Estimating the grassland aboveground biomass in the Three-River Headwater Region of China using machine learning and Bayesian model averaging-Reference-Cited by-同舟云学术

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Estimating the grassland aboveground biomass in the Three-River Headwater Region of China using machine learning and Bayesian model averaging

Published:2021-10-26 Issue:11 Volume:16 Page:114020
ISSN:1748-9326
Container-title:Environmental Research Letters
language:
Short-container-title:Environ. Res. Lett.

Author:

Zeng Na,Ren Xiaoli,He Honglin,Zhang Li^ORCID,Li Pan,Niu Zhongen

Funder

the Research Development Fund Project of Zhejiang Agriculture and Forestry University School

the National Key Research and development program of China

National Natural Science Foundation of China

Publisher

IOP Publishing

Subject

Public Health, Environmental and Occupational Health,General Environmental Science,Renewable Energy, Sustainability and the Environment

Link

https://iopscience.iop.org/article/10.1088/1748-9326/ac2e85/pdf

Reference80 articles.

1. Grassland degradation in China: methods of monitoring, management and restoration;Akiyama;Japan. Soc. Grassland Sci.,2007

2. Modeling managed grassland biomass estimation by using multitemporal remote sensing data—a machine learning approach;Ali;IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.,2017

3. Aboveground biomass assessment in Colombia: a remote sensing approach;Anaya;For. Ecol. Manage.,2009

4. Twentieth century redistribution in climatic drivers of global tree growth;Babst;Sci. Adv.,2019

5. Random forest in remote sensing: a review of applications and future directions;Belgiu;ISPRS J. Photogram. Remote Sens.,2016

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