Evaluation of machine learning methods and multi-source remote sensing data combinations to construct forest above-ground biomass models

Evaluation of machine learning methods and multi-source remote sensing data combinations to construct forest above-ground biomass models

ABSTRACTRapid and accurate estimation of forest biomass are essential to drive sustainable management of forests. Field-based measurements of forest above-ground biomass (AGB) can be costly and difficult to conduct. Multi-source remote sensing data offers the potential to improve the accuracy of mod...

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Hlavní autoři: Xingguang Yan, Jing Li, Andrew R. Smith, Di Yang, Tianyue Ma, YiTing Su, Jiahao Shao
Médium: Článek
Jazyk:English
Vydáno: Taylor & Francis Group 2023-12-01
Edice:International Journal of Digital Earth
Témata:
Google Earth Engine
mixed species
landscape
satellite
spectral
waveband
On-line přístup:https://www.tandfonline.com/doi/10.1080/17538947.2023.2270459

Internet

https://www.tandfonline.com/doi/10.1080/17538947.2023.2270459

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