植物叶绿素荧光被动遥感探测及应用研究
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摘要
叶绿素荧光包含了丰富的光合信息,一直是光合生理研究的热点课题,被称为研究植物光合功能快速、无损伤的敏感探针。遥感作为大面积、快速获取目标性质的手段,近年来得到了突飞猛进的发展,在农业诸多领域都得到了广泛的应用。两者结合可以发挥各自优势。本研究以冬小麦为主要研究对象,分别在单叶和冠层不同尺度上,采用不同的算法提取表观反射信号中的荧光信息。结合荧光参数、叶绿素等生理生化参数测定,探讨不同水、肥、病胁迫下叶绿素荧光光谱特征特性,以及荧光指标与其他参数间的关系,分析荧光被动遥感应用于作物胁迫诊断的可行性。研究取得如下结果:
1.采用不同算法成功地从单叶表观反射光谱中提取到叶绿素荧光光谱。采用ASD光谱仪和LI-COR 1800-12S积分球耦合,光源模拟日光辐射,通过对积分球光源加与不加不同种类(长波通、短波通)截止滤光片的办法,获得不同光照条件下的叶片反射光谱,按照不同算法提取叶绿素荧光信息。结果表明利用长波通滤光片测得的表观反射率差值光谱可以代表荧光光谱,在红光区和远红光区表现为明显的双峰特征。采用短波通滤光片可直接获得荧光光谱,不同植物种类荧光光谱差异明显。透射光中也包含叶绿素荧光,检测剑的荧光相对比例大致与反射光荧光相近。结果验证了荧光对表观反射率光谱也有一定贡献的结论,并可以定量提取。
2.初步明确了冠层反射光谱中能够敏感反映叶绿素荧光的指标。日光诱导的叶绿素荧光,更真实地反映植物的生理状态。通过日变化试验,定点观测不同植物(小麦、地锦)的冠层光谱,并同步进行了叶绿素荧光参数测定。结果表明,表观反射率计算的曲率指数CUR、一阶导数光谱比值Dmax/D702以及生理反射指数PRI与荧光参数Fv/Fm变化趋势一致,一天中均呈现高—低—高的“V”字型变化;利用冠层辐照度光谱中688nm和760nm两个氧气吸收形成的夫琅和费暗线特征,可以计算太阳光诱导的光合作用荧光;荧光对PAR十分敏感,与荧光动力学参数FvPFm存在极显著的负相关关系,复相关系数达到了0.9以上。论文提出的利用野外地物光谱仪的辐照度模式观测的数据探测植被荧光,拓展了野外地物光谱仪的使用功能。
3.不同肥水条件下单叶、冠层荧光光谱特性存在差异。单叶水平表观反射率光谱中提取的荧光双峰比值Dif685/Dif740与荧光参数Fv/Fm关系密切,可以用来反映叶片含水量状况和叶片全氮含量。冠层水平表观反射率光谱中提取的PRI、红边区一阶导数比值、夫
The chlorophyll fluorescence (CF) signature emitted from vegetation provides abundance of information of photosynthesis activity, and has been used as a powerful tool to obtain physiological information of plant leaves in a non-invasive way. Remote sensing (RS) can provide Earth's surface information in large area and temporal period with different scales. So far RS has been widely applied in many fields in agriculture. The combination of CF and RS may take respective advantages. In this study, wheat (Triticum aestivum L.) was selected as the main material. First, the methods and algorithms were studied to separate CF from apparent reflectance spectra at leaf and canopy levels respectively. Then, CF from apparent reflectance spectra was analyzed with physiological and biochemical parameters such as CF parameters measured by modulated chlorophyll fluorometer, chlorophyll, etc. The main purpose was to study the chacteristics in fluorescence spectra at stress conditions (such as water and nitrogen deficiency, rust infected), as well as the influences on CF and other physiological and biochemical parameters made by stress factors. Finally, the potential of passive sensing of CF applied in crop stress detection was discussed. The results were summarized as below.1. Chlorophyll fluorescence spectra were successfully obtained from apparent reflectance spectra by special methods and algorithms. The leaves apparent spectra were measured under illuminations with and without specially designed filters, using a LI-COR 1800 integrating sphere coupled with an ASD spectrometer. Two kinds of filters (3 for long wave pass edge and 2 for short wave pass edge) were tested respectively. The results showed that fluorescence spectra could be derived from reflectance difference spectra under illuminations with and without long pass filter. Similarly, fluorescence spectra were derived from reflectance under illumination with short pass filters directly. Obvious differences in fluorescence spectra were founded in different kinds of plant. Additionally, CF was also detected from the transmittance spectrum and the relative scale was approximately close with that of the reflectance. The results confirmed the conclusion that CF was contributed to apparent reflectance to some extent and it could be separated quantificationally.2. The CF indices that closely related to apparent reflectance spectra at canopy scale were preliminary illustrated. The solar-induced CF can reflect real plant physiological status. Diurnal change experiments were conducted to measure canopy reflectance in wheat and Parthenocissus tricuspidata respectively, at the same time CF parameters were measured. The results indicated that CUR (curvature index), Dmax/D702 (the ratio of the first derivative at two bands) and PRI (physiological reflectance index) had the same tendency with Fv/Fm, which showed a characteristic of 'V type. Then, a method based on FLD (Fraunhofer line discriminator) was introduced to calculate solar induced fluorescence according to the molecular oxygen absorption by the terrestrial atmosphere at 688 and 760 nm. CF derived from FLD was sensitive to PAR, and had a notably negative relation with fluorescence kinetic parameter Fv/Fm (R~2>0.9). The paper provide a new method to detect vegetation fluorescence signals by radiance mode using field spectrometer, which extend the application scales of the instruments.3. The characteristics of fluorescence spectra at leaf or canopy levels exhibited differences
under different N or water treatments. The ratio of the reflectance difference at 685nm and 740nm Dif685/Dif740 at leaf level was linear correlated with Fv/Fm and it could be an indicator to reflect leaf water or nitrogen content. At the canopy level PRI, Dmax/D702, FLD fluorescence present high correlationships with plant water content or canopy nitrogen density (CND). These indices have the potential to diagnose the water or nitrogen status in the fields, but the influence factors especially canopy structure should not be neglected.4. A preliminary study on CF for detecting stripe rust in wheat was conducted. The results showed that physiological parameters SPAD, photosynthetic rate decreased rapidly as leaf severity increases. CF parameters measured by modulated fluorometer showed that the maximal photochemical efficiency Fv/Fm and yield of quantum efficiency decreased gradually, whereas non-phochemical quenching co-effficient qN increased. CF intensity calculated from leaf apparent reflectance had an increase tendency at 685nm while decreased at 740nm. At the canopy level, CF at 688 nm was positively correlated with the disease index (DI) whereas CF at 760 nm was negatively correlated with DI. Ratios of CF at 688 to that at 760 nm, which found to be a suitable indicator of stress events in plants, were positively related to DI.5. The applicability of passive sensing of CF to the detection of crop stress was accessed. Spectral data and agricultural sampling data were not well linked together. On the basis of research on CF characteristics at leaf level, it is necessary to develop a model to simulate CF from leaf to canopy level, taking account of the influence of viewing geometry, atmospheric characteristics and the environmental factors. Additionally, CF technique should integrate with reflectance spectrum and crop cultivation characteristics in order to detect crop condition timely, rapidly and accurately, and to realize precision management under optimal regulation and control.
