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

被引：124

作者：

Meyer, Hanna ^{[1
]}

Pebesma, Edzer ^{[2
]}

机构：

[1] Westfal Wilhelms Univ Munster, Inst Landscape Ecol, Heisenbergstr 2, D-48149 Munster, Germany

[2] Westfal Wilhelms Univ Munster, Inst Geoinformat, Heisenbergstr 2, D-48149 Munster, Germany

来源：

NATURE COMMUNICATIONS | 2022年 / 13卷 / 01期

关键词：

VALIDATION; MODELS;

D O I：

10.1038/s41467-022-29838-9

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：4

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