Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR

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Original language	English
Article number	113968
Journal	Remote Sensing of Environment
Volume	302
Number of pages	21
ISSN	0034-4257
DOIs	https://doi.org/10.1016/j.rse.2023.113968
Publication status	Published - 2024

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@article{2b2321b312c54015a296bbfbd50e2e9b,

title = "Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR",

author = "Stefan Oehmcke and Lei Li and Katerina Trepekli and Revenga, {Jaime C.} and Thomas Nord-Larsen and Fabian Gieseke and Christian Igel",

year = "2024",

doi = "10.1016/j.rse.2023.113968",

language = "English",

volume = "302",

journal = "Remote Sensing of Environment",

issn = "0034-4257",

publisher = "Elsevier",

}

TY - JOUR

T1 - Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR

AU - Oehmcke, Stefan

AU - Li, Lei

AU - Trepekli, Katerina

AU - Revenga, Jaime C.

AU - Nord-Larsen, Thomas

AU - Gieseke, Fabian

AU - Igel, Christian

PY - 2024

Y1 - 2024

U2 - 10.1016/j.rse.2023.113968

DO - 10.1016/j.rse.2023.113968

M3 - Journal article

VL - 302

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

M1 - 113968

ER -