1.采用不同算法成功地从单叶表观反射光谱中提取到叶绿素荧光光谱。采用ASD光谱仪和LI-COR 1800-12S积分球耦合,光源模拟日光辐射,通过对积分球光源加与不加不同种类(长波通、短波通)截止滤光片的办法,获得不同光照条件下的叶片反射光谱,按照不同算法提取叶绿素荧光信息。结果表明利用长波通滤光片测得的表观反射率差值光谱可以代表荧光光谱,在红光区和远红光区表现为明显的双峰特征。采用短波通滤光片可直接获得荧光光谱,不同植物种类荧光光谱差异明显。透射光中也包含叶绿素荧光,检测剑的荧光相对比例大致与反射光荧光相近。结果验证了荧光对表观反射率光谱也有一定贡献的结论,并可以定量提取。
2.初步明确了冠层反射光谱中能够敏感反映叶绿素荧光的指标。日光诱导的叶绿素荧光,更真实地反映植物的生理状态。通过日变化试验,定点观测不同植物(小麦、地锦)的冠层光谱,并同步进行了叶绿素荧光参数测定。结果表明,表观反射率计算的曲率指数CUR、一阶导数光谱比值Dmax/D702以及生理反射指数PRI与荧光参数Fv/Fm变化趋势一致,一天中均呈现高—低—高的“V”字型变化;利用冠层辐照度光谱中688nm和760nm两个氧气吸收形成的夫琅和费暗线特征,可以计算太阳光诱导的光合作用荧光;荧光对PAR十分敏感,与荧光动力学参数FvPFm存在极显著的负相关关系,复相关系数达到了0.9以上。论文提出的利用野外地物光谱仪的辐照度模式观测的数据探测植被荧光,拓展了野外地物光谱仪的使用功能。
3.不同肥水条件下单叶、冠层荧光光谱特性存在差异。单叶水平表观反射率光谱中提取的荧光双峰比值Dif685/Dif740与荧光参数Fv/Fm关系密切,可以用来反映叶片含水量状况和叶片全氮含量。冠层水平表观反射率光谱中提取的PRI、红边区一阶导数比值、夫
The chlorophyll fluorescence (CF) signature emitted from vegetation provides abundance of information of photosynthesis activity, and has been used as a powerful tool to obtain physiological information of plant leaves in a non-invasive way. Remote sensing (RS) can provide Earth's surface information in large area and temporal period with different scales. So far RS has been widely applied in many fields in agriculture. The combination of CF and RS may take respective advantages. In this study, wheat (Triticum aestivum L.) was selected as the main material. First, the methods and algorithms were studied to separate CF from apparent reflectance spectra at leaf and canopy levels respectively. Then, CF from apparent reflectance spectra was analyzed with physiological and biochemical parameters such as CF parameters measured by modulated chlorophyll fluorometer, chlorophyll, etc. The main purpose was to study the chacteristics in fluorescence spectra at stress conditions (such as water and nitrogen deficiency, rust infected), as well as the influences on CF and other physiological and biochemical parameters made by stress factors. Finally, the potential of passive sensing of CF applied in crop stress detection was discussed. The results were summarized as below.1. Chlorophyll fluorescence spectra were successfully obtained from apparent reflectance spectra by special methods and algorithms. The leaves apparent spectra were measured under illuminations with and without specially designed filters, using a LI-COR 1800 integrating sphere coupled with an ASD spectrometer. Two kinds of filters (3 for long wave pass edge and 2 for short wave pass edge) were tested respectively. The results showed that fluorescence spectra could be derived from reflectance difference spectra under illuminations with and without long pass filter. Similarly, fluorescence spectra were derived from reflectance under illumination with short pass filters directly. Obvious differences in fluorescence spectra were founded in different kinds of plant. Additionally, CF was also detected from the transmittance spectrum and the relative scale was approximately close with that of the reflectance. The results confirmed the conclusion that CF was contributed to apparent reflectance to some extent and it could be separated quantificationally.2. The CF indices that closely related to apparent reflectance spectra at canopy scale were preliminary illustrated. The solar-induced CF can reflect real plant physiological status. Diurnal change experiments were conducted to measure canopy reflectance in wheat and Parthenocissus tricuspidata respectively, at the same time CF parameters were measured. The results indicated that CUR (curvature index), Dmax/D702 (the ratio of the first derivative at two bands) and PRI (physiological reflectance index) had the same tendency with Fv/Fm, which showed a characteristic of 'V type. Then, a method based on FLD (Fraunhofer line discriminator) was introduced to calculate solar induced fluorescence according to the molecular oxygen absorption by the terrestrial atmosphere at 688 and 760 nm. CF derived from FLD was sensitive to PAR, and had a notably negative relation with fluorescence kinetic parameter Fv/Fm (R~2>0.9). The paper provide a new method to detect vegetation fluorescence signals by radiance mode using field spectrometer, which extend the application scales of the instruments.3. The characteristics of fluorescence spectra at leaf or canopy levels exhibited differences
under different N or water treatments. The ratio of the reflectance difference at 685nm and 740nm Dif685/Dif740 at leaf level was linear correlated with Fv/Fm and it could be an indicator to reflect leaf water or nitrogen content. At the canopy level PRI, Dmax/D702, FLD fluorescence present high correlationships with plant water content or canopy nitrogen density (CND). These indices have the potential to diagnose the water or nitrogen status in the fields, but the influence factors especially canopy structure should not be neglected.4. A preliminary study on CF for detecting stripe rust in wheat was conducted. The results showed that physiological parameters SPAD, photosynthetic rate decreased rapidly as leaf severity increases. CF parameters measured by modulated fluorometer showed that the maximal photochemical efficiency Fv/Fm and yield of quantum efficiency decreased gradually, whereas non-phochemical quenching co-effficient qN increased. CF intensity calculated from leaf apparent reflectance had an increase tendency at 685nm while decreased at 740nm. At the canopy level, CF at 688 nm was positively correlated with the disease index (DI) whereas CF at 760 nm was negatively correlated with DI. Ratios of CF at 688 to that at 760 nm, which found to be a suitable indicator of stress events in plants, were positively related to DI.5. The applicability of passive sensing of CF to the detection of crop stress was accessed. Spectral data and agricultural sampling data were not well linked together. On the basis of research on CF characteristics at leaf level, it is necessary to develop a model to simulate CF from leaf to canopy level, taking account of the influence of viewing geometry, atmospheric characteristics and the environmental factors. Additionally, CF technique should integrate with reflectance spectrum and crop cultivation characteristics in order to detect crop condition timely, rapidly and accurately, and to realize precision management under optimal regulation and control.
引文
[1].董彩霞,赵世杰,田纪春,孟庆伟,邹琦。不同浓度的硝酸盐对高蛋白小麦幼苗叶片叶绿素荧光参数的影响。作物学报,2002,28(1):59-64.
[2].范燕萍,余让才,陈建勋,杨瑞陶。氮素营养胁迫对匙叶天南星生长及光合特性的影响.园艺学报,2000,27(4):297-299.
[3].冯志立,冯玉龙,曹坤芳。光强对砂仁叶片光合作用光抑制及热耗散的影响。植物生态学报,2002,26(1):77-82.
[4].黄木易,黄义德,黄文江,刘良云,王纪华,万安民。冬小麦条锈病生理变化及其遥感机理。安徽农业科学,2004,32(1):132-134.
[5].黄木易,王纪华,黄文江,黄义德,赵春江,万安民。冬小麦条锈病的光谱特征及遥感监测。农业工程学报,2003,19(6):154-158.
[6].黄文江,王纪华,刘良云,赵春江,杜小鸿。冬小麦红边参数变化规律及其营养诊断,遥感技术与应用,2003,18(4):206-211.
[7].李德成,徐彬彬,石晓日,张崇静,吴荣。模拟酸雨对水稻叶片荧光光谱特性的影响。中国环境科学,1998,18(6):498-500.
[8].李云梅,倪绍祥,黄敬峰。高光谱数据探讨水稻叶片叶绿素含量对叶片及冠层光谱反射特性的影响。遥感技术与应用,2003,18(1):1-5.
[9].林世青,许春辉,张其德,徐黎,毛大璋,匡廷云.叶绿素荧光动力学在植物抗性生理学、生态学和农业现代化中的应用.植物学报,1992,9(1):1-16.
[10].刘良云,黄木易,黄文江,王纪华,赵春江,郑兰芬,童庆禧。利用多时相的高光谱航空图像监测冬小麦条锈病。遥感学报,2004,8(3):275-281.
[11].刘良云。高光谱遥感在精准农业中的应用研究,中国科学院遥感应用研究所博士后研究工作报告,2002.
[12].刘伟东,项月琴,郑兰芬,童庆禧,吴长山。高光谱数据与水稻叶面积值数及叶绿素密度的相关分析。遥感学报,2000,4(4):279-283.
[13].卢从明,张其德,匡廷云。水分胁迫对小麦光系统Ⅱ的影响。植物学报,1994,36(2):93-98.
[14].卢艳丽。小麦株型与氮素营养品质的遥感监测。中国农业科学院博士学位论文,2005年6月.
[15].罗俊,张木清,吕建林,林彦铨。水分胁迫对不同甘蔗品种叶绿素a荧光动力学的影响。福建农业大学学报,2000,29(1):18-22.
[16].沈玉其,徐彬彬,石晓日,李德成,周斌,朱永豪,张崇静,吴荣,刘南英。关于植被激光荧光遥感的若干基本问题。环境遥感,1992,7(增):22-33.
[17].石晓日,徐彬彬,李德成,周斌,沈玉其,朱永豪,张崇静,吴荣,刘南英。土壤激光诱导荧光遥感研究初探。环境遥感,1992,7(增):15-21.
[18].唐延林,王秀珍,黄敬峰,王人潮。水稻微分光谱和植被指数的作用探讨。农业工程学报,2003,19(1):145-150.
[19].田庆久,宫鹏,赵春江,郭晓维。用光谱反射率诊断小麦水分状况的可行性分析,科学 通报,2000。45(24):2645-2650.
[20].王坷,沈掌泉,王人潮。应用荧光光谱特征监测水稻钾营养的可行性研究。:朱军主编,生命科学研究与应用,浙江大学出版社,1996,571.
[21].王可玢,许春辉,赵福洪,唐崇欣,戴云玲.水分胁迫对小麦旗叶某些体内叶绿素a荧光参数的影响.生物物理学报,1997,13(2):273-278.
