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Neural network guided interpolation for mapping canopy height of China's forests by integrating GEDI and ICESat-2 data 期刊论文
REMOTE SENSING OF ENVIRONMENT, 2022, 卷号: 269
作者:  Liu, Xiaoqiang;  Su, Yanjun;  Hu, Tianyu;  Yang, Qiuli;  Liu, Bingbing;  Deng, Yufei;  Tang, Hao;  Tang, Zhiyao;  Fang, Jingyun;  Guo, Qinghua
Adobe PDF(6152Kb)  |  收藏  |  浏览/下载：33/0  |  提交时间：2024/03/07
Forest canopy height  GEDI  ICESat-2 ATLAS  Lidar  Spatial interpolation  Deep neural network  
Mapping the Global Mangrove Forest Aboveground Biomass Using Multisource Remote Sensing Data 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 10
作者:  Hu, Tianyu;  Zhang, YingYing;  Su, Yanjun;  Zheng, Yi;  Lin, Guanghui;  Guo, Qinghua
Adobe PDF(3278Kb)  |  收藏  |  浏览/下载：89/0  |  提交时间：2022/03/01
mangrove  LiDAR  random forest  GLAS  aboveground biomass  
A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data 期刊论文
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2019, 卷号: 78, 页码: 25-38
作者:  Hu, Tianyu;  Ma, Qin;  Su, Yanjun;  Battles, John J.;  Collins, Brandon M.;  Stephens, Scott L.;  Kelly, Maggi;  Guo, Qinghua
Adobe PDF(15930Kb)  |  收藏  |  浏览/下载：83/0  |  提交时间：2022/01/06
Fire severity  Fire type  Tree canopy  Airborne LiDAR  Profile area change  
Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data 期刊论文
REMOTE SENSING OF ENVIRONMENT, 2016, 卷号: 173, 页码: 187-199
作者:  Su, Yanjun;  Guo, Qinghua;  Xue, Baolin;  Hu, Tianyu;  Alvarez, Otto;  Tao, Shengli;  Fang, Jingyun
Adobe PDF(4355Kb)  |  收藏  |  浏览/下载：77/0  |  提交时间：2022/07/08
Forest aboveground biomass  GIAS/ICESat  Lidar  Ground inventory  China  
Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data 期刊论文
REMOTE SENSING, 2016, 卷号: 8, 期号: 7
作者:  Hu, Tianyu;  Su, Yanjun;  Xue, Baolin;  Liu, Jin;  Zhao, Xiaoqian;  Fang, Jingyun;  Guo, Qinghua
Adobe PDF(8623Kb)  |  收藏  |  浏览/下载：65/0  |  提交时间：2022/07/08
global  forest  aboveground biomass  remote sensing  LiDAR