基于计算机视觉技术评价光照度对斜纹夜蛾幼虫体色的影响

【目的】为揭示光照度对斜纹夜蛾Prodenia litura(Fabricius)幼虫体色变化的影响,建立一套新的昆虫体色评价体系。【方法】采用计算机视觉检测技术,将斜纹夜蛾幼虫的颜色数值化,评价了斜纹夜蛾幼虫体色随日龄的变化规律及光照度对斜纹夜蛾幼虫体色变化的影响。【结果】随着日龄的增加,斜纹夜蛾幼虫的明度(B)和彩色指数(CI)逐渐减少,体色偏差系数(BDV)逐渐增加,色泽从开始的绿色占主导逐渐转变为红色占主导,不同日龄间主观色各颜色指标都差异显著(P<0.01);在低光照度(0~1 000 lx)下,明度(B)和体色偏差系数(BDV)主要受光照影响,而彩色指数(CI)和归一化RGB值主要受发育日龄的影响,在高光照度下(1 000 lx以上),所有颜色指标均受发育日龄影响较大,受光照处理相对较小,光照度对斜纹夜蛾幼虫体色影响的阈值为1 000 lx,在阈值下,明度(B)、彩色指数(CI)及体色分化系数(BDC)都随光照度的增加显著增加,体色偏差系数(BDV)、RGB色差则随光照度的增加而减少。【结论】光照度主要影响斜纹夜蛾幼虫体色的明暗程度,对色彩程度影响不大,且光照度的影响阈值大约为1 000 lx。     

杨树林全生长期LAI遥感估算模型适用性

基于时间序列的植被叶面积指数(LAI)估算方法一直是遥感领域研究的热点,对植被全生长期LAI进行估算以跟踪其生长情况具有重要的实用意义。以此为出发点,以滁州地区杨树林为研究对象,获取多时相环境卫星CCD(简称HJ-CDD)遥感影像,并利用LAI-2000同步测量杨树林叶面积指数(LAI)。使用归一化植被指数(NDVI)分别建立展叶期、花果期、叶面积稳定期和落叶始期的LAI估算模型,通过对比分析得到了全生长期LAI估算模型,并利用实测LAI对估算LAI进行了验证。最后进一步对该模型的适用性进行了验证,结果表明,此模型对于各个时期LAI的估算具有一定的适用性和有效性,可用于全生育期的遥感LAI生成,从而为LAI的动态变化监测提供了一种有效的研究思路和方法途径。     

Analysing spectral data: comparison and application of two techniques

This study compares two different methods of condensing complex spectral data into interpretable indices or metrics of colour. Colour spectra were measured on standardized Munsell colour paint chips and estimates of the three fundamental components of colour (brightness, chroma and hue) were generated using principal component analysis (PCA) and segment classification (SC). We tested the accuracy of these techniques for generating colour component estimates from spectral data in four different 'colour classes' (red/orange, yellow/ green, green/blue, and blue/purple) and in an aggregate data set containing all measured spectra. We conclude that both analysis techniques will generally provide more information than more conventional colour assessment techniques. Neither technique was superior under all conditions; appropriateness of each technique depends on the system under study. Efficacy of both techniques depends on the variability present in the data set; greater variance in colour tends to reduce overall resolution. An application of tfiese techniques is also presented in which we characterize sex-specific differences in colour between different populations of the poecilliid fish, Limia perugia.     

Colour and brightness coding in the central nervous system: theoretical aspects and visual evoked potentials to homogeneous red and green stimuli

We designed visual evoked potentials experiments to study the differential aspects of colour and brightness coding in man. The substitution of equally bright red and green stimuli for a background yellow was investigated and compared with different luminance increments and decrements of red and green. A dominant N87 component was found for a colour change from yellow to brighter red colours, which was less pronounced for green and absent for yellow luminance changes. It is also absent for pure red luminance increments and green luminance changes, but reappears with red luminance decrements or red-offset. The data are discussed within the framework of a new concept of how the visual system fuses red-green information and black-white border information. Retinal X-cells can transmit colour and high spatial frequency achromatic information simultaneously by encoding only the presence of edges (a.c.) for the black-white stimuli and the presence of both edges (a.c.) and uniform areas of colour (d.c.) for red-green stimuli. Phylogenetically this kind of information transmission enables colour vision to be implemented in a retina such as the cat's by adding only a second class of cones. Barlow's economy principle will be violated for colour in the periphery, but restored early in the striate cortex where there is an early decoding of the combined chromatic and achromatic information by the concentric double opponent cells. The N87 behaviour correlates with the proposed discharge of peripheral X-type cells, but not with the discharge of cortical double opponent concentric or simple cells, which no longer respond to homogeneous colour stimuli. It is suggested that N87 may be generated by geniculate afferents in the dendritic arborization of cortical cells, reflecting the behaviour of peripheral units, and thus the violation of the economy principle, rather than the next step in cortical processing. The early cortical restoration of the economy principle is supported by the absence of any further dissociated behaviour for colour and brightness in later components.     