[22].王茜,魏光辉。机油产品激光诱导荧光特性的研究。光子学报,2001,30(10):1289-1291.
[23].王人潮,陈铭臻,蒋亨显。水稻遥感估产的农学机理研究。Ⅰ。不同氮素水平的水稻光谱特征及其敏感波段的选择。浙江农业大学学报,1993 19(增刊):7-14.
[24].王人潮,蒋亨显,王珂,沈掌泉。论中国农业遥感与信息技术发展战略。科技通报,1999,15(1):1-7.
[25].王秀珍,王人潮,黄敬峰。微分光谱遥感及其在水稻农学参数测定上的应用研究。农业工程学报,2002,18(1):9-13.
[26].王之杰。冬小麦冠层氮素分布与品质遥感的研究。中国农业大学博士学位论文,2004年5月.
[27].吴长山,项月琴,郑兰芬,童庆禧。利用高光谱数据对作物群体叶绿素密度的研究。遥感学报,2000,4(3):228-232.
[28].夏达英,王振先,张士魁。荧光技术在海洋环境学上的应用研究,1999,21(3):66-72
[29].徐彬彬,石晓日,李德成。模拟酸雨对大豆的激光诱导荧光光谱和反射光谱的影响研究。土壤,2000(3):113-119.
[30].徐德聪,吕芳德,栗彬,蒋瑶。不同立地美国山核桃叶绿素荧光特性及叶性状比较。经济林研究 2005,23(4):17-20.
[31].许长成,李德全,邹琦,张建华.干旱条件下冬小麦不同叶龄叶绿素荧光及叶黄素循环组分的变化.植物生理学报,1999,25(1):29-37.
[32].薛利红,罗卫红,曹卫星,田永超。作物水分和氮素光谱诊断研究进展。遥感学报,2003,7(1):73-80.
[33].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。世界地质,2001,20(3):307-312.
[34].杨敏华。面向精准农业的高光谱遥感作物信息获取。中国农业大学博士学位论文,2002,6.
[35].张守仁。叶绿素荧光动力学参数的意义及讨论。植物学通报,1999,16(4):444-448.
[36].张霞,刘良云,赵春江,张兵。利用高光谱遥感图像估算小麦氮含量。遥感学报,2003,7(3):176～179.
[37].赵春江,黄文江,王纪华,杨敏华,薛绪掌。不同品种、肥水条件下冬小麦光谱红边参数研究。中国农业科学,2002,35(8):980-987.
[38].赵春江,黄文江,王之杰,王北洪,王纪华。不同水肥处理下冬小麦冠层含水率与温度关系的研究。农业工程学报,2002,18(2):25-28.
[39].赵英时等编著。遥感应用分析原理与方法。科学出版社。2003
[40].朱永豪,张崇静,吴荣,刘南英,沈玉其,徐彬彬,石晓日,李德成,周斌。激光荧光 技术用于地物遥感的可能性研究。环境遥感,1992,7(增):1-7.
[41]. Agati G, Cerovic Z, Moya I. The effect of temperature on chlorophyll fluorescence: the role of PSI in 735 nm fluorescence. Photochem. Photobiol, 2000, 72: 75-84.
[42]. Alonso L, Moreno J, Moya I, Miller J R. A comparison of different techniques for passive measurement of vegetation photosynthetic activity: solar-induced fluorescence, red-edge reflectance structure and photochemical reflectance indices. IEEE International Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 1: 604-606.
[43]. Barbini R, Colao F, Fantoni R, Micheli C, Palucci A, Ribezzo S. Design and application of a lidar fluorosensor system for remote monitoring of phytoplankton. ICES Journal of Marine Science, 1998, 55: 793-802.
[44]. Bassanezi R B, Amorim L, Bergamin Filho A, Berger R D. Gas exchange and emission of chlorophyll fluorescence during the monocycle of rust, angular leaf spot and anthracnose on bean leaves as a function of their trophic characteristics. Journal of Phytopathology, 2002, 150: 37-47.
[45]. Berges J A, Charlebois D O, Mauzerall D C, et al. Differential Effects of nitrogen limitation on photosynthetic efficiency of photosystems Ⅰ and Ⅱ in microalgae. Plant Physiol, 1996, 110: 689-696.
[46]. Blackburn G A. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leave. Int. J. Remote Sens. 1998, 19(4): 657-675.
[47]. Bravo C, Moshou D, West J S, McCartney H A, Ramon H. Early Disease Detection in Wheat Fields using Spectral Reflectance. Biosystems Engineering. 2003, 84(2): 137-145
[48]. Broge N H, Lebianc E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy cholorophyll density. Remote sensing of Environment, 2000, 76: 156-172.
[49]. Buschmann C, Lichtenthaler HK. Reflectance and chlorophyll fluorescence signatures in leaves. In: Lichetnthaler HK, ed. Applications of Chlorophyll Fluorescence. Kluwer Academic Publishers, Dordrecht. 1998, 325-332.
[50]. Campbell P K E, Middleton E M, Corp L A, McMurtrey J E, Kim M S, Chappelle E W, Butcher L M. Contribution of chlorophyll fluorescence to the reflectance of com foliage, Proceedings, International Geoscience and Remote Sensing Symposium, IGARSS 2002, Toronto, Canada, 3 pp., CD-ROM 6/24/2002.
[51]. Carter G A, Jones J H, Mitchell R J, et al. Detection of Solar-Excited Chlorophyll a Fluorescence and Leaf Photosynthetic Capacity Using a Fraunhofer Line Radiometer. Remote Sensing of Environment, 1996, 55(1): 89-92.
[52]. Carter G A. Primary and secondary effects of water content on the spectral reflectance of leaves. American Journal of Botany, 1991, 78(7): 916-924.
[53]. Cassanova D, Epema GF, Goudriaan J. Monitoring rice reflectance at field level for estimating biomass and LAI. Field Crops Res, 1998, 55, 83-92.
[54]. Ceccato P, Flasse S, Gregoire M J, Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications. Remote Sensing of Environment, 2002, 82: 198-207.
[55]. Cecchi G, Lognoli D, Mochi I, Palombi L, Petrini E, Raimondi V. A High Spectral Resolution Sensor for Active and Passive Remote Sensing of Vegetation Fluorescence. IGARSS 2003 IEEE Proceedings, 1: 591-593.
[56]. Cerovic Z G, Goulas Y, Gorbunov M, Briantais J M, Camenen L, Moya I. Fluorosensing of water stress in plants: Diurnal changes of the mean lifetime and yield of chlorophyll fluorescence, measured simultaneously and at distance with a τ-LIDAR and a modified PAM-fluorimeter, in maize, sugar beet and Kalanchoe. Remote Sens Environ, 1996, 58: 311-321.
[57]. Chappelle E W, Wood F M, McMurtrey J E, Newcomb W W. Laser-induced fluorescence of green plants 1: a technique for the remote detection of plants stress and species differentiation. Appl. Opt. 1984, 23(1): 134-138.
[58]. Ciompi S, Gentili E, Guidi L, et al. The effect of nitrogen deficiency on leaf gas exchange and chlorophyll fluorescence parameters. Plant Sci, 1996, 118: 177-184.
[59]. Corp L A, McMurtrey J E, Middleton E W, et al. Fluorescence sensing systems: In vivo detection of biophysical variations in field corn due to nitrogen supply. Remote Sensing of Environment 2003, 86: 470-479.
[60]. Curran P J, Dungan J L, Gholz H L. Explorong the Relationship Between Reflectance Red Edge and Chlorophyll Content in Slash Pine. Tree Physiology, 1990, 7: 33-38.
[61]. Danson F M, Steven M D, Maltlius T J, Clark J A. High-spectral resolution data for determining leaf water concentration. International Journal of Remote Sensing, 1992, 13: 461-470.
[62]. Demmig-Adams B, Adams W W. Photoprotection and other responses of plants to high light stress. Annual Review of Plant Physiology and Plant Molecular Biology. 1992, 43: 599-626.
[63]. Dobrowski S Z, Pushnik J C, Zarco-Tejada P J, Ustin S L. Simple reflectance indices track heat and water stress induced changes in steady state chlorophyll fluorescence. Remote Sensing of Environment, 2005, 97(3), 403-414.
[64]. Doerffer R, Sorensen K, Aiken J. MERIS potential for coastal zone applications. Intl. J. Remote Sens, 1999, 20(9): 1809-1818.
[65]. Elachi C 著。遥感的物理学和技术概论。气象出版社,1995.
[66]. Evain S, Flexas J, Moya I. A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence. Remote Sensing of the Environment, 2004, 91: 175-185.
[67]. Fernandez S, Vidal D, Simon E, Sole S L. Radiometric characteristics of triticum aestivum cv. Astral under water and nitrogen stress. International Journal of Remote Sensing, 1994, 15 (9): 1867-1884.
