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基于机器学习的生态变量全球图谱及其评估挑战。

Machine learning-based global maps of ecological variables and the challenge of assessing them.

机构信息

Institute of Landscape Ecology, Westfälische Wilhelms-Universität Münster, Heisenbergstraße 2, Münster, 48149, Germany.

Institute for Geoinformatics, Westfälische Wilhelms-Universität Münster, Heisenbergstraße 2, Münster, 48149, Germany.

出版信息

Nat Commun. 2022 Apr 22;13(1):2208. doi: 10.1038/s41467-022-29838-9.

DOI:10.1038/s41467-022-29838-9
PMID:35459230
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9033849/
Abstract

The recent wave of published global maps of ecological variables has caused as much excitement as it has received criticism. Here we look into the data and methods mostly used for creating these maps, and discuss whether the quality of predicted values can be assessed, globally and locally.

摘要

最近发布的一波全球生态变量地图引起了人们的兴奋,也招致了批评。在这里,我们研究了用于创建这些地图的主要数据和方法,并讨论了是否可以在全球和局部范围内评估预测值的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1192/9033849/aee7c2d8cd3d/41467_2022_29838_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1192/9033849/aee7c2d8cd3d/41467_2022_29838_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1192/9033849/aee7c2d8cd3d/41467_2022_29838_Fig1_HTML.jpg

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