Multispectral fluorescence and reflectance imaging at the leaf level and its possible applications

Images taken at different spectral bands are increasingly used for characterizing plants and their health status. In contrast to conventional point measurements, imaging detects the distribution and quantity of signals and thus improves the interpretation of fluorescence and reflectance signatures. In multispectral fluorescence and reflectance set-ups, images are separately acquired for the fluorescence in the blue, green, red, and far red, as well as for the reflectance in the green and in the near infrared regions. In addition, 'reference' colour images are taken with an RGB (red, green, blue) camera. Examples of imaging for the detection of photosynthetic activity, UV screening caused by UV-absorbing substances, fruit quality, leaf tissue structure, and disease symptoms are introduced. Subsequently, the different instrumentations used for multispectral fluorescence and reflectance imaging of leaves and fruits are discussed. Various types of irradiation and excitation light sources, detectors, and components for image acquisition and image processing are outlined. The acquired images (or image sequences) can be analysed either directly for each spectral range (wherein they were captured) or after calculating ratios of the different spectral bands. This analysis can be carried out for different regions of interest selected manually or (semi)-automatically. Fluorescence and reflectance imaging in different spectral bands represents a promising tool for non-destructive plant monitoring and a 'road' to a broad range of identification tasks.     

蜻蜒运动检测神经元的光谱反应

蜻蜒腹神经束上存在着自运动检测神经元和目标运动检测神经元.我们采用了两种视觉刺激条件来测试自运动检测神经元的光谱反应.当采用控制强度和波长的闪光进行测试时、它们的光谱反应曲线与绿色光感受器的光谱灵敏度曲线极其相似,峰值位于500nm处.然而采用运动的条纹进行测试时,它们的峰值却位于560nm处.当用一种颜色的运动图案作为目标放置在另一种颜色背景的前方测试时,发现存在某个目标的照明强度值能使反应下降到自发放电的水平,这表明自运动检测器无法检测这二种颜色的差别,即它们是色盲的、它主要接受来自绿色光感受器的信号.目标运动检测神经元的光谱反应特性与自运动检测神经元的不同,目标运动检测神经元在以380nm至580nm的范围中有着平坦的光谱反应曲线,有时在紫外频段出现峰有(?)前景与背景颜色不同且固定背景光的颜色与强度而改变前景的光强时,神经元的反应不会下降到自发放电水平,当背景为绿色而目标为另一个颜色.特别是兰色时,神经元反应强烈,但当背景为兰色而目标为绿色时,它们的反应相对较弱.这些结果表明目标运动检测神经元是对颜色敏感的.     

Biomass estimation using satellite remote sensing data—An investigation on possible approaches for natural forest

Vegetation type and its biomass are considered important components affecting biosphere-atmosphere interactions. The measurements of biomass per unit area and productivity have been set as one of the goals for International Geosphere-Biosphere Programme (IGBP). Ground assessment of biomass, however, has been found insufficient to present spatial extent of the biomass. The present study suggests approaches for using satellite remote sensing data for regional biomass mapping in Madhav National Park (MP). The stratified random sampling in the homogeneous vegetation strata mapped using satellite remote sensing has been effectively utilized to extrapolate the sample point biomass observations in the first approach. In the second approach attempt has been to develop empirical models with satellite measured spectral response and biomass. The results indicate that there is significant relationships with spectral responses. These relationships have seasonal dependency in varying phonological conditions. The relationships are strongest in visible bands and middle infrared bands. However, spectral biomass models developed using middle infrared bands would be more reliable as compared to the visible bands as the later spectral regions are less sensitive to atmospheric changes It was observed that brightness and wetness parameters show very strong relationship with the biomass values. Multiple regression equations using brightness and wetness isolates have been used to predict biomass values. The model used has correlation coefficient of 0.77. Per cent error between observed and predicted biomass was 10.5%. The biomass estimated for the entire national park using stratified and spectral response modelling approaches were compared and showed similarity with the difference of only 4.69%. The results indicate that satellite remote sensing data provide capability of biomass estimation     

