Using Convolutional Neural Networks for Cloud Detection from Meteor-M No. 2 MSU-MR Data

被引：10

作者：

Andreev, A., I ^{[1
]}

Shamilova, Yu A. ^{[1
]}

Kholodov, E., I ^{[1
]}

机构：

[1] Planeta Res Ctr Space Hydrometeorol, Far Eastern Ctr, Ul Lenina 18, Khabarovsk 680000, Russia

来源：

RUSSIAN METEOROLOGY AND HYDROLOGY | 2019年 / 44卷 / 07期

关键词：

MSU-MR; cloud mask; cloud detection; convolutional neural network; neural network classifier;

D O I：

10.3103/S1068373919070045

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

A method for cloud detection using the machine-learning algorithm based on a convolutional neural network is presented. Input data are satellite images received from the MSU-MR multispectral low-resolution scanning unit onboard the Meteor-M No. 2 satellite. The developed method can be an alternative to the traditional algorithms of cloud detection based on the calculation of differential indices and thresholds. The algorithm is verified using the machine-learning metrics, comparing the resulting cloud mask with the reference one obtained by interpreting the satellite image by an experienced meteorologist. It was also compared (for verification) with a similar product based on VIIRS spectroradiometer data. The cloud mask computed using the algorithm allows the automatic thematic processing of satellite images.

引用

页码：459 / 466

页数：8