Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-3121-2022
https://doi.org/10.5194/gmd-15-3121-2022
Development and technical paper
 | 
18 Apr 2022
Development and technical paper |  | 18 Apr 2022

Predicting global terrestrial biomes with the LeNet convolutional neural network

Hisashi Sato and Takeshi Ise

Data sets

Sato and Ise (submitted) Open Data, version 3 Hisashi Sato https://doi.org/10.5281/zenodo.4401233

Download
Short summary
Accurately predicting global coverage of terrestrial biome is one of the earliest ecological concerns, and many empirical schemes have been proposed to characterize their relationship. Here, we demonstrate an accurate and practical method to construct empirical models for operational biome mapping via a convolutional neural network (CNN) approach.