不同遮荫条件下苦槠和木荷的叶绿素含量及光谱特性

研究了遮荫处理对苦槠、木荷的叶绿素(SPAD相对值)、高光谱特性的影响。结果表明:遮荫处理提高了这两种亚热带常绿阔叶植物的叶绿素含量,80%遮荫处理下的叶绿素含量最大;随遮荫度的提高红光位置则会相应出现"红移"现象;但过高的遮荫度会抑制其生长,表现出"蓝移"现象。对所研究的树种而言,红边位置处—窄波长范围内的平均光谱反射率与叶绿素总量间的相关性普遍较高,相关系数大于0.7。建立的有关红边位置处的光谱反射率与叶绿素总量间的回归模型普遍具有较高的拟合度,应用前景广泛。     

冬小麦冠层光谱红边参数的变化及其与氮素含量的相关分析

通过对不同氮肥条件下的小麦植株由上而下进行器官疏剪,分析了不同处理下冠层光谱反射率及其红边参数的变化。结果表明,冠层光谱反射率因不同肥力、不同疏剪处理而有较大的差异,表现出不同程度的红边的“红移”和“蓝移”现象。各处理的红边曲线形状均出现双峰现象,表现为第二个峰值高于第一个峰值,并且均为N1>N2>N0。相关分析表明,随着由上而下的疏剪处理,不同叶位叶片光谱反射率对冠层光谱的贡献增加,并且其红边参数与相应的叶片全氮含量的相关系数也增加,部分达到显著或极显著相关水平。该结果为利用下部缺素敏感叶片的光谱特征进行小麦养分的及时补充提供了可靠的理论依据。     

落叶松早落病危害的光谱特征及与叶绿素浓度的关系研究

森林病虫害是影响森林健康的主要因素之一，全面、准确、迅速地对森林病虫害进行监测管理必须依靠先进的技术手段。利用光谱特征研究落叶松受害情况及叶绿素浓度变化情况，将落叶松的受害程度分为4个等级，选取了11组不同受害程度叶片的叶绿素、类胡萝卜素的浓度及相应的光谱反射率数据进行分析。结果表明，不同健康程度的光谱反射率有4个明显差别之处，分别在绿峰、吸收谷、“红边”位置及水分吸收带；随着受害程度的加重，“红边”位置“蓝移”，叶绿素反射峰“红移”明显。不同健康程度的落叶松叶片的“红边”拐点波长位置、吸收谷与其叶绿素浓度之间具有较强的相关性，为高光谱数据研究森林病虫害提供了方法和途径。     

用高光谱数据反演健康与病害落叶松冠层光合色素含量的模型研究——基于2005年吉林省敦化、和龙两市落叶松冠层采样测量数据

健康落叶松与遭受病害落叶松的冠层光谱反射率曲线具有明显差异,利用反映这种差异的光谱特征参数建立回归模型,可为反演落叶松冠层光合色素含量进而诊断落叶松健康状况提供方法和途径。以吉林省延边州敦化、和龙两市林场中健康的和遭受落叶松早落病侵害的人工落叶松林为调查对象,在对野外采集的14个落叶松冠层样本进行光谱测量及光合色素含量测量的基础上,选取8个对落叶松冠层光合色素含量变化反映敏感的光谱参数参与建立其光合色素含量的一元线性回归和多元逐步回归模型。研究结果表明,不同健康程度的落叶松冠层光谱曲线在其可见光及近红外波段有3个比较明显的特征差异处,分别位于光谱曲线的“绿峰”、“红谷”和“红边”位置。利用反映这些差异的8个光谱特征参数建立落叶松冠层光合色素含量的回归模型,除 “红边”这一参数回归效果不令人满意外,其余7个参数均得到了较好的回归效果,其中利用峰谷波长差Dgr建立的关于总叶绿素和叶绿素b含量的一元回归模型R²值分别达到0.842 8和0.749 8,利用NDGI建立的关于叶绿素a和类胡萝卜素含量的一元回归模型R²值分别达到0.875 8和0.789 7;多元逐步回归模型的回归效果与一元回归模型相比,各判定系数R²值均有所提高,总叶绿素、叶绿素a、b和类胡萝卜素含量的回归模型R²值分别达到0.885、0.910、0.839和0.862。     

