Improved Object-Based Estimation of Forest Aboveground Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region

Improved Object-Based Estimation of Forest Aboveground Biomass by Integrating LiDAR Data from GEDI and ICESat-2 with Multi-Sensor Images in a Heterogeneous Mountainous Region

Accurate and effective mapping of forest aboveground biomass (AGB) in heterogeneous mountainous regions is a huge challenge but an urgent demand for resource managements and carbon storage monitoring. Conventional studies have related the plot-measured or LiDAR-based biomass to remote sensing data u...

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Bibliographic Details
Main Authors: Lin Chen, Chunying Ren, Guangdao Bao, Bai Zhang, Zongming Wang, Mingyue Liu, Weidong Man, Jiafu Liu
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
GEDI LiDAR
ICESAT-2 LiDAR
object-based approach
heterogeneous mountainous forests
forest aboveground biomass
Online Access:https://www.mdpi.com/2072-4292/14/12/2743

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https://www.mdpi.com/2072-4292/14/12/2743

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