基于高光谱的水浇地与旱地春小麦拔节期叶绿素含量估测模型对比研究
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摘要
测定拔节期水浇地与旱地春小麦冠层光谱、叶绿素含量、覆盖度、苗高和叶宽,采用回归分析方法建立春小麦叶绿素含量高光谱估测模型,并对模型精度进行检验。结果表明:阳坡和双面坡地春小麦拔节期叶绿素含量与原始光谱反射率在可见光和近红外波段均呈正相关,水浇地和阴坡地在723 nm以前相关系数为负,723 nm以后为正。各地类春小麦叶绿素含量与各高光谱变量的相关性均较好,均达到了极显著水平(P<0.01)。无论在可见光还是近红外波段,水浇地春小麦叶绿素含量均与倒数之对数lg(1/R)的相关性最好,相关系数最大值可达0.98;阴坡地则与一阶微分的相关性最好,最大为0.94;而与阳坡和双面坡地相关性最好的高光谱指数为归一化植被指数。在各个波段,倒数之对数模型lg(1/R)、一阶微分模型(p')和归一化植被指数模型(N)分别是估测水浇地、阴坡地、阳坡和双面坡地春小麦叶绿素含量的最佳模型。虽然各模型R2均超过0.90,精确度均大于0.91,但阴坡地、阳坡和双面坡地的模型精确度和准确度略低于水浇地。以上模型的建立可为今后估测水浇地与旱地春小麦的健康状况提供参考。
In order to establish high spectral chlorophyll content model based on correlation analysis between chlorophyll content and five spectral variables of spring wheat under irrigated and dry land,canopy spectral,chlorophyll content,ground cover,seedling height,leaf width at jointing stage of spring wheat under different land were determined,and the precision of these model were tested. The result showed a positive correlation between chlorophyll content and original spectrum at visible light and near infrared band of sunny and double slopes at jointing stage of spring wheat,and a negative correlation below 723 nm and a positive correlation above 723 nm for irrigated land and shady slope. There was markedly significant correlation( P < 0. 01) between chlorophyll content and hyperspectral variables of spring wheat under different lands. Regardless of visible light or near infrared wave band,lg( 1 /R) was significantly correlated with the leaf chlorophyll content,with a correlation coefficient of 0. 98. Shady slope was correlated with first derivative( r = 0. 94),while for sunny and double slopes normalized difference vegetation index showed significant relationship. For each band,lg( 1 /R),p',and N were suitable indexes estimatingchlorophyll content for all lands of irrigated land,shady slope,and sunny and double-sided slope. Although the regression determination coefficient R2 was more than 0. 90,precision and accuracy of the proposed for shady slope,sunny and double slope are slightly lower than that of irrigated land.
In order to establish high spectral chlorophyll content model based on correlation analysis between chlorophyll content and five spectral variables of spring wheat under irrigated and dry land,canopy spectral,chlorophyll content,ground cover,seedling height,leaf width at jointing stage of spring wheat under different land were determined,and the precision of these model were tested. The result showed a positive correlation between chlorophyll content and original spectrum at visible light and near infrared band of sunny and double slopes at jointing stage of spring wheat,and a negative correlation below 723 nm and a positive correlation above 723 nm for irrigated land and shady slope. There was markedly significant correlation( P < 0. 01) between chlorophyll content and hyperspectral variables of spring wheat under different lands. Regardless of visible light or near infrared wave band,lg( 1 /R) was significantly correlated with the leaf chlorophyll content,with a correlation coefficient of 0. 98. Shady slope was correlated with first derivative( r = 0. 94),while for sunny and double slopes normalized difference vegetation index showed significant relationship. For each band,lg( 1 /R),p',and N were suitable indexes estimatingchlorophyll content for all lands of irrigated land,shady slope,and sunny and double-sided slope. Although the regression determination coefficient R2 was more than 0. 90,precision and accuracy of the proposed for shady slope,sunny and double slope are slightly lower than that of irrigated land.
引文
[1]易秋香,黄敬峰,王秀珍,等.玉米粗脂肪含量高光谱估算模型初探[J].作物学报,2007,33(1):171-174.
[2]疏小舟,尹球,匡定波,等.内陆水体藻类叶绿素浓度与反射光谱特征的关系[J].遥感学报报,2000,4(1):41-45.
