Quantitative Estimation of Rainfall from Remote Sensing Data Using Machine Learning Regression Models

Quantitative Estimation of Rainfall from Remote Sensing Data Using Machine Learning Regression Models

To estimate rainfall from remote sensing data, three machine learning-based regression models, K-Nearest Neighbors Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were implemented using MSG (Meteosat Second Generation) satellite data. Daytime and nighttime da...

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Bibliographic Details
Main Authors: Yacine Mohia, Rafik Absi, Mourad Lazri, Karim Labadi, Fethi Ouallouche, Soltane Ameur
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Hydrology
Subjects:
remote sensing
rainfall
MSG Satellite
SVR
RF
RR
Online Access:https://www.mdpi.com/2306-5338/10/2/52

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