Ultra-High Spatial Resolution Mapping of Urban Forest Canopy Height With Multimodal Remote Sensing Data and Deep Learning Method

Ultra-High Spatial Resolution Mapping of Urban Forest Canopy Height With Multimodal Remote Sensing Data and Deep Learning Method

Urban forest canopy height is an important indicator for urban carbon storage, vegetation ecosystems services, and devising effective forest management strategies to combat global climate change. Although both spaceborne or airborne light detection and ranging could offer forest canopy height inform...

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Bibliographic Details
Main Authors: Kun Xiao, Xiaoyang Zhao, Ying Ding, Chen Huang, Jueyu Lin, Yuxuan Mai, Ying Sun, Qinchuan Xin
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning
digital elevation model (DEM)
forest canopy height
remote sensing
ultra-high resolution
Online Access:https://ieeexplore.ieee.org/document/10902494/
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