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遥感技术与应用  2010, Vol. 25 Issue (5): 668-674    DOI: 10.11873/j.issn.1004-0323.2010.5.668
研究与应用     
花生叶面积指数与特征导数光谱的相关性
张晓艳,刘锋,王丽丽,封文杰,刘淑云,朱建华
(山东省农业科学院科技信息工程技术研究中心,山东 济南250100)
Correlations of Leaf Area Index (LAI) with Eigen Derivative Spectrum in Peanut
ZHANG Xiao-yan,LIU Feng,WANG Li-li,FENG Wen-jie,LIU Shu-yun,ZHU Jian-hua
(S&T Information Engineering Research Center of Shandong Academy ofAgricultural Sciences,Jinan 250100,China)
 全文: PDF(2119 KB)  
摘要:

运用导数光谱分析技术,研究了不同氮肥水平下不同品种花生的叶面积指数(Leaf Area Index,LAI)与冠层导数光谱及其衍生参数的定量关系。结果表明,花生导数光谱在红边区域680~750 nm范围内与叶面积指数的相关关系比较稳定,在680~710 nm范围内呈正相关,在710~750 nm范围内呈负相关,685 nm和735 nm波段相关程度达到最大。在三边参数中,振幅参数优于面积参数优于位置参数,且仅有红边的面积、振幅、位置参数与花生LAI的相关性最好,相关系数分别为-0.9345、-0.9869和0.7632。在系列衍生参数中,RDr.b、RDr.y、NDDr.y与LAI呈极显著正相关关系外,其它衍生参数均与LAI呈极显著负相关关系,红蓝边面积差DSDr.b、红黄边面积差DSDr.y、红黄边振幅差DDr.y与LAI的相关系数分别为-0.9690、-0.9485、-0.9764,相关程度均较高。因此,研究认为,可以利用685 nm和735 nm两波段的一阶导数光谱、红边面积、红边振幅、红蓝边面积差、红黄边面积差、红黄边振幅差等来监测花生的叶面积指数。

关键词: 叶面积指数导数光谱相关性分析花生    
Abstract:

By the analysis technology of derivative spectrum,the quantitative relation of the LAI with the canopy derivative spectrum and their derived parameters were studied in different peanut varieties under different nitrogen levels.The results showed that the correlation of peanut derivative spectrum with LAI was stable in 680~750 nm of red\|edge region,which was positive in the range of 680~710 nm,but negative in the range of 710~750 nm.And their correlations arrived at the largest at 685 nm and 735 nm.Within the trilateral parameters,the amplitude parameters were superior to the area parameters and the position parameters,and only the area,amplitude and position parameters of red edge correlated best with the peanut LAI,whose correlation coefficients were -0.9345,-0.9869 and 0.7632 respectively.Among the derived parameters,RDr.b,RDr.y and NDDr.y were significantly correlated with the peanut LAI,while the other derived parameters were negatively correlated with LAI.The correlation coefficients of DSDr.b,DSDr.y and DDr.y with LAI were -0.9690,-0.9485 and -0.9764 respectively,all of which were higher.In conclusion,the first derivative spectrum,SDr.Dr,DSDr.b,DSDr.y and DDr.y of the two brands of 685 nm and 735 nm could be used to monitor the LAI of peanut.

Key words: Leaf area index (LAI)    Derivative spectrum    Correlation analysis    Peanut
收稿日期: 2010-02-02 出版日期: 2013-10-30
基金资助:

国家科技支撑计划项目(2006BAD21B04\|20、2006BAD21B04\|20\|1)资助。

通讯作者: 朱建华(1959-),男,研究员,主要从事农业信息技术方面研究。E-mail:zhujh@saas.ac.cn。   
作者简介: 张晓艳(1974-),女,副研究员,博士,主要从事作物模拟模型及遥感在农业中的应用。E-mail:zxylf5367@163.com。
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引用本文:

张晓艳, 刘锋, 王丽丽, 封文杰, 刘淑云, 朱建华. 花生叶面积指数与特征导数光谱的相关性[J]. 遥感技术与应用, 2010, 25(5): 668-674.

ZHANG Xiao-Yan, LIU Feng, WANG Li-Li, FENG Wen-Jie, LIU Shu-Yun, ZHU Jian-Hua. Correlations of Leaf Area Index (LAI) with Eigen Derivative Spectrum in Peanut. Remote Sensing Technology and Application, 2010, 25(5): 668-674.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2010.5.668        http://www.rsta.ac.cn/CN/Y2010/V25/I5/668

