Estimation of forest aboveground biomass by using mixed-effects model

Author:

Feng Haoning1,Chen Qi2,Hu Yueming12,Du Zhiguo3,Lin Guantu1,Wang Changwei14,Huang Youju5

Affiliation:

1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou, China

2. Department of Geography, University of Hawai‘i at Mānoa, Honolulu, USA

3. College of Mathematics and Information, South China Agricultural University, Guangzhou, China

4. Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou, China

5. Remote Sensing Monitoring Center, Guangxi Zhuang Automomous Region Institute of Natural Resources Remote Sensing, Nanning, China

Funder

Promoting Economic Development of Guangdong Province Special Foundation

Science and Technology Major Project of Guangdong Province of China

Guangxi Innovative Development Grand Program

the Promoting Economic Development of Guangdong Province Special Foundation

the Guangxi Innovative Development Grand Program

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Reference63 articles.

1. Forest biomass estimation over regional scales using multisource data

2. Random effects structure for confirmatory hypothesis testing: Keep it maximal

3. Bates, Douglas M., Reinhold Kliegl, Shravan Vasishth, and Harald Baayen. 2018. “Parsimonious mixed models.” arXiv:1506.04967v2 [stat.ME].

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