Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach

Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach

Year of publication

2021

Authors

Yang, J.W.; Jiang, L.M.; Lemmetyinen, J.; Pan, J.M.; Luojus, K.; Takala, M.

Organizations and authors

Finnish Meteorological Institute

Luojus K. Orcid -palvelun logo

Takala M. Orcid -palvelun logo

Lemmetyinen J. Orcid -palvelun logo

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Publisher

Elsevier

Volume

264

Article number

112630

Pages

112630

​Publication forum

66054

​Publication forum level

3

Open access

Open access in the publisher’s service

No

Self-archived

No

Other information

Fields of science

Geosciences

Publication country

United States

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

DOI

10.1016/j.rse.2021.112630

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes