Improved Object-Based Mapping of Aboveground Biomass Using Geographic Stratification with GEDI Data and Multi-Sensor Imagery

Improved Object-Based Mapping of Aboveground Biomass Using Geographic Stratification with GEDI Data and Multi-Sensor Imagery

Aboveground biomass (AGB) mapping using spaceborne LiDAR data and multi-sensor images is essential for efficient carbon monitoring and climate change mitigation actions in heterogeneous forests. The optimal predictors of remote sensing-based AGB vary greatly with geographic stratification, such as t...

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Bibliographic Details
Main Authors: Lin Chen, Chunying Ren, Bai Zhang, Zongming Wang, Weidong Man, Mingyue Liu
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Remote Sensing
Subjects:
stratification by forest type
GEDI LiDAR
multi-sensor images
object-based mapping
random forests
forest aboveground biomass
Online Access:https://www.mdpi.com/2072-4292/15/10/2625

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https://www.mdpi.com/2072-4292/15/10/2625

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