| Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data Y Su, Q Guo, B Xue, T Hu, O Alvarez, S Tao, J Fang Remote Sensing of Environment 173, 187-199, 2016 | 222 | 2016 |
| An integrated UAV-borne lidar system for 3D habitat mapping in three forest ecosystems across China Q Guo, Y Su, T Hu, X Zhao, F Wu, Y Li, J Liu, L Chen, G Xu, G Lin, ... International journal of remote sensing 38 (8-10), 2954-2972, 2017 | 170 | 2017 |
| Mapping global forest aboveground biomass with spaceborne LiDAR, optical imagery, and forest inventory data T Hu, Y Su, B Xue, J Liu, X Zhao, J Fang, Q Guo Remote Sensing 8 (7), 565, 2016 | 157 | 2016 |
| 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 | 144 | 2018 |
| Stem–leaf segmentation and phenotypic trait extraction of individual maize using terrestrial LiDAR data S Jin, Y Su, F Wu, S Pang, S Gao, T Hu, J Liu, Q Guo IEEE Transactions on Geoscience and Remote Sensing 57 (3), 1336-1346, 2018 | 129 | 2018 |
| Development and performance evaluation of a very low-cost UAV-LiDAR system for forestry applications T Hu, X Sun, Y Su, H Guan, Q Sun, M Kelly, Q Guo Remote Sensing 13 (1), 77, 2020 | 126 | 2020 |
| Neural network guided interpolation for mapping canopy height of China's forests by integrating GEDI and ICESat-2 data X Liu, Y Su, T Hu, Q Yang, B Liu, Y Deng, H Tang, Z Tang, J Fang, Q Guo Remote Sensing of Environment 269, 112844, 2022 | 119 | 2022 |
| UAV-lidar aids automatic intelligent powerline inspection H Guan, X Sun, Y Su, T Hu, H Wang, H Wang, C Peng, Q Guo International Journal of Electrical Power & Energy Systems 130, 106987, 2021 | 99 | 2021 |
| An updated vegetation map of China (1: 1000000) Y Su, Q Guo, T Hu, H Guan, S Jin, S An, X Chen, K Guo, Z Hao, Y Hu, ... Science Bulletin 65 (13), 1125-1136, 2020 | 95 | 2020 |
| Lidar boosts 3D ecological observations and modelings: A review and perspective Q Guo, Y Su, T Hu, H Guan, S Jin, J Zhang, X Zhao, K Xu, D Wei, M Kelly, ... IEEE Geoscience and Remote Sensing Magazine 9 (1), 232-257, 2020 | 94 | 2020 |
| Mapping the global mangrove forest aboveground biomass using multisource remote sensing data T Hu, YY Zhang, Y Su, Y Zheng, G Lin, Q Guo Remote sensing 12 (10), 1690, 2020 | 80 | 2020 |
| Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data K Xu, Y Su, J Liu, T Hu, S Jin, Q Ma, Q Zhai, R Wang, J Zhang, Y Li, H Liu, ... Ecological Indicators 108, 105747, 2020 | 80 | 2020 |
| Separating the structural components of maize for field phenotyping using terrestrial LiDAR data and deep convolutional neural networks S Jin, Y Su, S Gao, F Wu, Q Ma, K Xu, T Hu, J Liu, S Pang, H Guan, ... IEEE Transactions on Geoscience and Remote Sensing 58 (4), 2644-2658, 2019 | 74 | 2019 |
| Drivers of lightning-and human-caused fire regimes in the Great Xing’an Mountains T Hu, G Zhou Forest Ecology and Management 329, 49-58, 2014 | 57 | 2014 |
| Non-destructive estimation of field maize biomass using terrestrial lidar: an evaluation from plot level to individual leaf level S Jin, Y Su, S Song, K Xu, T Hu, Q Yang, F Wu, G Xu, Q Ma, H Guan, ... Plant Methods 16, 1-19, 2020 | 54 | 2020 |
| The influence of vegetation characteristics on individual tree segmentation methods with airborne LiDAR data Q Yang, Y Su, S Jin, M Kelly, T Hu, Q Ma, Y Li, S Song, J Zhang, G Xu, ... Remote Sensing 11 (23), 2880, 2019 | 48 | 2019 |
| LiDAR principles, processing and applications in forest ecology Q Guo, Y Su, T Hu Academic Press, 2023 | 47 | 2023 |
| A global corrected SRTM DEM product for vegetated areas X Zhao, Y Su, T Hu, L Chen, S Gao, R Wang, S Jin, Q Guo Remote Sensing Letters 9 (4), 393-402, 2018 | 47 | 2018 |
| The development and evaluation of a backpack LiDAR system for accurate and efficient forest inventory Y Su, Q Guo, S Jin, H Guan, X Sun, Q Ma, T Hu, R Wang, Y Li IEEE Geoscience and Remote Sensing Letters 18 (9), 1660-1664, 2020 | 45 | 2020 |
| A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data T Hu, Q Ma, Y Su, JJ Battles, BM Collins, SL Stephens, M Kelly, Q Guo International Journal of Applied Earth Observation and Geoinformation 78, 25-38, 2019 | 42 | 2019 |
Yanjun SuProfessor, Institute of Botany, Chinese Academy of Sciences在 ucmerced.edu 的电子邮件经过验证
