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This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar

Nanchao Wang, Da Xiao, Igor Veselovskii, Yuan Wang, Lynn M. Russell, Chuanfeng Zhao, Jianping Guo, Chengcai Li, Silke Groß, Xu Liu, Xueqi Ni, Lizhou Tan, Yuxuan Liu, Kai Zhang, Yicheng Tong, Lingyun Wu, Feitong Chen, Binyu Wang, Chong Liu, Weibiao Chen, Dong Liu

2022Remote Sensing of Environment14 citationsDOI

Topics & Concepts

LidarAerosolRemote sensingMode (computer interface)Computer scienceEnvironmental scienceWavelengthMeteorologyOpticsGeologyPhysicsOperating systemAtmospheric aerosols and cloudsAtmospheric and Environmental Gas DynamicsAtmospheric chemistry and aerosols
This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar | Litcius