A stacking ensemble algorithm for improving the biases of forest aboveground biomass estimations from multiple remotely sensed datasets

Accurately quantifying the aboveground biomass (AGB) of forests is crucial for understanding global change-related issues such as the carbon cycle and climate change. Many studies have estimated AGB from multiple remotely sensed datasets using various algorithms, but substantial uncertainties remain...

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Автори:	Yuzhen Zhang, Jun Ma, Shunlin Liang, Xisheng Li, Jindong Liu
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Taylor & Francis Group 2022-12-01
Серія:	GIScience & Remote Sensing
Предмети:	stacking forest biomass ensemble algorithm remote sensing
Онлайн доступ:	http://dx.doi.org/10.1080/15481603.2021.2023842
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