[68]. Flesas J, Briantais J M, Cerovic Z, Medrano H, Moya I. Steady-state and maximum chlorophyll fluorescence responses to water stress in grapevine leaves: a new remote sensing system. Remote Sensing of the Environment, 2000, 73: 283-297.
[69]. Flexas J, Escalona J M, Evain S, Gulias J, Moya I, Osmond CB, Medrano H. Steady-state chlorophyll fluorescence (Fs) measurements as a tool to follow variations of net CO_2 assimilation and stomatal conductance during water-stress in C3 plants. Physiol Plant, 2002, 114(2): 231-240.
[70]. Gamon J A, Surfus J S. Assessing leaf pigment content and activity with a reflectometer. New Phytol, 1999, 143: 105-117.
[71]. Gamon J A, Penuelas J, Field C B. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment, 1992, 41:35-35
[72]. Gamon J A, Serrano L, Surfus J. The photochemical reflectance index: An optical indicator of photosynthetic radiation-use efficiency across species, functional types and nutrient levels. Oecologia (Berlin), 1997, 112:492-501.
[73]. Genty B, Briantais J M, Baker N R. The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochim Biophys Acta, 1989, 990: 87-92.
[74]. Gitelson A A, Buschmann C, Lichtenthaler H K. Leaf chlorophyll fluorescence corrected for re-absorption by means of absorption and reflectance measurements. J Plant Physiol, 1998, 152: 283-296.
[75]. Hartmut K. Lichtenthalera, Fatbardha Babania. Detection of photosynthetic activity and water stress by imaging the red chlorophyll fluorescence. Plant Physiol. Biochem, 2000, 38: 889-895.
[76]. http://ipp.nasa.gov/innovation/innovation_93/6-sb-pfsensor.html
[77]. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod22.pdf
[78]. http://www.esa.int/esaLP/ESA56BVTYWC_index_0.htm
[79]. http://www.esrin.esa.it/esaLP/SEMXIDYDE2E_index_2.html
[80]. Inoue Y, Morinaga S, Shibayama M. Non-destructive estimation of water status of intact crop leaves based on spectral reflectance measurements. Japanese Journal of Crop Science, 1993, 62: 462-469.
[81]. Kebabian P L, Theisen A F, Kallelis S, Freedman A. A passive two-band sensor of sunlight-excited plant fluorescence. Review of Scientific Instruments, 1999, 70(11): 4386-4393.
[82]. Kim M S, Chappelle E W, Corp L, McMurtrey E. The Contribution of Chlorophyll Fluorescence to the Reflectance Spectra of Green Vegetation, International Geoscience and Remote Sensing Symposium, Tokyo, Japan, 1993, Aug 18-21, Vol. 3, pp. 1321-1324.
[83]. Kokaly R F. Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration. Remote Sensing of Environment, 2001, 75: 153-161.
[84].Krause and Weis. Chlorophyll Fluorescence and Photosynthesis: The Basic, Annu. Rev. Plant Physiol. Plant Mol.l991.42:313-349.
[85].Lichtenthaler H K, Wenzel O, Buschmann C, Gitelson A A. Plant Stress Detection by Reflectance and Fluorescence. Ann NY Acad Sci, 1998, 851: 271-285.
[86].Lichtenthaler H K, Lang M, Sowinska M, Heise F, Miehe J A. Detection of vegetation stress via a new high resolution fluorescence imaging system. J. Plant Physiol., 1996, 148:599-612
[87].Lichtenthaler H K, MiehéJA. Fluorescence imaging as a diagnostic tool for plant stress. Trends Plant Sci, 1997, 2: 316-320.
[88].Lichtenthaler H K. Possibilities for Remote Sensing of Terrestrial Vegetation by a combination of Reflectance and Laser-induced Chlorophyll Fluorescence. Proceedings of IGARRS '89 /12th Can. Symp. On Remote Sensing, Vancouver, B.C. 1989, 1349-1354.
[89].LI-COR Inc. LI-1800 portable spectroradiometer instruction manual. Publication No. 8210-0030. Nebraska USA. 1989.
[90]. Louis J, Ounis A, Ducruet J M., Evain S, Laurila T, Thum T, Aurela M, Wingsle G, Alonso L, Pedros R, Moya I. Remote sensing of sunlight-induced chlorophyll fluorescence and reflectance of Scots pine in the boreal forest during spring recovery. Remote Sensing Of Environment, 2005, 96(1): 37-48.
[91].Lu Q T, Li W H, Jiang G M, Ge Q Y, Hao N B, Sun J Z, Guo R J. Studies on the characteristics of chlorophyll fluorescence of winter wheat flag leaves at different developing stages.Acta Botanica Sinica,2001, 43(8):801-804.
[92].Lüdeker W, Dahn H G, Gtlnther K P, Schulz H. Laser-induced fluorescence-A method to detect the vitality of Scots pines. Remote Sens. Environ, 1999, 68:225-236.
[93].Maxwell K, Johnson G N. Chlorophyll fluorescence - a practical guide. J Exp Bot, 2000, 345: 659-668.
[94].Mcfarlane J C, Watson R D, Theisen A F, et al. Plant Stress Detection By Remote Measurement of Fluorescence. Applied Optics, 1980, 19(19), 3287-3289.
[95].McMurtrey J E, Chappelle E W, Kim M S, et al. Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectancemeasurements. Remote Sens. Environ, 1994, 47:36-44.
[96].McMurtrey J E, Middleton E M, Corp L A, Campbell PKE, Butcher L M, Daughtry CST. Optical reflectance and fluorescence for detecting nitrogen needs in Zea mays L. IGARSSProceedings, 2003, 7, 4602-4604.
[97].Methy M. Analysis of photosynthetic activity at the leaf and canopy levels from reflectance measurements: a case study. Photosynthetica, 2000, 38: 505-512.
[98].Meyer S, Cartelat A, Moya I, Cerovic Z G. UV-induced blue-green and far-red fluorescence along wheat leaves: a potential signature of leaf ageing. Journal of Experimental Botany, 2003, 54 (383): 757-768.
[99].Middleton E M, McMurtrey J E, Entcheva Campbell P K, Corp L A, Butcher L M, Chappelle E W. Foliar Reflectance and Fluorescence Responses for Plants Under Nitrogen Stress. Geoscience and Remote Sensing Symposium, 2003. IEEE International Volume 1, 21-25 July 2003: 594-597.
[100]. Moshou D, Bravo C, Oberti R, West J, Bodria L, McCartney A, Ramon H. Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps. Real Time Imaging Ⅱ. 2005: 75-83.
[101]. Moshou D, Bravo C, West J S , Wahlen S , Mccartney H A, Ramon H. Automatic detection of 'yellow rust' in wheat using reflectance measurements and neural networks. Computers and Electronics in Agriculture, 2004, 44: 173-188.
[102]. Moya I, Camenen L, Evain S, Goulas Y, Cerovic Z G, Latouche G, Flexas J, Ounis A. A new instrument for passive remote sensing 1. Measurements of sunlight～induced chlorophyll fluorescence. Remote Sensing of Environment, 2004, 91: 186-197.
[103]. Moya I, Cartelat A, Cerovic Z G, et al. Possible Approaches to Remote Sensing of Photosynthetic Activity. IEEE International Geoscience and Remote Sensing Symposium, 2003, 1: 588-590.
[104]. Norikane J, Goto E, Kurata K, Takakura T. A new relative referencing method for crop monitoring using chlorophyll fluorescence. Adv Space Res. 2003, 31(1): 245-248.
[105]. Oliose A, Methy M, Lacaze B. Simulation of canopy fluorescence as a function of canopy structure and leaf fluorescence. Remote Sens. Environ, 1992, 41: 239-247.
[106]. Ounis A, Cerovic Z G, Briantais J M, Moya I. Dual excitation FLIDAR for the estimation of epidermal UV absorption in leaves and canopies. Remote Sens Environ, 2001, 76: 33-48.
[107]. Penuelas J, Filella I, Biel C, et al. The reflectance at the 950～970 nm region as an indicator of plant water status. International Journal of Remote Sensing, 1993, 14(10): 1887～1905.
[108]. Penuelas J, Inoue Y. Reflectance indices indicative of changes in water and pigment contents of peanut and wheat leaves. Photosynthetica, 1999, 36(3): 355-360.
[109]. Penuelas J, Llusia J, Pinol J, Filella I. Photochemical reflectance index and leaf photosynthetic radiation-use efficiency assessment in Mediterranean trees. International Journal of Remote Sensing, 1997, 18(13): 2863-2868.
[110]. Penuelas J, Filella I, Gamon J A. Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytol, 1995, 131: 291-296.
[111]. Penuelas J, Gamon J A, Fredeen A L, Merino J, Field C B. Reflectance indices associated with physiological changes in nitrogen-and water-limited sunflower leaves. Remote Sens. Environ, 1994, 48, 135-146.
