Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass in heterogenous landscapes
Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest aboveground biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering – that is, excluding re...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2022-12-01
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Series: | GIScience & Remote Sensing |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/15481603.2022.2103069 |