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.
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%0 Journal Article
%1 journals/remotesensing/ChenRBZWLML22
%A Chen, Lin
%A Ren, Chunying
%A Bao, Guangdao
%A Zhang, Bai
%A Wang, Zongming
%A Liu, Mingyue
%A Man, Weidong
%A Liu, Jiafu
%D 2022
%J Remote. Sens.
%K dblp
%N 12
%P 2743
%T 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.
%U http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing14.html#ChenRBZWLML22
%V 14
@article{journals/remotesensing/ChenRBZWLML22,
added-at = {2023-09-30T00:00:00.000+0200},
author = {Chen, Lin and Ren, Chunying and Bao, Guangdao and Zhang, Bai and Wang, Zongming and Liu, Mingyue and Man, Weidong and Liu, Jiafu},
biburl = {https://www.bibsonomy.org/bibtex/29dbbc5278ec38af27d83e1bc7bbe1b8c/dblp},
ee = {https://doi.org/10.3390/rs14122743},
interhash = {50fa6d3d95865e3a44ffa35e26d97e30},
intrahash = {9dbbc5278ec38af27d83e1bc7bbe1b8c},
journal = {Remote. Sens.},
keywords = {dblp},
number = 12,
pages = 2743,
timestamp = {2024-04-08T11:41:56.000+0200},
title = {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.},
url = {http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing14.html#ChenRBZWLML22},
volume = 14,
year = 2022
}
