Estimation of National Forest Aboveground Biomass from Multi-Source Remotely Sensed Dataset with Machine Learning Algorithms in China

Estimation of National Forest Aboveground Biomass from Multi-Source Remotely Sensed Dataset with Machine Learning Algorithms in China

Forests are the largest terrestrial ecosystem carbon pool and provide the most important nature-based climate mitigation pathway. Compared with belowground biomass (BGB) and soil carbon, aboveground biomass (AGB) is more sensitive to human disturbance and climate change. Therefore, accurate forest A...

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Bibliografische gegevens
Hoofdauteurs: Zhi Tang, Xiaosheng Xia, Yonghua Huang, Yan Lu, Zhongyang Guo
Formaat: Artikel
Taal:English
Gepubliceerd in: MDPI AG 2022-10-01
Reeks:Remote Sensing
Onderwerpen:
forest
aboveground biomass
machine learning
multi-source dataset
China
Online toegang:https://www.mdpi.com/2072-4292/14/21/5487

Internet

https://www.mdpi.com/2072-4292/14/21/5487

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