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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：79/0  |  提交时间：2022/01/06
Fire severity  Fire type  Tree canopy  Airborne LiDAR  Profile area change  
Impact of Error in Lidar-Derived Canopy Height and Canopy Base Height on Modeled Wildfire Behavior in the Sierra Nevada, California, USA 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 1
作者:  Kelly, Maggi;  Su, Yanjun;  Di Tommaso, Stefania;  Fry, Danny L.;  Collins, Brandon M.;  Stephens, Scott L.;  Guo, Qinghua
Adobe PDF(4708Kb)  |  收藏  |  浏览/下载：74/0  |  提交时间：2022/02/25
wildfire burn probability  crown fire  forest fuels  Sierra Nevada  Lidar  error  
Evaluating the uncertainty of Landsat-derived vegetation indices in quantifying forest fuel treatments using bi-temporal LiDAR data 期刊论文
ECOLOGICAL INDICATORS, 2018, 卷号: 95, 页码: 298-310
作者:  Ma, Qin;  Su, Yanjun;  Luo, Laiping;  Li, Le;  Kelly, Maggi;  Guo, Qinghua
Adobe PDF(3094Kb)  |  收藏  |  浏览/下载：88/0  |  提交时间：2022/02/25
Forest fuel treatment  Vegetation index  Aboveground biomass  LiDAR  
Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery 期刊论文
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2017, 卷号: 10, 期号: 3, 页码: 307-323
作者:  Su, Yanjun;  Ma, Qin;  Guo, Qinghua
Adobe PDF(4133Kb)  |  收藏  |  浏览/下载：61/0  |  提交时间：2022/03/28
Tree height  Sierra Nevada  LiDAR  integration  fine resolution  
Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 卷号: 37, 期号: 14, 页码: 3322-3345
作者:  Su, Yanjun;  Guo, Qinghua;  Collins, Brandon M.;  Fry, Danny L.;  Hu, Tianyu;  Kelly, Maggi
Adobe PDF(4413Kb)  |  收藏  |  浏览/下载：78/0  |  提交时间：2022/07/08