Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge-Reference-Cited by-同舟云学术

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge

Published:2024-02 Issue: Volume:345 Page:109810
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Wheeler Kathryn I.^ORCID,Dietze Michael C.,LeBauer David^ORCID,Peters Jody A.,Richardson Andrew D.^ORCID,Ross Arun A.,Thomas R. Quinn^ORCID,Zhu Kai^ORCID,Bhat Uttam^ORCID,Munch Stephan,Buzbee Raphaela Floreani^ORCID,Chen Min,Goldstein Benjamin^ORCID,Guo Jessica,Hao Dalei^ORCID,Jones Chris^ORCID,Kelly-Fair Mira,Liu Haoran^ORCID,Malmborg Charlotte^ORCID,Neupane Naresh,Pal Debasmita^ORCID,Shirey Vaughn,Song Yiluan^ORCID,Steen McKalee,Vance Eric A.^ORCID,Woelmer Whitney M.,Wynne Jacob H.^ORCID,Zachmann Luke^ORCID

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference63 articles.

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4. Boettiger, C., Thomas, R.Q., 2022. neon4cast: helper utilities for the EFI NEON forecast challenge. R package version 0.1.0.

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