[112]. Perez-Priego O, Zarco-Tejada P J, Miller J R, Sepulcre-Cant6G, Fereres E. Detection of Water Stress in Orchard Trees with a High-Resolution Spectrometer through Chlorophyll Fluorescence in-filling of the O2-A band. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(12): 2860-2869.
[113]. Peterson R B, Aylor D E. Chlorophyll fluorescence induction in leaves of Phaseolus vulgaris infected with bean rust (Uromyces appendiculatus). Plant Physiology, 1995, 108: 163-171.
[114]. Pfundel E. Estimating the contribution of photosyntem I to total leaf chlorophyll fluorescence. Photosynth. Res, 1998, 56: 185-195.
[115]. Plascyk J A, Gabriel F C. The Fraunhofer line discriminator MKⅡ—an airborne instrument for precise and standardized ecological luminescence measurements. IEEE Transactions on Instrumentation and Measurement, 1975, 24, 306-313.
[116]. Richard B, Peterson & Evelyn A, Havir. The multiphasic nature of nonphotochemical quenching: implications for assessment of photosynthetic electron transport based on chlorophyll fluorescence. Photosynthesis Research, 2004, 82: 95-107.
[117]. Rosema A, Zahn. H. Laser pulse energy requirements for remote sensing of chlorophyll fluorescence. Remote sensing of Rnvironment, 1997, 62:101-108.
[118]. Running S W, Nemani R R. Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates. Remote Sensing of Environment, 1988, 24: 347-367.
[119]. Saito Y, Yajima K, Kobayashi F, Nomura A, Suzuki T. Image detection of solar-induced plant fluorescence. Geoscience and Remote Sensing Symposium, 2003, (l):607 - 609.
[120]. Schreiber U, Bilger W, Neubauer C. Chlorophyll fluorescence as a non-intrusive indicator for rapid assessment of in vivo photosynthesis. In: Schreiber U, ed. Caldwell MM, ed. Ecophysiology of photosynthesis. Springer-Verlag, Berlin. 1994. pp. 49-70.
[121]. Schuerger A C, Capelle G A, Di Benedetto J A, et a.l Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection of zinc stress and chlorophyll concentration in bahia grass. Remote Sensing of Environment, 2003, 84:572-588.
[122]. Shibayama M, AkiyamaT. A spectroradiometer for field use. Ⅶ. Radiometric estimation of nitrogen levels in field rice canopies. Japanese Journal of Crop Science, 1986, 55(4): 439-445.
[123]. Smith K L, Steven M D, Colls J J. Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks. Remote Sensing of Environment, 2004, 92 :207-217.
[124]. Smorenburg K, Bazalgette Courrèges-Lacoste G, Berger M., Buschmann C, et al. Remote sensing of solar induced fluorescence of vegetation. PROC.SPIE, 2002,4542:178-190.
[125]. Stone M L, Solie J B, Raun W R, Whitney R W, Taylor S L, Ringer J D. Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Transaction of the ASAE 1996, 39(5): 1623-1631.
[126]. Subhash N, Mallia J R. Changes in laser induced chlorophyll fluorescence signatures during regeneration of Kacholam and Colocasia plants from water stress. IGARSS Proceedings 5, 2003: 3293-3295.
[127]. Subhash N, Wenzel O, Hartmut K, Lichtenthaler H K. Changes in blue-green and chlorophyll fluorescence emission and fluorescence ratios during senescence of tobacco plants. Remote Sensing of Environment, 1999, 69: 215-223.
[128]. Thenkabail P S, Smith R B, Pauw E D. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sens Environ, 2000, 71: 158～182.
[129]. Thomas J R, Namken L N, Oerther G F, Brown R G. Estimating leaf water content by reflectance measurement. Agronomy Journal, 1971, 63: 845-847.
[130]. Tsai F, Philpot W. Derivative analysis of hyperspectral data. Remote Sensing of Environment, 1998, 66: 41-51.
[131]. Vidaver W E, Lister G R. Brooke R C, Binder W D. A manual for the use of variable chlorophyll fluorescence in the assessment of the ecophysiology of conifer seedlings. FRDA Rep. 1991, 163, 60.
[132]. Wang K, Shen Z Q, Wang R C. Effects of nitrogen nutrition on the spectral reflectance characteristics of rice leaf and canopy. Journal of Zhejiang Agricultural University, 1998, 24: 93-97.
[133]. Winkel T, Me'thy M, The'not F. Radiation use efficiency, chlorophyll fluorescence, and reflectance indices associated with ontogenic changes in water-limited Chenopodium quinoa leaves. Photosynthetica, 2002, 40: 227-232.
[134]. Yoder B J, Pettigrew-Crosby E P. Predictiing nitrogen and chlorophyll content and concentrations form reflectance spectra (400-2500 nm) at leaf and canopy scales. Remote Sensing of Environment, 1995, 53: 199-211.
[135]. Zarco-Tejada P J, Miller J R, Mohammed G H, et al. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment, 2000, 74: 582-595.
[136]. Zarco-Tejada P J, Miller J R, Gina H, Mohammed, et al. Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: Ⅱ. Laboratory and Airborne Canopy-Level Measurements with Hyperspectral Data. Remote Sensing of Environment, 2000, 74: 596-608
[137]. Zarco-Tejada P J, Miller J R, Mohammed G H, et al. Vegetation stress detection through chlorophyll a+b estimation and fluorescence effects on hyperspectral imagery. J. Environ. Qual. 2002, 31: 1433-1441.
[138]. Zarco-Tejada P J, Miller J R, Mohammed G H, Noland T L. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment, 2000, 74: 582-595.
[139]. Zarco-Tejada P J, Miller J R, Mohammed G H. Chlorophyll Fluorescence effects on Leaf and Canopy Reflectance: Experimental Results and Model Simulation. First Workshop on Remote Sensing of Solar Induced Fluorescence, ESA/ESTEC, Noordwiik, The Netherlands, 19-20 June 2002.
[140]. Zarco-Tejada P J, Miller J R, Mohammed G H, Noland T L, Sampson P H. Estimation of chlorophyll fluorescence under natural illumination from hyperspectral data. Int. J. Appl. Earth Observ. Geoinfo. 2001, 3:321-327.
[141]. Zarco-Tejada P J, Pushnik J, Dobrowsk S, Ustin S L, Steady-state chlorophyll a Fluorescence detection from canopy derivative reflectance and Double-Peak Red-Edge effects. Remote Sensing of Environment, 2003, 84(2), 283-294.
[142]. Zhang L, Dickinson M. Fluorescence from rust fungi: a simple and effective method to monitor the dynamics of fungal growth in planta. Physiological and Molecular Plant Patholog,2001,59:137-141.
[143]. Zhao C M, Wang G X. Effects of Drought Stress on the Photoprotection in Ammopiptanthus mongolicus Leaves. Acta Botanica Sinica, 2002, 44(11):1309-1313.
[144]. Zhumar A Yu. Use of narrow-band spectra to detect rust diseases of wheat crops. IGARSS Proceedings, 1999:794-796.
[2].范燕萍,余让才,陈建勋,杨瑞陶。氮素营养胁迫对匙叶天南星生长及光合特性的影响.园艺学报,2000,27(4):297-299.
[3].冯志立,冯玉龙,曹坤芳。光强对砂仁叶片光合作用光抑制及热耗散的影响。植物生态学报,2002,26(1):77-82.
[4].黄木易,黄义德,黄文江,刘良云,王纪华,万安民。冬小麦条锈病生理变化及其遥感机理。安徽农业科学,2004,32(1):132-134.
[5].黄木易,王纪华,黄文江,黄义德,赵春江,万安民。冬小麦条锈病的光谱特征及遥感监测。农业工程学报,2003,19(6):154-158.
[6].黄文江,王纪华,刘良云,赵春江,杜小鸿。冬小麦红边参数变化规律及其营养诊断,遥感技术与应用,2003,18(4):206-211.
[7].李德成,徐彬彬,石晓日,张崇静,吴荣。模拟酸雨对水稻叶片荧光光谱特性的影响。中国环境科学,1998,18(6):498-500.
[8].李云梅,倪绍祥,黄敬峰。高光谱数据探讨水稻叶片叶绿素含量对叶片及冠层光谱反射特性的影响。遥感技术与应用,2003,18(1):1-5.
[9].林世青,许春辉,张其德,徐黎,毛大璋,匡廷云.叶绿素荧光动力学在植物抗性生理学、生态学和农业现代化中的应用.植物学报,1992,9(1):1-16.
[10].刘良云,黄木易,黄文江,王纪华,赵春江,郑兰芬,童庆禧。利用多时相的高光谱航空图像监测冬小麦条锈病。遥感学报,2004,8(3):275-281.
[11].刘良云。高光谱遥感在精准农业中的应用研究,中国科学院遥感应用研究所博士后研究工作报告,2002.