那曲典型草地植被光谱特征分析

遥感是大尺度生态研究的重要工具之一,而地面植物群落特征与其光谱特征之间的关系是解译遥感影像的关键。地面实测数据由于其高空间分辨率和高光谱分辨率,能够准确反映地物光谱信息,可以用来指导卫星遥感解译工作,同时为遥感监测草地退化、草地模型建立等提供数据支持。选取西藏那曲地区的优势植被类型作为研究对象,利用ASD FieldSpec 3便携式光谱仪测定优势种的冠层光谱并进行比较,并取其中一种优势种测量其在不同覆盖度和不同生长期的光谱反射特点。研究结果表明:①不同植被群落冠层光谱具有特殊的光谱曲线,可见光波段光谱反射率依次是紫花针茅、小嵩草和藏北嵩草,近红外波段光谱反射率则依次是小嵩草、藏北嵩草和紫花针茅;红边位置可以识别藏北嵩草,但是不能区分小嵩草和紫花针茅;②不同覆盖度的小嵩草红边、“绿峰”位置不随覆盖度的变化而发生变化;连续统去除后得到吸收深度随覆盖度的增加而变大,吸收峰面积随覆盖度的增加而增加;③小嵩草衰退期内,在可见光波段和红边波段,冠层光谱反射率随着叶绿素含量的减少而下降,出现“红边蓝移,绿峰下降”的现象。     

基于光谱分析的长江口湿地互花米草叶片叶绿素含量反演研究

互花米草是我国滨海湿地主要入侵植物之一,对当地生态系统产生深远影响,其叶绿素含量信息是湿地生态系统关键生态功能定量化研究的重要基础数据。以长江口崇明东滩湿地为研究区,以实测互花米草叶片光谱反射率和总叶绿素含量为数据源,在400~1 000nm范围内研究原始光谱反射率和一阶导数光谱反射率的比值形式(RVI)与归一化差值形式(NDVI)组合,与叶绿素含量的相关性分析,并构建叶绿素含量估算模型。结果表明:基于原始光谱反射率的RVI和NDVI植被指数形式所构建的模型的精度最高,均方根误差RMSE分别达到0.24和0.25;一阶导数光谱反射率因噪声影响较大,其估算效果不佳;从模型所入选波段来看,红边波段在互花米草叶绿素含量估算中尤为重要。     

基于反射光谱数据的茶树叶片SPAD值估算模型研究

实验中将茶树的叶片分为3个部位进行研究,每个部位各采集50个叶片,30组数据作为预测样本,20组数据作为试验模拟样本。设计绿峰位置、绿峰最大反射率、红谷位置、红谷最小反射率、红边位置、红边对应的最大一阶导数反射率、绿峰对应的最大反射率和红谷对应的最小反射率的比值指数以及它们的归一化指数等8个反射光谱参数。首先对茶树叶片的反射光谱参数和茶树叶片的SPAD值进行相关分析;其次以8个反射光谱参数作为自变量,茶树叶片的SPAD值为因变量,进行逐步回归分析,确定茶树不同部位叶片的回归方程.茶树A部位嫩叶片的SPAD值预测模型以λr、Rg/Ro为自变量,其模拟的调整决定系数为0.461;茶树B部位的成熟叶子的SPAD值预测模型以Rg、Rg/Ro、Rg-Ro/Rg+Ro为自变量,其模拟的调整决定系数为0.882;茶树C部位的老叶子的SPAD值预测模型以λr、Dr为自变量,其模拟的调整决定系数为0.407。结果表明,利用反射高光谱参数预测茶树不同部位叶片的SPAD模型是成功的。     

水稻叶绿素浓度与光谱反射率关系研究

结合田间小区实验,获取了水稻生育期9组叶片叶绿素浓度和相应的光谱反射率数据,进行了相关分析研究,结果表明:水稻叶片叶绿素浓度与其光谱反射率之间具有相关性,在450～686nm和750～770 nm光谱区内相关性较好,且在686 nm处两者达到最高的相关性;水稻叶片的“红边”拐点波长位置与其叶绿素浓度之间具有很强的相关性,复相关系数为0.88,并由此进一步讨论了高光谱遥感定量探测水稻叶绿素浓度的可行性。
     