基于TM遥感影像的陕北黄土区结构化植被因子指数提取

根据结构化植被因子指数的概念,以TM影像为信息源,探讨了利用遥感技术提取陕北黄土区结构化植被因子指数（C_s）的途径与方法.结果表明：在陕北黄土区,C_s能更好地描述植被群落的水土保持效益,其与绿度植被指数（归一化植被指数NDVI、修正土壤调整植被指数MSAVI）和黄度植被指（归一化差异衰败指数NDSVI、归一化耕作指数NDTI）等单一的遥感植被指数虽然均存在良好的相关关系,但用绿度与黄度植被指数相结合可综合反映植被的水土保持功能,能较好地克服单一指数在描述植被控制水土流失中的不足;MSAVI、NDTI分别是基于遥感影像提取C_s较为理想的绿度和黄度植被指数;根据群落结构化植被因子指数与遥感植被指数的关系推算区域尺度上的结构化植被因子指数是可行的,但由于不同地区植物物候期的差异,要使该方法在其他地区适用,仍需开展相应的率定和验证工作.     

Learning and discrimination of coloured papers in the walking blowfly,Lucilia cuprina

Summary A new training and testing paradigm for walking sheep blowflies, Lucilia cuprina, is described. A fly is trained by presenting it with a droplet of sugar solution on a patch of coloured paper. After having consumed the sugar droplet, the fly starts a systematic search. While searching, it is confronted with an array of colour marks consisting of four colours displayed on the test cardboard (Fig. 1). Colours used for training and test include blue, green, yellow, orange, red, white and black.Before training, naive flies are tested for their spontaneous colour preferences on the test array. Yellow is visited most frequently, green least frequently (Table 2). Spontaneous colour preferences do not simply depend on subjective brightness (Table 1).The flies trained to one of the colours prefer this colour significantly (Figs. 5 and 9–11). This behaviour reflects true learning rather than sensitisation (Figs. 6–7). The blue and yellow marks are learned easily and discriminated well (Figs. 5, 9, 11). White is also discriminated well, although the response frequencies are lower than to blue and yellow (Fig. 11). Green is discriminated from blue but weakly from yellow and orange (Figs. 5, 9, 10). Red is a stimulus as weak as black (Figs. 8, 9). These features of colour discrimination reflect the spectral loci of colours in the colour triangle (Fig. 14).The coloured papers seem to be discriminated mainly by the hue of colours (Fig. 12), but brightness may also be used to discriminate colour stimuli (Fig. 13).     

水胁迫下多角度幼龄檀香图像颜色变化分析及含水率反演

干旱与水淹胁迫是植物遭受的主要非生物胁迫,对植物的生理活动造成严重影响.本研究基于单反相机获取幼龄檀香的纵向和冠层叶片图像,使用分割算法提取叶片和颜色特征,然后讨论两种胁迫条件下多角度檀香叶片颜色变化及含水率反演.结果表明:干旱组在胁迫前期(前6d)叶片亮度降低,绿色分量增加,之后叶片亮度增加,绿色分量降低;水淹组叶片在整个胁迫周期亮度持续降低,黄色分量增加;对照组则与干旱组的变化趋势类似,但拐点出现的时间较晚.当叶片含水率在50%~70%时,随着含水率的增加,彩色图像的红(R)、绿(G)、蓝(B)通道值均会减小;但当叶片含水率小于40%时,会出现R通道值大于G通道值的现象.在使用极限学习机反演含水率时,校正后的颜色分量对拟合优度及预测精度均有所提高.纵向图像更适合用来反演叶片的含水量,决定系数和平均绝对百分比误差分别为0.8352和2.3%;而冠层图像对叶片等效水厚度的表达更准确,上述指标分别为0.7924和9.3%.     