[1]Broge N H,Mortensen J V.Deriving Green Crop Area Index and Canopy Chlorophyll Density of Winter Wheat from Spectral Reflectance Data[J].Remote Sensing of Environment,2002,81(1):45-57.
[2]Chen J M,Cihlar J.Retrieving Leaf Area Index of Boreal Conifer Forests Using Landsat TM Images[J].Remote Sensing of Environment,1996,55(2):153-162.
[3]Wiegand C L,Gausman  H W,Cuellar J A,et al.Vegetation Density as Deduced from ERTS-1 MSS Response[R].Third Earth Resources Technology Satellite-1 Symposium,Volume 1,Section A,NASA SP-351,1974:93-116.
[4]Jordan C F.Derivation of Leaf Area Index from Quality of Light on the Forest Floor[J].Ecological Society of America,1969,50(4):663-666.
[5]Pearson R L,Miller D L.Remote Mapping of Standing Crop Biomass for Estimation of the Productivity of the Shortgrass Prairie[C]//Proceedings of the 8th International Symposium on Remote Sensing of Environment.Environmental Research Institute of Michigan.Ann ARbor,MI,USA,1972:1357-1381.
[6]Rouse J W,Haas R H,Schell J A,et al.Monitoring the Vernal Advancement of Retrogradation of Natural Vegetation[R].NASA/GSFC,Type Ⅲ,Final Report,Greenbelt,MD,USA,1974:1-371.
[7]Wu Honggan,Qiao Yanyou,Chen Linhong,et al.Remote Se-nsing Monitoring of Dynamic Changes of Leaf Area Index in Masson Pine Stands[J].Acta Phytoecologica Sinica,1997,21(5):485-488.[武红敢,乔彦友,陈林洪,等.马尾松林叶面积指数动态变化的遥感监测研究[J].植物生态学报,1997,21(5):485-488.]
[8]Xue Lihong,Cao Weixing,Luo Weihong,et al.Relationship between Spectral Vegetation Indices and  LAI in Rice[J].Acta Phytoecologica Sinica,2004,28(1):47-52.[薛利红,曹卫星,罗卫红,等.光谱植被指数与水稻叶面积指数相关性的研究[J].植物生态学报,2004,28(1):47-52.]
[9]Tan Changwei,Huang Yide,Huang Wenjiang,et al.Study on Colony Leaf Area Index of Summer Maize by Remote Sensing Vegetation Indexes Method[J].Journal of Anhui Agricultural University,2004,31(4):392-397.[谭昌伟,黄义德,黄文江,等.夏玉米叶面积指数的高光谱遥感植被指数法研究[J].安徽农业大学学报,2004,31(4):392-397.]
[10]Vane G,Goetz A F H.Terrestrial Imaging Spectrometry:Cu-rrent Status,Future Trends[J].Remote Sensing of Environment,1993,44(2):117-126.
[11]Li Y,Demetriades-Shah T H,Kanemasu E T,et al.Use of Second Derivatives of Canopy Reflectance for Monitoring Prairie Vegetation over Different Soil Backgrounds[J].Remote Sensing of Environment,1993,44(1):81-87.
[12]Philpot W D.The Derivative Ratio Algorithm:Avoiding Atmospheric Effects in Remote Sensing[J].IEEE Transactions on Geosciences and Remote Sensing,1991,29(3):350-357.
[13]Wang Xiuzhen,Huang Jingfeng,Li Yunmei,et al.The Study on Hyperspectral Remote Sensing Estimation Models about LAI of Rice[J].Journal of Remote Sensing,2004,8(1):81-88.[王秀珍,黄敬峰,李云梅,等.水稻叶面积指数的高光谱遥感估算模型[J].遥感学报,2004,8(1):81-88.]
[14]Wang Xiuzhen,Huang Jingfeng,Li Yunmei,et al.Study on Hyperspectral Remote Sensing Estimation Models for the Ground Fresh Biomass of Rice[J].Acta Agronomica Sinica,2003,29(6):815-821.[王秀珍,黄敬峰,李云梅,等.水稻地上鲜生物量的高光谱遥感估算模型研究[J].作物学报,2003,29(6):815-821.]
[15]Huang Jingfeng,Wang Yuan,Wang Fumin,et al.Red Edge Characteristics and Leaf Area Index Estimation Model Using Hyperspectral Data for Rape[J].Transactions of the Chinese Society of Agricultural Engineering,2006,22(8):22-26.[黄敬峰,王渊,王福民,等.油菜红边特征及其叶面积指数的高光谱估算模型[J].农业工程学报,2006,22(8):22-26.]
[16]Ju Changhua,Tian Yongchao,Zhu Yan,et al.Relationship between Derivative Spectra and Photosynthetic Organ Area in Rape Seed(Brassica napus)[J].Journal of Plant Ecology(Chinese Version),2008,32(3):664-672.[鞠昌华,田永超,朱艳,等.油菜光合器官面积与导数光谱特征的相关关系[J].植物生态学报,2008,32(3):664-672.]
[17]Wan Shubo.Peanut (Arachis hypogaea L.) Cultivation in China[M].Shanghai:Shanghai Scientific & Technical Publishers,2003,279-290.[万书波.中国花生栽培学[M].上海:上海科学技术出版社,2003:279-290.]

 

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