光谱学与光谱分析 |
|
|
|
|
|
Estimation of Leaf Area Index by Normalized Composite Vegetation Index Fusing the Spectral Feature of Canopy Water Content |
CAO Shi1, LIU Xiang-nan1*, LIU Mei-ling1, CAO Shan2, YAO Shuai1 |
1. School of Information Engineering, China University of Geosciences, Beijing 100083, China 2. Sinohydro Bureau No. 8, Changsha 410000, China |
|
|
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.
|
Received: 2010-04-23
Accepted: 2010-09-08
|
|
Corresponding Authors:
LIU Xiang-nan
E-mail: liuxncugb@163.com
|
|
[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.
|
[1] |
WANG Hong-jian1, YU Hai-ye1, GAO Shan-yun1, LI Jin-quan1, LIU Guo-hong1, YU Yue1, LI Xiao-kai1, ZHANG Lei1, ZHANG Xin1, LU Ri-feng2, SUI Yuan-yuan1*. A Model for Predicting Early Spot Disease of Maize Based on Fluorescence Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3710-3718. |
[2] |
HAO Zi-yuan1, YANG Wei1*, LI Hao1, YU Hao1, LI Min-zan1, 2. Study on Prediction Models for Leaf Area Index of Multiple Crops Based on Multi-Source Information and Deep Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3862-3870. |
[3] |
HUANG You-ju1, TIAN Yi-chao2, 3*, ZHANG Qiang2, TAO Jin2, ZHANG Ya-li2, YANG Yong-wei2, LIN Jun-liang2. Estimation of Aboveground Biomass of Mangroves in Maowei Sea of Beibu Gulf Based on ZY-1-02D Satellite Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3906-3915. |
[4] |
LI Yang1, LI Xiao-qi1, YANG Jia-ying1, SUN Li-juan2, CHEN Yuan-yuan1, YU Le1, WU Jing-zhu1*. Visualisation of Starch Distribution in Corn Seeds Based on Terahertz Time-Domain Spectral Reflection Imaging Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2722-2728. |
[5] |
ZHANG Fu1, 2, WANG Xin-yue1, CUI Xia-hua1, YU Huang1, CAO Wei-hua1, ZHANG Ya-kun1, XIONG Ying3, FU San-ling4*. Identification of Maize Varieties by Hyperspectral Combined With Extreme Learning Machine[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2928-2934. |
[6] |
YANG Dong-feng1, HU Jun2*. Accurate Identification of Maize Varieties Based on Feature Fusion of Near Infrared Spectrum and Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2588-2595. |
[7] |
LIU Zhao1, 2, LI Hua-peng1, CHEN Hui1, 2, ZHANG Shu-qing1*. Maize Yield Forecasting and Associated Optimum Lead Time Research Based on Temporal Remote Sensing Data and Different Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2627-2637. |
[8] |
ZHANG Chao1*, SU Xiao-yu1, XIA Tian2, YANG Ke-ming3, FENG Fei-sheng4. Monitoring the Degree of Pollution in Different Varieties of Maize Under Copper and Lead Stress[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1268-1274. |
[9] |
ZHANG Yan1, 2, WANG Hui-le1, LIU Zhong2, ZHAO Hui-fang1, YU Ying-ying1, LI Jing1, TONG Xin1. Spectral Analysis of Liquefaction Residue From Corn Stalk Polyhydric
Alcohols Liquefaction at Ambient Pressure[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 911-916. |
[10] |
YANG Dong-feng1, LI Ai-chuan1, LIU Jin-ming1, CHEN Zheng-guang1, SHI Chuang1, HU Jun2*. Optimization of Seed Vigor Near-Infrared Detection by Coupling Mean Impact Value With Successive Projection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3135-3142. |
[11] |
YANG Xin1, 2, YUAN Zi-ran1, 2, YE Yin1, 2*, WANG Dao-zhong1, 2, HUA Ke-ke1, 2, GUO Zhi-bin1, 2. Winter Wheat Total Nitrogen Content Estimation Based on UAV
Hyperspectral Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3269-3274. |
[12] |
WU Bing, YANG Ke-ming*, GAO Wei, LI Yan-ru, HAN Qian-qian, ZHANG Jian-hong. EC-PB Rules for Spectral Discrimination of Copper and Lead Pollution Elements in Corn Leaves[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3256-3262. |
[13] |
ZHANG Yan1, WANG Hui-le1, ZHAO Hui-fang1, LI Jing1, TONG Xin1, LIU Zhong2. Optimization of Corn Stalk Liquefaction Conditions Under Atmospheric Pressure and Analysis of Biofuel[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2551-2556. |
[14] |
WANG Ge1, YU Qiang1*, Yang Di2, NIU Teng1, LONG Qian-qian1. Retrieval of Dust Retention Distribution in Beijing Urban Green Space Based on Spectral Characteristics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2572-2578. |
[15] |
FENG Tian-shi1, 2, 3, PANG Zhi-guo1, 2, 3*, JIANG Wei1, 2, 3. Remote Sensing Retrieval of Chlorophyll-a Concentration in Lake Chaohu Based on Zhuhai-1 Hyperspectral Satellite[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2642-2648. |
|
|
|
|