[12].刘伟东,项月琴,郑兰芬,童庆禧,吴长山。高光谱数据与水稻叶面积值数及叶绿素密度的相关分析。遥感学报,2000,4(4):279-283.
[13].卢从明,张其德,匡廷云。水分胁迫对小麦光系统Ⅱ的影响。植物学报,1994,36(2):93-98.
[14].卢艳丽。小麦株型与氮素营养品质的遥感监测。中国农业科学院博士学位论文,2005年6月.
[15].罗俊,张木清,吕建林,林彦铨。水分胁迫对不同甘蔗品种叶绿素a荧光动力学的影响。福建农业大学学报,2000,29(1):18-22.
[16].沈玉其,徐彬彬,石晓日,李德成,周斌,朱永豪,张崇静,吴荣,刘南英。关于植被激光荧光遥感的若干基本问题。环境遥感,1992,7(增):22-33.
[17].石晓日,徐彬彬,李德成,周斌,沈玉其,朱永豪,张崇静,吴荣,刘南英。土壤激光诱导荧光遥感研究初探。环境遥感,1992,7(增):15-21.
[18].唐延林,王秀珍,黄敬峰,王人潮。水稻微分光谱和植被指数的作用探讨。农业工程学报,2003,19(1):145-150.
[19].田庆久,宫鹏,赵春江,郭晓维。用光谱反射率诊断小麦水分状况的可行性分析,科学 通报,2000。45(24):2645-2650.
[20].王坷,沈掌泉,王人潮。应用荧光光谱特征监测水稻钾营养的可行性研究。:朱军主编,生命科学研究与应用,浙江大学出版社,1996,571.
[21].王可玢,许春辉,赵福洪,唐崇欣,戴云玲.水分胁迫对小麦旗叶某些体内叶绿素a荧光参数的影响.生物物理学报,1997,13(2):273-278.
[22].王茜,魏光辉。机油产品激光诱导荧光特性的研究。光子学报,2001,30(10):1289-1291.
[23].王人潮,陈铭臻,蒋亨显。水稻遥感估产的农学机理研究。Ⅰ。不同氮素水平的水稻光谱特征及其敏感波段的选择。浙江农业大学学报,1993 19(增刊):7-14.
[24].王人潮,蒋亨显,王珂,沈掌泉。论中国农业遥感与信息技术发展战略。科技通报,1999,15(1):1-7.
[25].王秀珍,王人潮,黄敬峰。微分光谱遥感及其在水稻农学参数测定上的应用研究。农业工程学报,2002,18(1):9-13.
[26].王之杰。冬小麦冠层氮素分布与品质遥感的研究。中国农业大学博士学位论文,2004年5月.
[27].吴长山,项月琴,郑兰芬,童庆禧。利用高光谱数据对作物群体叶绿素密度的研究。遥感学报,2000,4(3):228-232.
[28].夏达英,王振先,张士魁。荧光技术在海洋环境学上的应用研究,1999,21(3):66-72
[29].徐彬彬,石晓日,李德成。模拟酸雨对大豆的激光诱导荧光光谱和反射光谱的影响研究。土壤,2000(3):113-119.
[30].徐德聪,吕芳德,栗彬,蒋瑶。不同立地美国山核桃叶绿素荧光特性及叶性状比较。经济林研究 2005,23(4):17-20.
[31].许长成,李德全,邹琦,张建华.干旱条件下冬小麦不同叶龄叶绿素荧光及叶黄素循环组分的变化.植物生理学报,1999,25(1):29-37.
[32].薛利红,罗卫红,曹卫星,田永超。作物水分和氮素光谱诊断研究进展。遥感学报,2003,7(1):73-80.
[33].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。世界地质,2001,20(3):307-312.
[34].杨敏华。面向精准农业的高光谱遥感作物信息获取。中国农业大学博士学位论文,2002,6.
[35].张守仁。叶绿素荧光动力学参数的意义及讨论。植物学通报,1999,16(4):444-448.
[36].张霞,刘良云,赵春江,张兵。利用高光谱遥感图像估算小麦氮含量。遥感学报,2003,7(3):176～179.
[37].赵春江,黄文江,王纪华,杨敏华,薛绪掌。不同品种、肥水条件下冬小麦光谱红边参数研究。中国农业科学,2002,35(8):980-987.
[38].赵春江,黄文江,王之杰,王北洪,王纪华。不同水肥处理下冬小麦冠层含水率与温度关系的研究。农业工程学报,2002,18(2):25-28.
[39].赵英时等编著。遥感应用分析原理与方法。科学出版社。2003
[40].朱永豪,张崇静,吴荣,刘南英,沈玉其,徐彬彬,石晓日,李德成,周斌。激光荧光 技术用于地物遥感的可能性研究。环境遥感,1992,7(增):1-7.
[41]. Agati G, Cerovic Z, Moya I. The effect of temperature on chlorophyll fluorescence: the role of PSI in 735 nm fluorescence. Photochem. Photobiol, 2000, 72: 75-84.
[42]. Alonso L, Moreno J, Moya I, Miller J R. A comparison of different techniques for passive measurement of vegetation photosynthetic activity: solar-induced fluorescence, red-edge reflectance structure and photochemical reflectance indices. IEEE International Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 1: 604-606.
[43]. Barbini R, Colao F, Fantoni R, Micheli C, Palucci A, Ribezzo S. Design and application of a lidar fluorosensor system for remote monitoring of phytoplankton. ICES Journal of Marine Science, 1998, 55: 793-802.
[44]. Bassanezi R B, Amorim L, Bergamin Filho A, Berger R D. Gas exchange and emission of chlorophyll fluorescence during the monocycle of rust, angular leaf spot and anthracnose on bean leaves as a function of their trophic characteristics. Journal of Phytopathology, 2002, 150: 37-47.
[45]. Berges J A, Charlebois D O, Mauzerall D C, et al. Differential Effects of nitrogen limitation on photosynthetic efficiency of photosystems Ⅰ and Ⅱ in microalgae. Plant Physiol, 1996, 110: 689-696.
[46]. Blackburn G A. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leave. Int. J. Remote Sens. 1998, 19(4): 657-675.
[47]. Bravo C, Moshou D, West J S, McCartney H A, Ramon H. Early Disease Detection in Wheat Fields using Spectral Reflectance. Biosystems Engineering. 2003, 84(2): 137-145
[48]. Broge N H, Lebianc E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy cholorophyll density. Remote sensing of Environment, 2000, 76: 156-172.
[49]. Buschmann C, Lichtenthaler HK. Reflectance and chlorophyll fluorescence signatures in leaves. In: Lichetnthaler HK, ed. Applications of Chlorophyll Fluorescence. Kluwer Academic Publishers, Dordrecht. 1998, 325-332.
[50]. Campbell P K E, Middleton E M, Corp L A, McMurtrey J E, Kim M S, Chappelle E W, Butcher L M. Contribution of chlorophyll fluorescence to the reflectance of com foliage, Proceedings, International Geoscience and Remote Sensing Symposium, IGARSS 2002, Toronto, Canada, 3 pp., CD-ROM 6/24/2002.
[51]. Carter G A, Jones J H, Mitchell R J, et al. Detection of Solar-Excited Chlorophyll a Fluorescence and Leaf Photosynthetic Capacity Using a Fraunhofer Line Radiometer. Remote Sensing of Environment, 1996, 55(1): 89-92.
[52]. Carter G A. Primary and secondary effects of water content on the spectral reflectance of leaves. American Journal of Botany, 1991, 78(7): 916-924.
[53]. Cassanova D, Epema GF, Goudriaan J. Monitoring rice reflectance at field level for estimating biomass and LAI. Field Crops Res, 1998, 55, 83-92.
[54]. Ceccato P, Flasse S, Gregoire M J, Designing a spectral index to estimate vegetation water content from remote sensing data: Part 2. Validation and applications. Remote Sensing of Environment, 2002, 82: 198-207.
[55]. Cecchi G, Lognoli D, Mochi I, Palombi L, Petrini E, Raimondi V. A High Spectral Resolution Sensor for Active and Passive Remote Sensing of Vegetation Fluorescence. IGARSS 2003 IEEE Proceedings, 1: 591-593.
[56]. Cerovic Z G, Goulas Y, Gorbunov M, Briantais J M, Camenen L, Moya I. Fluorosensing of water stress in plants: Diurnal changes of the mean lifetime and yield of chlorophyll fluorescence, measured simultaneously and at distance with a τ-LIDAR and a modified PAM-fluorimeter, in maize, sugar beet and Kalanchoe. Remote Sens Environ, 1996, 58: 311-321.
[57]. Chappelle E W, Wood F M, McMurtrey J E, Newcomb W W. Laser-induced fluorescence of green plants 1: a technique for the remote detection of plants stress and species differentiation. Appl. Opt. 1984, 23(1): 134-138.
