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Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects 期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2021, 卷号: 171, 页码: 202-223
Authors:  Jin, Shichao;  Sun, Xiliang;  Wu, Fangfang;  Su, Yanjun;  Li, Yumei;  Song, Shiling;  Xu, Kexin;  Ma, Qin;  Baret, Frederic;  Jiang, Dong;  Ding, Yanfeng;  Guo, Qinghua
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Lidar  Traits  Phenomics  Breeding  Management  Multi-omits  
Lidar Boosts 3D Ecological Observations and Modelings: A Review and Perspective 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2021, 卷号: 9, 期号: 1, 页码: 232-257
Authors:  Guo, Qinghua;  Su, Yanjun;  Hu, Tianyu;  Guan, Hongcan;  Jin, Shichao;  Zhang, Jing;  Zhao, Xiaoxia;  Xu, Kexin;  Wei, Dengjie;  Kelly, Maggi;  Coops, Nicholas C.
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Laser radar  Vegetation mapping  Three-dimensional displays  Surface emitting lasers  Optical sensors  Ecosystems  Optical reflection  
Separating the Structural Components of Maize for Field Phenotyping Using Terrestrial LiDAR Data and Deep Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 卷号: 58, 期号: 4, 页码: 2644-2658
Authors:  Jin, Shichao;  Su, Yanjun;  Gao, Shang;  Wu, Fangfang;  Ma, Qin;  Xu, Kexin;  Hu, Tianyu;  Liu, Jin;  Pang, Shuxin;  Guan, Hongcan;  Zhang, Jing;  Guo, Qinghua
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Classification  deep learning  LiDAR  phenotype  segmentation  structural components  
Non-destructive estimation of field maize biomass using terrestrial lidar: an evaluation from plot level to individual leaf level 期刊论文
PLANT METHODS, 2020, 卷号: 16, 期号: 1
Authors:  Jin, Shichao;  Su, Yanjun;  Song, Shilin;  Xu, Kexin;  Hu, Tianyu;  Yang, Qiuli;  Wu, Fangfang;  Xu, Guangcai;  Ma, Qin;  Guan, Hongcan;  Pang, Shuxin;  Li, Yumei;  Guo, Qinghua
Adobe PDF(4774Kb)  |  Favorite  |  View/Download:83/0  |  Submit date:2022/03/01
Biomass  Phenotype  Machine learning  Terrestrial lidar  Precision agriculture  
Application of deep learning in ecological resource research: Theories, methods, and challenges 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2020, 卷号: 63, 期号: 10, 页码: 1457-1474
Authors:  Guo, Qinghua;  Jin, Shichao;  Li, Min;  Yang, Qiuli;  Xu, Kexin;  Ju, Yuanzhen;  Zhang, Jing;  Xuan, Jing;  Liu, Jin;  Su, Yanjun;  Xu, Qiang;  Liu, Yu
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Ecological resources  Deep learning  Neural network  Big data  Theory and tools  Application and challenge  
Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data 期刊论文
ECOLOGICAL INDICATORS, 2020, 卷号: 108
Authors:  Xu, Kexin;  Su, Yanjun;  Liu, Jin;  Hu, Tianyu;  Jin, Shichao;  Ma, Qin;  Zhai, Qiuping;  Wang, Rui;  Zhang, Jing;  Li, Yumei;  Liu, Hon An;  Guo, Qinghua
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Aboveground biomass (AGB)  Degraded grassland  Machine learning  Northern agro-pastoral ecotone  Terrestrial laser scanning (TLS)