Visual ecology of aphids—a critical review on the role of colours in host finding

We review the rich literature on behavioural responses of aphids (Hemiptera: Aphididae) to stimuli of different colours. Only in one species there are adequate physiological data on spectral sensitivity to explain behaviour crisply in mechanistic terms. Because of the great interest in aphid responses to coloured targets from an evolutionary, ecological and applied perspective, there is a substantial need to expand these studies to more species of aphids, and to quantify spectral properties of stimuli rigorously. We show that aphid responses to colours, at least for some species, are likely based on a specific colour opponency mechanism, with positive input from the green domain of the spectrum and negative input from the blue and/or UV region. We further demonstrate that the usual yellow preference of aphids encountered in field experiments is not a true colour preference but involves additional brightness effects. We discuss the implications for agriculture and sensory ecology, with special respect to the recent debate on autumn leaf colouration. We illustrate that recent evolutionary theories concerning aphid–tree interactions imply far-reaching assumptions on aphid responses to colours that are not likely to hold. Finally we also discuss the implications for developing and optimising strategies of aphid control and monitoring.     

Light emitting diode(LED)‐based trapping of the greenhouse whitefly (Trialeurodes vaporariorum)

Visual traps like yellow sticky card traps are used for monitoring and control of the greenhouse whitefly (Trialeurodes vaporariorum). However, reflected intensity (brightness) and hence, attractiveness depend on the ambient light conditions, and the colour (wavelength) might not fit with the sensitivity of whitefly photoreceptors. The use of light emitting diodes (LEDs) is a promising approach to increase the attractiveness, specificity and adaptability of visual traps. We constructed LED‐based visual traps equipped with blue and green high‐power LEDs and ultraviolet (UV) standard LEDs according to the putative spectral sensitivities of the insects' photoreceptors. In a series of small‐scale choice and no‐choice recapture experiments, the factors time of day as well as light intensity and light quality (colour) of LED traps were studied in terms of attractiveness compared to yellow traps without LEDs. Green LED traps (517 nm peak wavelength) were comparably attractive in no‐choice experiments but clearly preferred over yellow traps in all choice experiments. The time of day had a clear effect on the flight activity of the whiteflies and thereby on the trapping success. Blue LEDs (474 nm) suppressed the attractiveness of the light traps when combined with green LEDs suggesting that a yet undetected photoreceptor, sensitive for blue light, and an inhibiting interaction with the green receptor, might exist in T. vaporariorum. In choice experiments between LED traps emitting green light only or in combination with UV (368 nm), the green‐UV combination was preferred. In no‐choice night‐time experiments, UV LEDs considerably increased whitefly flight activity and efficacy of trapping. Most likely, the reason for the modifying effect of UV is the stimulating influence on flight activity. In conclusion, it seems that the use of green LEDs alone or in combination with UV LEDs could be an innovative option for improving attractiveness of visual traps.     

Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

The need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

     

基于小波理论的干旱区内陆湖泊叶绿素a的TM影像遥感反演

叶绿素a(Chl-a)是衡量湖泊富营养化的重要指标,利用遥感技术动态监测面积较大的湖区水体中Chl-a浓度对了解湖区水质具有重要意义。以内蒙古乌梁素海为例,提出利用TM影像中的水体实测光谱进行小波去噪和光谱信号重构,并结合水质采样实测数据进行神经网络拟合,建立光谱反射率比值与Chl-a浓度的反演模型的方法。结果显示:小波理论和神经网络相结合的模型可以适用于估算乌梁素海Chl-a浓度,去噪后Chl-a浓度与光谱信号的相关系数(-0.575)较去噪前(-0.417)明显增强,去噪后的采样点光谱信号与Chl-a浓度之间表现出比原始信号更强的负相关性,证明了去噪后的观测值可进一步减弱随机误差的干扰和去除噪声,使观测数据更加逼近Chl-a浓度的真实情况,图像去噪重构结果显示重构后的光谱范围较之前有所缩窄,部分信号点得到了增强,但基本剖面结构并没有产生较大变化,反演模型的平均相对误差为0.142,与其他研究相比差别不大。反演得出的乌梁素海Chl-a浓度分布反映了污染源的分布,同时说明了乌梁素海Chl-a浓度在时空分布上呈现一定的差异,表现为丰水期呈现浅水区Chl-a浓度值高于湖心区,来水区高于其他湖区的分布趋势,枯水期乌梁素海中部呈现由西向东Chl-a浓度逐步降低的分布规律,西部呈均一化分布。反演模型基本可以满足实际预测的需要。但模型在具体应用中在影像数据采集、数据量及算法方面还有很大的改进空间,该方法的提出为干旱区大型内陆水体富营养化的实时定量遥感监测提供了新的解决方案。     

Zum Farbsehvermögen von Hausziegen (Capra hircus L.)

