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...

Descripció completa

Dades bibliogràfiques

Autors principals:	Yuzhen Zhang, Jun Ma, Shunlin Liang, Xisheng Li, Jindong Liu
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2022-12-01
Col·lecció:	GIScience & Remote Sensing
Matèries:	stacking forest biomass ensemble algorithm remote sensing
Accés en línia:	http://dx.doi.org/10.1080/15481603.2021.2023842
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!