Wenkai Li
Zitiert von
Zitiert von
A new method for segmenting individual trees from the lidar point cloud
W Li, Q Guo, MK Jakubowski, M Kelly
Photogrammetric Engineering & Remote Sensing 78 (1), 75-84, 2012
Effects of topographic variability and lidar sampling density on several DEM interpolation methods
Q Guo, W Li, H Yu, O Alvarez
Photogrammetric Engineering & Remote Sensing 76 (6), 701-712, 2010
Delineating Individual Trees from Lidar Data: A Comparison of Vector-and Raster-based Segmentation Approaches
MK Jakubowski, W Li, Q Guo, M Kelly
Remote Sensing 5 (9), 4163-4186, 2013
A positive and unlabeled learning algorithm for one-class classification of remote-sensing data
W Li, Q Guo, C Elkan
IEEE Transactions on Geoscience and Remote Sensing 49 (2), 717-725, 2011
Analysis of the adverse health effects of PM2. 5 from 2001 to 2017 in China and the role of urbanization in aggravating the health burden
X Lu, C Lin, W Li, Y Chen, Y Huang, JCH Fung, AKH Lau
Science of The Total Environment 652, 683-695, 2019
Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories
S Tao, F Wu, Q Guo, Y Wang, W Li, B Xue, X Hu, P Li, D Tian, C Li, H Yao, ...
ISPRS Journal of Photogrammetry and Remote Sensing 110, 66-76, 2015
A bottom-up approach to segment individual deciduous trees using leaf-off lidar point cloud data
X Lu, Q Guo, W Li, J Flanagan
ISPRS Journal of Photogrammetry and Remote Sensing 94, 1-12, 2014
Deep learning: individual maize segmentation from terrestrial lidar data using faster R-CNN and regional growth algorithms
S Jin, Y Su, S Gao, F Wu, T Hu, J Liu, W Li, D Wang, S Chen, Y Jiang, ...
Frontiers in plant science 9, 866, 2018
Can we model the probability of presence of species without absence data?
W Li, Q Guo, C Elkan
Ecography 34 (6), 1096-1105, 2011
How to assess the prediction accuracy of species presence–absence models without absence data?
W Li, Q Guo
Ecography 36 (7), 788-799, 2013
A maximum entropy approach to one-class classification of remote sensing imagery
W Li, Q Guo
International Journal of Remote Sensing 31 (8), 2227-2235, 2010
Airborne Lidar-derived volume metrics for aboveground biomass estimation: A comparative assessment for conifer stands
S Tao, Q Guo, L Li, B Xue, M Kelly, W Li, G Xu, Y Su
Agricultural and Forest Meteorology 198, 24-32, 2014
A New Accuracy Assessment Method for One-Class Remote Sensing Classification
W Li, Q Guo
IEEE Transactions on Geoscience and Remote Sensing 52 (8), 4621 - 4632, 2014
SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery
Y Su, Q Guo, Q Ma, W Li
Remote Sensing 7 (9), 11202-11225, 2015
Land-use decision support in brownfield redevelopment for urban renewal based on crowdsourced data and a presence-and-background learning (PBL) method
Y Liu, AX Zhu, J Wang, W Li, G Hu, Y Hu
Land use policy 88, 104188, 2019
One-class remote sensing classification: one-class vs. binary classifiers
X Deng, W Li, X Liu, Q Guo, S Newsam
International Journal of Remote Sensing 39 (6), 1890-1910, 2018
郭庆华, 刘瑾, 陶胜利, 薛宝林, 李乐, 徐光彩, 李文楷, 吴芳芳, 李玉美, ...
科学通报 (中文版) 59 (6), 459-478, 2014
VBRT: A novel voxel-based radiative transfer model for heterogeneous three-dimensional forest scenes
W Li, Q Guo, S Tao, Y Su
Remote Sensing of Environment 206, 318-335, 2018
One-Class Classification of Airborne LiDAR Data in Urban Areas Using a Presence and Background Learning Algorithm
Z Ao, Y Su, W Li, Q Guo, J Zhang
Remote Sensing 9 (10), 1001, 2017
A marker-free method for registering multi-scan terrestrial laser scanning data in forest environments
H Guan, Y Su, X Sun, G Xu, W Li, Q Ma, X Wu, J Wu, L Liu, Q Guo
ISPRS Journal of Photogrammetry and Remote Sensing 166, 82-94, 2020
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