Cite
Exploration of Machine Learning Techniques in Emulating a Coupled Soil–Canopy–Atmosphere Radiative Transfer Model for Multi-Parameter Estimation From Satellite Observations.
MLA
Shi, Hanyu, et al. “Exploration of Machine Learning Techniques in Emulating a Coupled Soil–Canopy–Atmosphere Radiative Transfer Model for Multi-Parameter Estimation From Satellite Observations.” IEEE Transactions on Geoscience & Remote Sensing, vol. 57, no. 11, Nov. 2019, pp. 8522–33. EBSCOhost, https://doi.org/10.1109/TGRS.2019.2921392.
APA
Shi, H., Xiao, Z., & Tian, X. (2019). Exploration of Machine Learning Techniques in Emulating a Coupled Soil–Canopy–Atmosphere Radiative Transfer Model for Multi-Parameter Estimation From Satellite Observations. IEEE Transactions on Geoscience & Remote Sensing, 57(11), 8522–8533. https://doi.org/10.1109/TGRS.2019.2921392
Chicago
Shi, Hanyu, Zhiqiang Xiao, and Xiaodan Tian. 2019. “Exploration of Machine Learning Techniques in Emulating a Coupled Soil–Canopy–Atmosphere Radiative Transfer Model for Multi-Parameter Estimation From Satellite Observations.” IEEE Transactions on Geoscience & Remote Sensing 57 (11): 8522–33. doi:10.1109/TGRS.2019.2921392.