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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：81/0  |  提交时间：2022/01/06
Fire severity  Fire type  Tree canopy  Airborne LiDAR  Profile area change  
An Object-Based Strategy for Improving the Accuracy of Spatiotemporal Satellite Imagery Fusion for Vegetation-Mapping Applications 期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 24
作者:  Guan, Hongcan;  Su, Yanjun;  Hu, Tianyu;  Chen, Jin;  Guo, Qinghua
Adobe PDF(10441Kb)  |  收藏  |  浏览/下载：93/0  |  提交时间：2022/01/06
spatiotemporal data fusion  object-based framework  similar pixel  vegetation mapping  
Evaluating the Performance of Sentinel-2, Landsat 8 and Pleiades-1 in Mapping Mangrove Extent and Species 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 9
作者:  Wang, Dezhi;  Wan, Bo;  Qiu, Penghua;  Su, Yanjun;  Guo, Qinghua;  Wang, Run;  Sun, Fei;  Wu, Xincai
Adobe PDF(5307Kb)  |  收藏  |  浏览/下载：95/0  |  提交时间：2022/02/25
mangroves  species  Sentinel-2  Landsat 8  Pleiades-1  random forest  
The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data 期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 8
作者:  Jin, Shichao;  Su, Yanjun;  Gao, Shang;  Hu, Tianyu;  Liu, Jin;  Guo, Qinghua
Adobe PDF(4477Kb)  |  收藏  |  浏览/下载：73/0  |  提交时间：2022/02/25
canopy height  Random Forest  LiDAR  multi-source  vegetation type  location  scale  
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  
An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China 期刊论文
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 卷号: 38, 期号: 8-10, 页码: 2954-2972
作者:  Guo, Qinghua;  Su, Yanjun;  Hu, Tianyu;  Zhao, Xiaoqian;  Wu, Fangfang;  Li, Yumei;  Liu, Jin;  Chen, Linhai;  Xu, Guangcai;  Lin, Guanghui;  Zheng, Yi;  Lin, Yiqiong;  Mi, Xiangcheng;  Fei, Lin;  Wang, Xugao
Adobe PDF(2839Kb)  |  收藏  |  浏览/下载：82/0  |  提交时间：2022/03/28
Emerging Stress and Relative Resiliency of Giant Sequoia Groves Experiencing Multiyear Dry Periods in a Warming Climate 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 2017, 卷号: 122, 期号: 11, 页码: 3063-3075
作者:  Su, Yanjun;  Bales, Roger C.;  Ma, Qin;  Nydick, Koren;  Ray, Ram L.;  Li, Wenkai;  Guo, Qinghua
Adobe PDF(1445Kb)  |  收藏  |  浏览/下载：73/0  |  提交时间：2022/03/28
Giant Sequoia  Climate change  Drought  Vulnerability  Remote senisng  
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
SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery 期刊论文
REMOTE SENSING, 2015, 卷号: 7, 期号: 9, 页码: 11202-11225
作者:  Su, Yanjun;  Guo, Qinghua;  Ma, Qin;  Li, Wenkai
Adobe PDF(3624Kb)  |  收藏  |  浏览/下载：62/0  |  提交时间：2022/09/13
SRTM  DEM  LiDAR  ICESat  GLAS  vegetation  mountain  canopy height  canopy cover