Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in s...

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Bibliographic Details
Main Authors: Yanxing Hu, Tao Che, Liyun Dai, Lin Xiao
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
snow depth datasets
data fusion
machine learning algorithms
the Northern Hemisphere
Online Access:https://www.mdpi.com/2072-4292/13/7/1250

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