[3]G Vane.Terrestrial imaging spectrometry:current status,future trends[J].Remote Sensing of Environment,1993,44(1):109-127.
[4]方红亮,田庆久.高光谱遥感在植被监测中的研究综述[J].遥感技术与应用,1998,13(1):62-68.
[5]陆凳槐.农业遥感的应用效益及在我国的发展战略[J].农业工程学报,1998,14(3):64-67.
[6]Madeira A C,Mendonca A,Ferreira M E,et al.Relationship between spectro radiometric and chlorophyll measurements in green beans[J].Communications in Soil Science and Plant Analysis,2000,31(6):631-643.
[7]孙红,李民赞,赵勇,等.冬小麦生长期光谱变化特征与叶绿素含量监测研究[J].光谱学与光谱分析,2010,30(1):193-195.
[8]Chappelle E W,Kim M S,Mcmurtrey J E.Ration analysis of reflectance spectra(RARS):an algorithm for the remote estimation of the concentrations of chlorophyll A,chlorophyll B and the carotencids in soybean leaves[J].Remote Sensing of Environment,1992,39:239-247.
[9]蒋金豹,陈云浩,黄文江,等.病害胁迫下冬小麦冠层叶片色素含量高光谱遥感估测研究[J].光谱学与光谱分析,2007,27(7):1364-1369.
[10]吴长山,项月琴,郑兰芬,等.利用高光谱数据对作物群体叶绿素密度估算的研究[J].遥感学报,2000,4(3):228-231.
[11]刘伟东,项月琴,郑兰芬,等.高光谱数据与水稻叶面积指数及叶绿素密度的相关分析[J].遥感学报,2000,4(4):279-283.
[12]杨吉龙,李家存,杨德明.高光谱分辨率遥感在植被监测中的应用综述[J].世界地质,2001,20(3):307-312.
[13]黄春燕,王登伟,曹连莆,等.棉花地上鲜生物量的高光谱估算模型研究[J].农业工程学报,2007,23(3):131-135.
[14]王登伟,李少昆,田庆玖,等.棉花主要栽培生理参数的高光谱估测研究[J].中国农业科学,2003,36(7):770-774.
[15]Prased S T,Ronald D P.Hyperspectral vegetation indices and their relationships with agricultural crop characteristics[J].Remote Sensing of Environment,2000,71:158-182.
[16]Hansena P M,Schjoerring J K.Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression[J].Remote Sens Environ,2003,86:542-553.
[17]Broge N H,Leblanc E.Comparing predicting power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density[J].Remote Sensing of Environment,2001,(76):156-172.
[18]林辉,唐代生.株洲主要地类地物波谱特征研究[J].中南林学院学报,2003,23(1):93-96.
[19]Zhou Q,Robson M.Automated rangeland vegetation cover and density estimation using ground digital images and a spectralcontextual classifier[J].Remote Sensing of Environment,2001,22:3457-3470.
[20]何挺,王静.土壤氧化铁光谱特征研究[J].地理与地理信息科学,2006,3(2):30-34.
[21]唐延林,王人潮,黄敬峰,等.不同供氮水平下水稻高光谱及其红边特征研究[J].遥感学报,2004,8(2):186-190.
[22]George Alan Blackbrun.Quantifying chlorophylls and caroteniods at leaf and canopy scales:An evaluation of some hyperspectral approaches[J].Remote Sen Environment,1998,66:273-285.
[23]乔红波,周益林,白由路,等.地面高光谱和低空遥感监测小麦白粉病初探[J].植物保护学报,2006,33(4):342-346.
[24]浦瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000:115-120.
[25]Krishnan P,Alexander J D,Butler B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Sci.Soc,1980,44:1282-1285.
[26]Massart D L,B G M Vandeginste,S M Deming,et al.Chenomet rics:A Textbook[M].Amsterdam:Elsevier,1988:35-37.
[27]王进,李新建,白丽,等.干旱区棉花冠层高光谱反射特征研究[J].中国农业气象,2012,33(1):114-118.
[28]唐延林,王秀珍,王珂.利用光谱法测定水稻生物物理参数及其与光谱变量的相关性研究[J].贵州大学学报(农业与生物科学版),2002,21(5):327-331.
[2]疏小舟,尹球,匡定波,等.内陆水体藻类叶绿素浓度与反射光谱特征的关系[J].遥感学报报,2000,4(1):41-45.
