Pei-Lun HU, Yu-Wei CHEN, Chang-Hui JIANG, Qi-Nan LIN, Wei LI, Jian-Bo QI, Lin-Feng YU, Hui SHAO, Hua-Guo HUANG. Spectral observation and classification of typical tree species leaves based on indoor hyperspectral lidar[J]. Journal of Infrared and Millimeter Waves, 2020, 39(3): 372.
参考文献
[1]LiZeng-Yuan, LiuQing-Wang, PangYong. Research progress of forest parameter inversion of LiDAR [J]. ,,, 2016, 20(5): 1138-1150.
[2]ChenShu-Peng, TongQing-Xi, GuoHua-Dong. Mechanism of remote sensing information [M]. Beijing: Science press (陈述彭,,,. 1998.
[3]Fang-Hong-Liang, TianQing-Jiu. Research review of hyperspectral remote sensing in vegetation monitoring [J]. ,. 1998, 13(1): 62-69.
[4]MartinM E, NewmanS D, AberJ D, et al. Determining forest species composition using high spectral resolution remote sensing data[J]. . 1998, 65(3): 249-254.
[5]HakalaT, NevalainenO, KaasalainenS, et al. Hyperspectral lidar time series of pine canopy physiological parameters[J]. . 2014, 11(10): 15019-15035.
[6]JiaS, ShiS, WeiG, et al. Evaluation of hyperspectral LiDAR for monitoring rice leaf nitrogen by comparison with multispectral LiDAR and passive spectrometer[J]. . 2017, 7: 40362.
[7]KulawardhanaR W, PopescuS C, FeaginR A. Fusion of lidar and multispectral data to quantify salt marsh carbon stocks[J]. . 2014, 154: 345-357.
[8]KaasalainenS, NevalainenO, HakalaT, et al. Incidence Angle Dependency of Leaf Vegetation Indices from Hyperspectral Lidar Measurements[J]. . 2016, 2016(2): 75-84.
[9]ShuaiG, ZhengN, GangS, et al. Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm[J]. . 2015, 12(9): 1978-1982.
[10]WingB M, RitchieM W, BostonK, et al. Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest[J]. . 2012, 124: 730-741.
[11]TanS, NarayananR M. Design and performance of a multiwavelength airborne polarimetric lidar for vegetation remote sensing.[J]. . 2004, 43(11): 2360-2368.
[12]MorsdorfF, NicholC, MalthusT, et al. Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling[J]. . 2009, 113(10 ): 2152-2163.
[13]ChenY, JiangC, HyyppäJ, et al. Feasibility Study of Ore Classification Using Active Hyperspectral LiDAR[J]. . 2018(99): 1-5.
[14]WangL, GangS, ZhengN, et al. Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system[J]. . 2014, 5(8): 693-702.
[15]JiangC, ChenY, WuH, et al. Study of a High Spectral Resolution Hyperspectral LiDAR in Vegetation Red Edge Parameters Extraction[J]. . 2019, 11(17): 2007.
[16]ChenY, JiangC, HyyppäJ, et al. Feasibility Study of Ore Classification Using Active Hyperspectral LiDAR[J]. . 2018, 15(11): 1-5.
胡佩纶, 陈育伟, 蒋长辉, 林起楠, 李伟, 漆建波, 俞琳锋, 邵慧, 黄华国. 基于室内高光谱激光雷达的典型树种叶片光谱观测和分类[J]. 红外与毫米波学报, 2020, 39(3): 372. Pei-Lun HU, Yu-Wei CHEN, Chang-Hui JIANG, Qi-Nan LIN, Wei LI, Jian-Bo QI, Lin-Feng YU, Hui SHAO, Hua-Guo HUANG. Spectral observation and classification of typical tree species leaves based on indoor hyperspectral lidar[J]. Journal of Infrared and Millimeter Waves, 2020, 39(3): 372.