The Analysis of Vegetation Spectra Based on Multi-Band Lidar
FENG Ming-bo1,2, NIU Zheng1*, SUN Gang1
1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：Multi-band Lidar is a new means to obtain spectra. It is different from the traditional spectrometer which can only get spectra in the two-dimensional level. The multi-band Lidar based on the super-continuum spectrum laser light, uses the penetrability and high concentration of laser and gets the spectra of vegetation in vertical direction, relying on the grating instrument system. With it the spectral distribution of vegetation in the three-dimensional level can be obtained. In this paper, 32-band Lidar is applied. Firstly, the spectra obtained with 32-band Lidar and ASD spectrometer in a darkroom are compared, which proves that they have the same shape, accurately indicating the reflection characteristics of vegetation from 458 to 865 nm. Then with the analysis of the correlations of spectral index and chlorophyll content, it is found that the fitting relations between the spectral indices and chlorophyll content acquire nice effect and there is highly significant correlation between the Modified Simple Ratio (MSR) based on multi-band Lidar spectra and chlorophyll content, the determination coefficient (R2) is 0.780 2 and the RMSE is only 0.508 1. Finally, with multi-band Lidar, the spectra in the vertical direction and the three-dimensional point cloud distribution of spectra are obtained via multiple scanning. Based on the optimal fitting equation between MSR and chlorophyll content, three-dimensional distribution of chlorophyll content is gotten.
丰明博，牛 铮，孙 刚. 多波段激光雷达植被光谱分析[J]. 光谱学与光谱分析, 2017, 37(06): 1809-1813.
FENG Ming-bo, NIU Zheng, SUN Gang. The Analysis of Vegetation Spectra Based on Multi-Band Lidar. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(06): 1809-1813.
[1] Hakala T, Suomalainen J, Kaasalainen S, et al. Optics Express, 2012, 20(7): 7119.
[2] Puttonen E, Suomalainen J, Hakala T, et al. Forest Ecology and Management, 2010, 260(10): 1843.
[3] Kaasalainen S, Suomalainen J, Hakala T, et al. Active Hyperspectral LIDAR Methods for Object Classification. Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on, 2010. 5594863.
[4] WU Chao-yang, NIU Zheng(吴朝阳，牛 铮). Chinese Bulletin of Botany(植物学通报), 2008, 25(6): 714.
[5] Rondeaux G, Steven M, Baret F. Remote Sensing of Environment, 1996, 55(2): 95.
[6] Gitelson A, Merzlyak M N. Journal of Plant Physiology, 1994, 143(3)：286.
[7] WANG Jian-yu, HONG Guang-lie(王建宇, 洪光烈). Laser & Infrared(激光与红外), 2006, 36(9): 742.
[8] Coren F, Sterzai P. International Journal of Remote Sensing, 2006, 27(15): 3097.
[9] Wagner W, Ullrich A, Ducic V, et al. ISPRS Journal of Photogrammetry and Remote Sensing, 2006, 60(2): 100.
[10] LIU Qing-wang, LI Zeng-yuan, CHEN Er-xue, et al(刘清旺，李增元，陈尔学，等). SCIENCE CHINA Earth Sciences(中国科学：地球科学), 2012, 41(11): 1670.
[11] Sun G, Ranson K J. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(6): 2617.
[12] Ni-Meister W, Jupp D L B, Dubayah R. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(9): 1943.
[13] Kotchenova S Y, Shabanov N V, Knyazikhin Y, et al. Journal of Geophysical Research, 2003, 108(15): 4484.
[14] Gamon J, Serrano L, Surfus J. Oecologia, 1997, 112(4): 492.