在水分胁迫下棉花冠层叶片全氮含量的高光谱遥感估算模型研究

研究利用美国产ASD地物光谱仪,获取新疆北部地区棉花冠层关键生育时期的高光谱数据,采用红边积分面积变量估测棉花冠层叶片的全氮含量,对反射光谱进行一阶微分,应用一阶微分光谱数据,衍生出基于光谱位置变量的分析方法,以红边积分面积(SDr)为自变量,冠层全氮(TN)含量为因变量,做相关分析与处理,构建新陆早6号红边积分面积与冠层叶片TN含量的相关数学模型。研究在不同水处理条件下,对棉花冠层单叶叶绿素含量和单叶全氮含量做相关分析,结果表明:叶绿素含量与TN含量呈显著的正相关(R=0.8723,n=39),叶绿素含量能有效的估计棉花单叶TN含量;红边积分面积变量与冠层TN含量呈显著的相关性,相关系数是0.7394(n=40),利用构建的相关模型可以较为精确地估测棉花两个品种新陆早6号与8号冠层叶片的全氮含量,RMSE分别为0.3859和0.4272。研究认为红边积分面积变量具有预测棉花冠层全氮含量的应用潜力,研究得出利用3边面积变量构造的数学模型对反演作物冠层TN含量有较高应用价值。研究认为,红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。研究结果证明:①随着棉花的生长发育,叶片的生理生化参数发生变化,冠层的生理生化参数随之发生变化;②.棉花叶片叶绿素含量与叶片的全氮含量相关性显著(R=0.8723,n=38),通过建立数学模型,可以估测叶片中全氮的含量;③由一阶微分光谱衍生出基于光谱“红边”位置变量的分析方法,使我们认识到“红边”的变幅、形状和面积包含了各个波段的信息,这些波段综合产生的变量所构造的模型,为棉花氮素营养参数的估计提供了预测能力;④如果棉花叶绿素含量高,说明水分充足、氮代谢旺盛,植株处于生长旺盛时期,红边向蓝光方向发生了位移。利用红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。     

在水分胁迫下棉花冠层叶片全氮含量的高光谱遥感估算模型研究

研究利用美国产ASD地物光谱仪,获取新疆北部地区棉花冠层关键生育时期的高光谱数据,采用红边积分面积变量估测棉花冠层叶片的全氮含量,对反射光谱进行一阶微分,应用一阶微分光谱数据,衍生出基于光谱位置变量的分析方法,以红边积分面积(SDr)为自变量,冠层全氮(TN)含量为因变量,做相关分析与处理,构建新陆早6号红边积分面积与冠层叶片TN含量的相关数学模型。研究在不同水处理条件下,对棉花冠层单叶叶绿素含量和单叶全氮含量做相关分析,结果表明:叶绿素含量与TN含量呈显著的正相关(R=0.8723,n=39),叶绿素含量能有效的估计棉花单叶TN含量;红边积分面积变量与冠层TN含量呈显著的相关性,相关系数是0.7394(n=40),利用构建的相关模型可以较为精确地估测棉花两个品种新陆早6号与8号冠层叶片的全氮含量,RMSE分别为0.3859和0.4272。研究认为红边积分面积变量具有预测棉花冠层全氮含量的应用潜力,研究得出利用3边面积变量构造的数学模型对反演作物冠层TN含量有较高应用价值。研究认为,红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。研究结果证明:①随着棉花的生长发育,叶片的生理生化参数发生变化,冠层的生理生化参数随之发生变化;②.棉花叶片叶绿素含量与叶片的全氮含量相关性显著(R=0.8723,n=38),通过建立数学模型,可以估测叶片中全氮的含量;③由一阶微分光谱衍生出基于光谱“红边”位置变量的分析方法,使我们认识到“红边”的变幅、形状和面积包含了各个波段的信息,这些波段综合产生的变量所构造的模型,为棉花氮素营养参数的估计提供了预测能力;④如果棉花叶绿素含量高,说明水分充足、氮代谢旺盛,植株处于生长旺盛时期,红边向蓝光方向发生了位移。利用红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。     