[58]. Ciompi S, Gentili E, Guidi L, et al. The effect of nitrogen deficiency on leaf gas exchange and chlorophyll fluorescence parameters. Plant Sci, 1996, 118: 177-184.
[59]. Corp L A, McMurtrey J E, Middleton E W, et al. Fluorescence sensing systems: In vivo detection of biophysical variations in field corn due to nitrogen supply. Remote Sensing of Environment 2003, 86: 470-479.
[60]. Curran P J, Dungan J L, Gholz H L. Explorong the Relationship Between Reflectance Red Edge and Chlorophyll Content in Slash Pine. Tree Physiology, 1990, 7: 33-38.
[61]. Danson F M, Steven M D, Maltlius T J, Clark J A. High-spectral resolution data for determining leaf water concentration. International Journal of Remote Sensing, 1992, 13: 461-470.
[62]. Demmig-Adams B, Adams W W. Photoprotection and other responses of plants to high light stress. Annual Review of Plant Physiology and Plant Molecular Biology. 1992, 43: 599-626.
[63]. Dobrowski S Z, Pushnik J C, Zarco-Tejada P J, Ustin S L. Simple reflectance indices track heat and water stress induced changes in steady state chlorophyll fluorescence. Remote Sensing of Environment, 2005, 97(3), 403-414.
[64]. Doerffer R, Sorensen K, Aiken J. MERIS potential for coastal zone applications. Intl. J. Remote Sens, 1999, 20(9): 1809-1818.
[65]. Elachi C 著。遥感的物理学和技术概论。气象出版社,1995.
[66]. Evain S, Flexas J, Moya I. A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence. Remote Sensing of the Environment, 2004, 91: 175-185.
[67]. Fernandez S, Vidal D, Simon E, Sole S L. Radiometric characteristics of triticum aestivum cv. Astral under water and nitrogen stress. International Journal of Remote Sensing, 1994, 15 (9): 1867-1884.
[68]. Flesas J, Briantais J M, Cerovic Z, Medrano H, Moya I. Steady-state and maximum chlorophyll fluorescence responses to water stress in grapevine leaves: a new remote sensing system. Remote Sensing of the Environment, 2000, 73: 283-297.
[69]. Flexas J, Escalona J M, Evain S, Gulias J, Moya I, Osmond CB, Medrano H. Steady-state chlorophyll fluorescence (Fs) measurements as a tool to follow variations of net CO_2 assimilation and stomatal conductance during water-stress in C3 plants. Physiol Plant, 2002, 114(2): 231-240.
[70]. Gamon J A, Surfus J S. Assessing leaf pigment content and activity with a reflectometer. New Phytol, 1999, 143: 105-117.
[71]. Gamon J A, Penuelas J, Field C B. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment, 1992, 41:35-35
[72]. Gamon J A, Serrano L, Surfus J. The photochemical reflectance index: An optical indicator of photosynthetic radiation-use efficiency across species, functional types and nutrient levels. Oecologia (Berlin), 1997, 112:492-501.
[73]. Genty B, Briantais J M, Baker N R. The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochim Biophys Acta, 1989, 990: 87-92.
[74]. Gitelson A A, Buschmann C, Lichtenthaler H K. Leaf chlorophyll fluorescence corrected for re-absorption by means of absorption and reflectance measurements. J Plant Physiol, 1998, 152: 283-296.
[75]. Hartmut K. Lichtenthalera, Fatbardha Babania. Detection of photosynthetic activity and water stress by imaging the red chlorophyll fluorescence. Plant Physiol. Biochem, 2000, 38: 889-895.
[76]. http://ipp.nasa.gov/innovation/innovation_93/6-sb-pfsensor.html
[77]. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod22.pdf
[78]. http://www.esa.int/esaLP/ESA56BVTYWC_index_0.htm
[79]. http://www.esrin.esa.it/esaLP/SEMXIDYDE2E_index_2.html
[80]. Inoue Y, Morinaga S, Shibayama M. Non-destructive estimation of water status of intact crop leaves based on spectral reflectance measurements. Japanese Journal of Crop Science, 1993, 62: 462-469.
[81]. Kebabian P L, Theisen A F, Kallelis S, Freedman A. A passive two-band sensor of sunlight-excited plant fluorescence. Review of Scientific Instruments, 1999, 70(11): 4386-4393.
[82]. Kim M S, Chappelle E W, Corp L, McMurtrey E. The Contribution of Chlorophyll Fluorescence to the Reflectance Spectra of Green Vegetation, International Geoscience and Remote Sensing Symposium, Tokyo, Japan, 1993, Aug 18-21, Vol. 3, pp. 1321-1324.
[83]. Kokaly R F. Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration. Remote Sensing of Environment, 2001, 75: 153-161.
[84].Krause and Weis. Chlorophyll Fluorescence and Photosynthesis: The Basic, Annu. Rev. Plant Physiol. Plant Mol.l991.42:313-349.
[85].Lichtenthaler H K, Wenzel O, Buschmann C, Gitelson A A. Plant Stress Detection by Reflectance and Fluorescence. Ann NY Acad Sci, 1998, 851: 271-285.
[86].Lichtenthaler H K, Lang M, Sowinska M, Heise F, Miehe J A. Detection of vegetation stress via a new high resolution fluorescence imaging system. J. Plant Physiol., 1996, 148:599-612
[87].Lichtenthaler H K, MiehéJA. Fluorescence imaging as a diagnostic tool for plant stress. Trends Plant Sci, 1997, 2: 316-320.
[88].Lichtenthaler H K. Possibilities for Remote Sensing of Terrestrial Vegetation by a combination of Reflectance and Laser-induced Chlorophyll Fluorescence. Proceedings of IGARRS '89 /12th Can. Symp. On Remote Sensing, Vancouver, B.C. 1989, 1349-1354.
[89].LI-COR Inc. LI-1800 portable spectroradiometer instruction manual. Publication No. 8210-0030. Nebraska USA. 1989.
[90]. Louis J, Ounis A, Ducruet J M., Evain S, Laurila T, Thum T, Aurela M, Wingsle G, Alonso L, Pedros R, Moya I. Remote sensing of sunlight-induced chlorophyll fluorescence and reflectance of Scots pine in the boreal forest during spring recovery. Remote Sensing Of Environment, 2005, 96(1): 37-48.
[91].Lu Q T, Li W H, Jiang G M, Ge Q Y, Hao N B, Sun J Z, Guo R J. Studies on the characteristics of chlorophyll fluorescence of winter wheat flag leaves at different developing stages.Acta Botanica Sinica,2001, 43(8):801-804.
[92].Lüdeker W, Dahn H G, Gtlnther K P, Schulz H. Laser-induced fluorescence-A method to detect the vitality of Scots pines. Remote Sens. Environ, 1999, 68:225-236.
[93].Maxwell K, Johnson G N. Chlorophyll fluorescence - a practical guide. J Exp Bot, 2000, 345: 659-668.
[94].Mcfarlane J C, Watson R D, Theisen A F, et al. Plant Stress Detection By Remote Measurement of Fluorescence. Applied Optics, 1980, 19(19), 3287-3289.
[95].McMurtrey J E, Chappelle E W, Kim M S, et al. Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectancemeasurements. Remote Sens. Environ, 1994, 47:36-44.
[96].McMurtrey J E, Middleton E M, Corp L A, Campbell PKE, Butcher L M, Daughtry CST. Optical reflectance and fluorescence for detecting nitrogen needs in Zea mays L. IGARSSProceedings, 2003, 7, 4602-4604.
[97].Methy M. Analysis of photosynthetic activity at the leaf and canopy levels from reflectance measurements: a case study. Photosynthetica, 2000, 38: 505-512.
[98].Meyer S, Cartelat A, Moya I, Cerovic Z G. UV-induced blue-green and far-red fluorescence along wheat leaves: a potential signature of leaf ageing. Journal of Experimental Botany, 2003, 54 (383): 757-768.
[99].Middleton E M, McMurtrey J E, Entcheva Campbell P K, Corp L A, Butcher L M, Chappelle E W. Foliar Reflectance and Fluorescence Responses for Plants Under Nitrogen Stress. Geoscience and Remote Sensing Symposium, 2003. IEEE International Volume 1, 21-25 July 2003: 594-597.
[100]. Moshou D, Bravo C, Oberti R, West J, Bodria L, McCartney A, Ramon H. Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps. Real Time Imaging Ⅱ. 2005: 75-83.
[101]. Moshou D, Bravo C, West J S , Wahlen S , Mccartney H A, Ramon H. Automatic detection of 'yellow rust' in wheat using reflectance measurements and neural networks. Computers and Electronics in Agriculture, 2004, 44: 173-188.
[102]. Moya I, Camenen L, Evain S, Goulas Y, Cerovic Z G, Latouche G, Flexas J, Ounis A. A new instrument for passive remote sensing 1. Measurements of sunlight～induced chlorophyll fluorescence. Remote Sensing of Environment, 2004, 91: 186-197.
