The usual method of aerosol retrieval using remote sensing is interpolation of look-up-table (LUT), but it is too time-consuming. However, artificial neural network for nonlinear problem has been not applied widely for aerosol retrieval before. In this paper, aerosol optical depth (AOD) is retrieved using two methods: interpolation and neural network. Then, the retrieval capabilities of the two methods were compared. By comparison, not only is the retrieval error of the neural network within acceptable range, but also it can reduce much processing time. © 2010 IEEE
Abstract. The calibrated ground-based sky imager devel-oped in the Marine Physical Laboratory, the W...
This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) a...
Aerosols can absorb and scatter surface solar radiation (SSR), which is called the aerosol radiative...
In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties fro...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
Aerosols are an integral part of Earth's climate system and their effect on climate makes this field...
In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties fro...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
Abstract — In many applications of the neural networks, predicting the conditional average of the ta...
To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared...
inn this paper, we present three algorithms for aerosol parameters retrieval from TROPOMI measuremen...
Abstract:-Aerosol size distribution (ASD) is an integral parameter in regional atmospheric models [1...
In this work, we present a method to predict missing aerosol optical depth (AOD) values at an AERONE...
Abstract. The calibrated ground-based sky imager devel-oped in the Marine Physical Laboratory, the W...
This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) a...
Aerosols can absorb and scatter surface solar radiation (SSR), which is called the aerosol radiative...
In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties fro...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
Aerosols are an integral part of Earth's climate system and their effect on climate makes this field...
In this paper, the use of a neural network algorithm for the retrieval of the aerosol properties fro...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is pres...
Abstract — In many applications of the neural networks, predicting the conditional average of the ta...
To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared...
inn this paper, we present three algorithms for aerosol parameters retrieval from TROPOMI measuremen...
Abstract:-Aerosol size distribution (ASD) is an integral parameter in regional atmospheric models [1...
In this work, we present a method to predict missing aerosol optical depth (AOD) values at an AERONE...
Abstract. The calibrated ground-based sky imager devel-oped in the Marine Physical Laboratory, the W...
This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) a...
Aerosols can absorb and scatter surface solar radiation (SSR), which is called the aerosol radiative...