[3]G Vane.Terrestrial imaging spectrometry:current status,future trends[J].Remote Sensing of Environment,1993,44(1):109-127.
[4]方红亮,田庆久.高光谱遥感在植被监测中的研究综述[J].遥感技术与应用,1998,13(1):62-68.
[5]陆凳槐.农业遥感的应用效益及在我国的发展战略[J].农业工程学报,1998,14(3):64-67.
[6]Madeira A C,Mendonca A,Ferreira M E,et al.Relationship between spectro radiometric and chlorophyll measurements in green beans[J].Communications in Soil Science and Plant Analysis,2000,31(6):631-643.
[7]孙红,李民赞,赵勇,等.冬小麦生长期光谱变化特征与叶绿素含量监测研究[J].光谱学与光谱分析,2010,30(1):193-195.
[8]Chappelle E W,Kim M S,Mcmurtrey J E.Ration analysis of reflectance spectra(RARS):an algorithm for the remote estimation of the concentrations of chlorophyll A,chlorophyll B and the carotencids in soybean leaves[J].Remote Sensing of Environment,1992,39:239-247.
[9]蒋金豹,陈云浩,黄文江,等.病害胁迫下冬小麦冠层叶片色素含量高光谱遥感估测研究[J].光谱学与光谱分析,2007,27(7):1364-1369.
[10]吴长山,项月琴,郑兰芬,等.利用高光谱数据对作物群体叶绿素密度估算的研究[J].遥感学报,2000,4(3):228-231.
[11]刘伟东,项月琴,郑兰芬,等.高光谱数据与水稻叶面积指数及叶绿素密度的相关分析[J].遥感学报,2000,4(4):279-283.
[12]杨吉龙,李家存,杨德明.高光谱分辨率遥感在植被监测中的应用综述[J].世界地质,2001,20(3):307-312.
[13]黄春燕,王登伟,曹连莆,等.棉花地上鲜生物量的高光谱估算模型研究[J].农业工程学报,2007,23(3):131-135.
[14]王登伟,李少昆,田庆玖,等.棉花主要栽培生理参数的高光谱估测研究[J].中国农业科学,2003,36(7):770-774.
[15]Prased S T,Ronald D P.Hyperspectral vegetation indices and their relationships with agricultural crop characteristics[J].Remote Sensing of Environment,2000,71:158-182.
[16]Hansena P M,Schjoerring J K.Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression[J].Remote Sens Environ,2003,86:542-553.
[17]Broge N H,Leblanc E.Comparing predicting power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density[J].Remote Sensing of Environment,2001,(76):156-172.
[18]林辉,唐代生.株洲主要地类地物波谱特征研究[J].中南林学院学报,2003,23(1):93-96.
[19]Zhou Q,Robson M.Automated rangeland vegetation cover and density estimation using ground digital images and a spectralcontextual classifier[J].Remote Sensing of Environment,2001,22:3457-3470.
[20]何挺,王静.土壤氧化铁光谱特征研究[J].地理与地理信息科学,2006,3(2):30-34.
[21]唐延林,王人潮,黄敬峰,等.不同供氮水平下水稻高光谱及其红边特征研究[J].遥感学报,2004,8(2):186-190.
[22]George Alan Blackbrun.Quantifying chlorophylls and caroteniods at leaf and canopy scales:An evaluation of some hyperspectral approaches[J].Remote Sen Environment,1998,66:273-285.
[23]乔红波,周益林,白由路,等.地面高光谱和低空遥感监测小麦白粉病初探[J].植物保护学报,2006,33(4):342-346.
[24]浦瑞良,宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000:115-120.
[25]Krishnan P,Alexander J D,Butler B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Sci.Soc,1980,44:1282-1285.
[26]Massart D L,B G M Vandeginste,S M Deming,et al.Chenomet rics:A Textbook[M].Amsterdam:Elsevier,1988:35-37.
[27]王进,李新建,白丽,等.干旱区棉花冠层高光谱反射特征研究[J].中国农业气象,2012,33(1):114-118.
[28]唐延林,王秀珍,王珂.利用光谱法测定水稻生物物理参数及其与光谱变量的相关性研究[J].贵州大学学报(农业与生物科学版),2002,21(5):327-331.
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