[103]. Moya I, Cartelat A, Cerovic Z G, et al. Possible Approaches to Remote Sensing of Photosynthetic Activity. IEEE International Geoscience and Remote Sensing Symposium, 2003, 1: 588-590.
[104]. Norikane J, Goto E, Kurata K, Takakura T. A new relative referencing method for crop monitoring using chlorophyll fluorescence. Adv Space Res. 2003, 31(1): 245-248.
[105]. Oliose A, Methy M, Lacaze B. Simulation of canopy fluorescence as a function of canopy structure and leaf fluorescence. Remote Sens. Environ, 1992, 41: 239-247.
[106]. Ounis A, Cerovic Z G, Briantais J M, Moya I. Dual excitation FLIDAR for the estimation of epidermal UV absorption in leaves and canopies. Remote Sens Environ, 2001, 76: 33-48.
[107]. Penuelas J, Filella I, Biel C, et al. The reflectance at the 950～970 nm region as an indicator of plant water status. International Journal of Remote Sensing, 1993, 14(10): 1887～1905.
[108]. Penuelas J, Inoue Y. Reflectance indices indicative of changes in water and pigment contents of peanut and wheat leaves. Photosynthetica, 1999, 36(3): 355-360.
[109]. Penuelas J, Llusia J, Pinol J, Filella I. Photochemical reflectance index and leaf photosynthetic radiation-use efficiency assessment in Mediterranean trees. International Journal of Remote Sensing, 1997, 18(13): 2863-2868.
[110]. Penuelas J, Filella I, Gamon J A. Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytol, 1995, 131: 291-296.
[111]. Penuelas J, Gamon J A, Fredeen A L, Merino J, Field C B. Reflectance indices associated with physiological changes in nitrogen-and water-limited sunflower leaves. Remote Sens. Environ, 1994, 48, 135-146.
[112]. Perez-Priego O, Zarco-Tejada P J, Miller J R, Sepulcre-Cant6G, Fereres E. Detection of Water Stress in Orchard Trees with a High-Resolution Spectrometer through Chlorophyll Fluorescence in-filling of the O2-A band. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(12): 2860-2869.
[113]. Peterson R B, Aylor D E. Chlorophyll fluorescence induction in leaves of Phaseolus vulgaris infected with bean rust (Uromyces appendiculatus). Plant Physiology, 1995, 108: 163-171.
[114]. Pfundel E. Estimating the contribution of photosyntem I to total leaf chlorophyll fluorescence. Photosynth. Res, 1998, 56: 185-195.
[115]. Plascyk J A, Gabriel F C. The Fraunhofer line discriminator MKⅡ—an airborne instrument for precise and standardized ecological luminescence measurements. IEEE Transactions on Instrumentation and Measurement, 1975, 24, 306-313.
[116]. Richard B, Peterson & Evelyn A, Havir. The multiphasic nature of nonphotochemical quenching: implications for assessment of photosynthetic electron transport based on chlorophyll fluorescence. Photosynthesis Research, 2004, 82: 95-107.
[117]. Rosema A, Zahn. H. Laser pulse energy requirements for remote sensing of chlorophyll fluorescence. Remote sensing of Rnvironment, 1997, 62:101-108.
[118]. Running S W, Nemani R R. Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates. Remote Sensing of Environment, 1988, 24: 347-367.
[119]. Saito Y, Yajima K, Kobayashi F, Nomura A, Suzuki T. Image detection of solar-induced plant fluorescence. Geoscience and Remote Sensing Symposium, 2003, (l):607 - 609.
[120]. Schreiber U, Bilger W, Neubauer C. Chlorophyll fluorescence as a non-intrusive indicator for rapid assessment of in vivo photosynthesis. In: Schreiber U, ed. Caldwell MM, ed. Ecophysiology of photosynthesis. Springer-Verlag, Berlin. 1994. pp. 49-70.
[121]. Schuerger A C, Capelle G A, Di Benedetto J A, et a.l Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection of zinc stress and chlorophyll concentration in bahia grass. Remote Sensing of Environment, 2003, 84:572-588.
[122]. Shibayama M, AkiyamaT. A spectroradiometer for field use. Ⅶ. Radiometric estimation of nitrogen levels in field rice canopies. Japanese Journal of Crop Science, 1986, 55(4): 439-445.
[123]. Smith K L, Steven M D, Colls J J. Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks. Remote Sensing of Environment, 2004, 92 :207-217.
[124]. Smorenburg K, Bazalgette Courrèges-Lacoste G, Berger M., Buschmann C, et al. Remote sensing of solar induced fluorescence of vegetation. PROC.SPIE, 2002,4542:178-190.
[125]. Stone M L, Solie J B, Raun W R, Whitney R W, Taylor S L, Ringer J D. Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Transaction of the ASAE 1996, 39(5): 1623-1631.
[126]. Subhash N, Mallia J R. Changes in laser induced chlorophyll fluorescence signatures during regeneration of Kacholam and Colocasia plants from water stress. IGARSS Proceedings 5, 2003: 3293-3295.
[127]. Subhash N, Wenzel O, Hartmut K, Lichtenthaler H K. Changes in blue-green and chlorophyll fluorescence emission and fluorescence ratios during senescence of tobacco plants. Remote Sensing of Environment, 1999, 69: 215-223.
[128]. Thenkabail P S, Smith R B, Pauw E D. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sens Environ, 2000, 71: 158～182.
[129]. Thomas J R, Namken L N, Oerther G F, Brown R G. Estimating leaf water content by reflectance measurement. Agronomy Journal, 1971, 63: 845-847.
[130]. Tsai F, Philpot W. Derivative analysis of hyperspectral data. Remote Sensing of Environment, 1998, 66: 41-51.
[131]. Vidaver W E, Lister G R. Brooke R C, Binder W D. A manual for the use of variable chlorophyll fluorescence in the assessment of the ecophysiology of conifer seedlings. FRDA Rep. 1991, 163, 60.
[132]. Wang K, Shen Z Q, Wang R C. Effects of nitrogen nutrition on the spectral reflectance characteristics of rice leaf and canopy. Journal of Zhejiang Agricultural University, 1998, 24: 93-97.
[133]. Winkel T, Me'thy M, The'not F. Radiation use efficiency, chlorophyll fluorescence, and reflectance indices associated with ontogenic changes in water-limited Chenopodium quinoa leaves. Photosynthetica, 2002, 40: 227-232.
[134]. Yoder B J, Pettigrew-Crosby E P. Predictiing nitrogen and chlorophyll content and concentrations form reflectance spectra (400-2500 nm) at leaf and canopy scales. Remote Sensing of Environment, 1995, 53: 199-211.
[135]. Zarco-Tejada P J, Miller J R, Mohammed G H, et al. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment, 2000, 74: 582-595.
[136]. Zarco-Tejada P J, Miller J R, Gina H, Mohammed, et al. Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: Ⅱ. Laboratory and Airborne Canopy-Level Measurements with Hyperspectral Data. Remote Sensing of Environment, 2000, 74: 596-608
[137]. Zarco-Tejada P J, Miller J R, Mohammed G H, et al. Vegetation stress detection through chlorophyll a+b estimation and fluorescence effects on hyperspectral imagery. J. Environ. Qual. 2002, 31: 1433-1441.
[138]. Zarco-Tejada P J, Miller J R, Mohammed G H, Noland T L. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment, 2000, 74: 582-595.
[139]. Zarco-Tejada P J, Miller J R, Mohammed G H. Chlorophyll Fluorescence effects on Leaf and Canopy Reflectance: Experimental Results and Model Simulation. First Workshop on Remote Sensing of Solar Induced Fluorescence, ESA/ESTEC, Noordwiik, The Netherlands, 19-20 June 2002.
[140]. Zarco-Tejada P J, Miller J R, Mohammed G H, Noland T L, Sampson P H. Estimation of chlorophyll fluorescence under natural illumination from hyperspectral data. Int. J. Appl. Earth Observ. Geoinfo. 2001, 3:321-327.
[141]. Zarco-Tejada P J, Pushnik J, Dobrowsk S, Ustin S L, Steady-state chlorophyll a Fluorescence detection from canopy derivative reflectance and Double-Peak Red-Edge effects. Remote Sensing of Environment, 2003, 84(2), 283-294.
[142]. Zhang L, Dickinson M. Fluorescence from rust fungi: a simple and effective method to monitor the dynamics of fungal growth in planta. Physiological and Molecular Plant Patholog,2001,59:137-141.
[143]. Zhao C M, Wang G X. Effects of Drought Stress on the Photoprotection in Ammopiptanthus mongolicus Leaves. Acta Botanica Sinica, 2002, 44(11):1309-1313.
[144]. Zhumar A Yu. Use of narrow-band spectra to detect rust diseases of wheat crops. IGARSS Proceedings, 1999:794-796.