Abstract：The accurate inversion of leaf area index (LAI) in canopy is very important for guiding crop management and assessing crop yield. Sixty samples belonging to corn in four different areas of Jilin City were scanned by ASD field pro3 and LAI-2000 for optical data and LAI. A new vegetation index, the normalized composite Vegetation index (NCVI), containing the factor of canopy water content, is proposed in the present paper for a better quantitative estimation of LAI than with the remotely sensed normalized difference vegetation index (NDVI), especially in the arid and semi-arid areas. A model was built for inversion of LAI with NCVI, and experience validation. The results showed that there was a good linear correlation between the simulation LAI inversed from NCVI model and the real LAI values. The model breaking the limitations of the traditional empirical models for LAI inversion has a good result for estimating LAI of the dense canopy whose LAI value was greater than 3. In addition, NCVI model was very sensitive to the water environment of soil, and the inversion result in the arid and semi-arid areas was superior to the general area.
Key words：Leaf area index;Normalized composite vegetation index (NCVI);Canopy water content;Remote sensing inversion;Corn
曹 仕1，刘湘南1*，刘美玲1，曹 珊2，姚 帅1 . 融合冠层水分特征的光谱参数NCVI及反演玉米LAI[J]. 光谱学与光谱分析, 2011, 31(02): 478-482.
CAO Shi1, LIU Xiang-nan1*, LIU Mei-ling1, CAO Shan2, YAO Shuai1 . Estimation of Leaf Area Index by Normalized Composite Vegetation Index Fusing the Spectral Feature of Canopy Water Content . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(02): 478-482.
[1] Chen J M, Black T A. Plant, Cell and Environment, 1992, 15: 421. [2] Bonan G B. Remote Sensing of Environment, 1995, 51:57. [3] Hanan N P, Bégué A. Agricultural and Forest Meteorology, 1995, 74: 155. [4] Veroustraete F, Patyn J, Myneni R B. Remote Sensing of Environment, 1996, 58: 115. [5] WANG Xi-qun, MA Lü-yi, JIA Zhong-kui, et al(王希群, 马履一, 贾忠奎, 等). Chinese Journal of Ecology(生态学杂志), 2005, 24(5): 537. [6] Verstraete M M, Pinty B, Myneini R B. Remote Sensing of Environment, 1996, 58: 201. [7] Wang P, Sun R, Hu J, et al. Journal of Environmental Management, 2007, 85: 607. [8] Tian Q, Luo Z, Chen J M, et al. Journal of Environmental Management, 2007, 85: 624. [9] Kouiti H, Hiroshi M, Hayato T, et al. Remote Sensing of Environment, 2010, 114: 514. [10] CHAI Lin-na, QU Yong-hua, ZHANG Li-xin, et al(柴琳娜, 屈永华, 张立新, 等). Advances in Earth Science(地球科学进展), 2009, 24(7): 756. [11] LI Ya, FENG Xiao, QIAO Shu, et al(黎 娅, 冯 晓, 乔 淑, 等). Journal of Henan Agricultural University(河南农业大学学报), 2009, 43(4): 364. [12] SONG Kai-shan, ZHANG Bai, WANG Zong-ming, et al(宋开山, 张 柏, 王宗明, 等). Chinese Journal of Ecology(生态学杂志), 2007, 26(10): 1690. [13] Penuelas J, Isla R, Filella I, et al. Crop Science, 1997, 37(1): 198. [14] Gao B C. Remote Sensing of Environment, 1996, 58: 257. [15] Strachan I B, Pattey E, Boisvert J B. Remote Sensing of Environment, 2002, 80: 213. [16] Apan A, Held A, Phinn S, et al. International Journal of Remote Sensing, 2004, 25(2): 489. [17] WAN Yu-qing, TAN Ke-long, ZHOU Ri-sheng, et al(万余庆, 谭克龙, 周日升, 等). Research of Hyperspectral Remote Sensing Application(高光谱遥感应用研究). Beijing: Science Press(北京: 科学出版社), 2006. 142.
