Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation

Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation

Identifying dust aerosols from passive satellite images is of great interest for many applications. In this study, we developed five different machine-learning (ML) based algorithms, including Logistic Regression, K Nearest Neighbor, Random Forest (RF), Feed Forward Neural Network (FFNN), and Convol...

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Bibliographic Details
Main Authors: Jangho Lee, Yingxi Rona Shi, Changjie Cai, Pubu Ciren, Jianwu Wang, Aryya Gangopadhyay, Zhibo Zhang
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
CALIOP
VIIRS
machine learning
deep learning
dust detection
Online Access:https://www.mdpi.com/2072-4292/13/3/456

Internet

https://www.mdpi.com/2072-4292/13/3/456

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