70125-y

Chicago

Gholami, Hamid, Aliakbar Mohammadifar, Yougui Song, Yue Li, Paria Rahmani, Dimitris G. Kaskaoutis, Panos Panagos, and Pasquale Borrelli. 2024. “An Assessment of Global Land Susceptibility to Wind Erosion Based on Deep-Active Learning Modelling and Interpretation Techniques.” Scientific Reports 14 (1): 1–16. doi:10.1038/s41598-024-70125-y.