Tests on male goats were designed to determine their capacity for colour vision. The colours yellow, orange, blue, violet and green were tested against gray nuances of like brightness. Goats were found to be able to distinguish between colours and gray nuances. The rate of errors increased in the order: orange, green, red, yellow, violet, blue.     

Monitoring Powdery Mildew of Winter Wheat by Using Moderate Resolution Multi-Temporal Satellite Imagery

Powdery mildew is one of the most serious diseases that have a significant impact on the production of winter wheat. As an effective alternative to traditional sampling methods, remote sensing can be a useful tool in disease detection. This study attempted to use multi-temporal moderate resolution satellite-based data of surface reflectances in blue (B), green (G), red (R) and near infrared (NIR) bands from HJ-CCD (CCD sensor on Huanjing satellite) to monitor disease at a regional scale. In a suburban area in Beijing, China, an extensive field campaign for disease intensity survey was conducted at key growth stages of winter wheat in 2010. Meanwhile, corresponding time series of HJ-CCD images were acquired over the study area. In this study, a number of single-stage and multi-stage spectral features, which were sensitive to powdery mildew, were selected by using an independent t-test. With the selected spectral features, four advanced methods: mahalanobis distance, maximum likelihood classifier, partial least square regression and mixture tuned matched filtering were tested and evaluated for their performances in disease mapping. The experimental results showed that all four algorithms could generate disease maps with a generally correct distribution pattern of powdery mildew at the grain filling stage (Zadoks 72). However, by comparing these disease maps with ground survey data (validation samples), all of the four algorithms also produced a variable degree of error in estimating the disease occurrence and severity. Further, we found that the integration of MTMF and PLSR algorithms could result in a significant accuracy improvement of identifying and determining the disease intensity (overall accuracy of 72% increased to 78% and kappa coefficient of 0.49 increased to 0.59). The experimental results also demonstrated that the multi-temporal satellite images have a great potential in crop diseases mapping at a regional scale.     

An investigation of colour discrimination with horses (Equus caballus)

The ability of four horses (Equus caballus) to discriminate coloured (three shades of blue, green, red, and yellow) from grey (neutral density) stimuli, produced by back projected lighting filters, was investigated in a two response forced-choice procedure. Pushes of the lever in front of a coloured screen were occasionally reinforced, pushes of the lever in front of a grey screen were never reinforced. Each colour shade was randomly paired with a grey that was brighter, one that was dimmer, and one that approximately matched the colour in terms of brightness. Each horse experienced the colours in a different order, a new colour was started after 85% correct responses over five consecutive sessions or if accuracy showed no trend over sessions. All horses reached the 85% correct with blue versus grey, three horses did so with both yellow and green versus grey. All were above chance with red versus grey but none reached criterion. Further analysis showed the wavelengths of the green stimuli used overlapped with the yellow. The results are consistent with histological and behavioural studies that suggest that horses are dichromatic. They differ from some earlier data in that they indicate horses can discriminate yellow and blue, but that they may have deficiencies in discriminating red and green.     

Leaf Colour as a Signal of Chemical Defence to Insect Herbivores in Wild Cabbage (Brassica oleracea)

Leaf colour has been proposed to signal levels of host defence to insect herbivores, but we lack data on herbivory, leaf colour and levels of defence for wild host populations necessary to test this hypothesis. Such a test requires measurements of leaf spectra as they would be sensed by herbivore visual systems, as well as simultaneous measurements of chemical defences and herbivore responses to leaf colour in natural host-herbivore populations. In a large-scale field survey of wild cabbage (Brassica oleracea) populations, we show that variation in leaf colour and brightness, measured according to herbivore spectral sensitivities, predicts both levels of chemical defences (glucosinolates) and abundance of specialist lepidopteran (Pieris rapae) and hemipteran (Brevicoryne brassicae) herbivores. In subsequent experiments, P. rapae larvae achieved faster growth and greater pupal mass when feeding on plants with bluer leaves, which contained lower levels of aliphatic glucosinolates. Glucosinolate-mediated effects on larval performance may thus contribute to the association between P. rapae herbivory and leaf colour observed in the field. However, preference tests found no evidence that adult butterflies selected host plants based on leaf coloration. In the field, B. brassicae abundance varied with leaf brightness but greenhouse experiments were unable to identify any effects of brightness on aphid preference or performance. Our findings suggest that although leaf colour reflects both levels of host defences and herbivore abundance in the field, the ability of herbivores to respond to colour signals may be limited, even in species where performance is correlated with leaf colour.     

UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest

Development of vegetation communities in areas of Antarctica without permanent ice cover emphasizes the need for effective remote sensing techniques for proper monitoring of local environmental changes. Detection and mapping of vegetation by image classification remains limited in the Antarctic environment due to the complexity of its surface cover, and the spatial heterogeneity and spectral homogeneity of cryptogamic vegetation. As ultra-high resolution aerial images allow a comprehensive analysis of vegetation, this study aims to identify different types of vegetation cover (i.e., algae, mosses, and lichens) in an ice-free area of  Hope Bay, on the northern tip of the Antarctic Peninsula. Using the geographic object-based image analysis (GEOBIA) approach, remote sensing data sets are tested in the random forest classifier in order to distinguish vegetation classes within vegetated areas. Because species of algae, mosses, and lichens may have similar spectral characteristics, subclasses are established. The results show that when only the mean values of green, red, and NIR bands are considered, the subclasses have low separability. Variations in accuracy and visual changes are identified according to the set of features used in the classification. Accuracy improves when multilayer information is used. A combination of spectral and morphometric products and by-products provides the best result for the detection and delineation of different types of vegetation, with an overall accuracy of 0.966 and a Kappa coefficient of 0.946. The method allowed for the identification of units primarily composed of algae, mosses, and lichens as well as differences in communities. This study demonstrates that ultra-high spatial resolution data can provide the necessary properties for the classification of vegetation in Maritime Antarctica, even in images obtained by sensors with low spectral resolution.     

基于光谱指数的植物叶片叶绿素含量的估算模型

叶绿素是光合作用能力和植被发育阶段的指示器,是监测湿地植被生长健康状况的重要指标之一;高光谱遥感技术可以为植物叶绿素含量的定量化诊断提供简便有效、非破坏性的数据采集和处理方法。为保证被探测叶片面积相同,消除背景反射、叶片表面弯曲造成的光谱波动及叶片内部变异造成的影响,研究采用Field Spec 3光谱仪加载手持叶夹式叶片光谱探测器,测定野鸭湖湿地典型植物的叶片高光谱反射率数据,同时通过分光光度计室内测定相应叶片的叶绿素含量。采用相关性及单变量线性拟合分析技术,建立二者的关系模型,包括叶绿素含量与"三边"参数的相关模型以及比值光谱指数(SR)模型和归一化差值光谱指数(ND)模型,并采用交叉检验中的3K-CV方法对估算模型进行模型精度检验。结果表明:植物叶片叶绿素含量与"三边"参数大多都呈极显著相关,相关系数最大达到0.867;计算光谱反射率组成的比值(SR)和归一化(ND)光谱指数与叶绿素含量的决定系数,总体相关性比较高,较好的波段组合均为550—700nm与700—1400nm以及550—700nm与1600—1900nm,与叶绿素含量相关性最好的指数分别是SR(565nm,740nm)和ND(565nm,735nm)。并通过选取相关性最佳的光谱特征参数,分别基于"三边"参数和ND模型指数构建了植物叶片叶绿素含量的估算模型。其中,基于红边位置(WP_r)光谱特征参数和ND(565nm,735nm)光谱指数建立的叶绿素含量估算模型,取得了较好的测试效果,检验拟合方程的决定系数(R2)都达到0.8以上,估算模型分别为y=0.113x-78.74,y=5.5762x+4.4828。通过3K-CV方法进行测试和检验,植物叶绿素含量估算模型均取得了较为理想的预测精度,预测精度的分别为93.9%及90.7%。高光谱遥感技术对植被进行微弱光谱差异的定量分析,在植被遥感研究与应用中表现出强大优势,为植物叶绿素含量诊断中的实际应用提供了重要的理论依据和技术支持。