Using multivariate analysis to detect the hyperspectral response of Chinese fir to acid stress

A useful method was developed to establish a diagnostic model using hyperspectral remote sensing to predict and monitor acid stress on plants. We analysed the hyperspectral response of Chinese fir to acid rain by measuring the spectral reflectance of the seedling leaves, sprayed by simulated acid rain (pH, 2.5, 4.0, and 5.6), for three periods. The sensitive bands were located and the rules for predicting classes of simulated acid stress on Chinese fir were established using a classification and regression tree (CART) approach. The acid-sensitive bands of Chinese fir were nearly all located between 380 and 410 nm, 460 and 560 nm, and 640 and 750 nm. CART predictor variables, which were selected from sensitive bands, reduce data dimensionality significantly. The misclassification errors of the CART training process in correctly attributing variables to respective target classes are 7.78%, 6.67%, and 11.67% respectively, at each measurement period, and the cross-validation misclassification errors are 16.6%, 11.1%, and 23.3%, respectively. Our results show that the spectral reference bands, which are related to chlorophyll-a and b around 670 and 450 nm, as well as the slight peak in the green around 550 nm, significantly affected the classification accuracy on acid stress. These provide useful optical response to acid stress.     

Study on the Inversion of Chlorophyll Content of Spartina Alterniflora Leaf in the Yangtze River Estuary Wetland based on Spectral Analysis#br#

Spartina alterniflora is one of the most important invasive species in the coastal wetlands in China,which have a profound impact on the local ecological system.The information of chlorophyll content is an important basic data for quantitative research on key ecological function of wetland ecosystem.The Yangtze River in Chongming Dongtan wetland is the study area.Based on the measured leaf spectral reflectance and total chlorophyll content of Spartina alterniflora,in the range of 400~1 000 nm,the ratio of the original form of the spectral reflectance and first derivative spectral reflectance(RVI)and normalized difference vegetation index(NDVI)in the form of combination are established for the correlation with the content of chlorophyll and the construction of the estimation model.The results show that RVI and NDVI vegetation index form model based on the original spectra have the highest accuracy,whose root mean square error(RMSE)are up to respectively 0.24 and 0.25;Because of the nosie in the first derivative spectral reflectance,the estimation model of chlorophyll has poor results;Based on the band selected from the model,the red edge band is particularly important in the estimation of chlorophyll content of Spartina alterniflora.     

不同油蒿树势的光谱分析

以宁夏灵武油蒿主要分布区为研究地,野外调查并获取了健康及受钻蛀性害虫危害后油蒿冠层光谱的反射率,并应用一阶微分方法处理光谱反射率进行研究。研究表明,健康油蒿受到钻蛀性害虫危害后,具有明显的＂红边＂蓝移现象,同时,利用高光谱数据监测虫害发生是可行的,而且对植株本身不造成任何伤害。该研究为荒漠灌木林是否可利用高光谱数据来进行钻蛀性害虫监测提供了基础。     

Influence of plant pigments on spectral reflectance of maize,groundnut and soybean grown in semi-arid environments

Abstract. Spectral reflectance of leaves is influenced primarily by plant pigments, chlorophyll and carotenoids. Such reflectance can be used to study the changes in chlorophyll content and nitrogen status and in turn measures the amount of biomass accumulation. A field experiment was laid out at the Research Farm of ANGR Agricultural University, Hyderabad. The reflectance observations were taken using a hand-held ground radiometer at an interval of 15 days beginning from 30 days after sowing (DAS) until harvest of the crops. The plant pigments were determined simultaneously using DMSO (dimethyl sulphoxide) method in the laboratory. The experimental results revealed the influence of plant pigments on spectral reflectance of maize, groundnut and soybean. It was observed that there was an increase in chlorophyll- a, chlorophyll- b, total chlorophyll and carotenoid content up to flowering and thereafter chlorophyll- a content declined at a faster rate than chlorophyll- b towards physiological maturity. With the increase in concentrations of chlorophyll and carotenoids, there was a decline in spectral reflectance of the blue band (450-520 nm) and the red band (620-680 nm). Whereas, NIR (near-infrared) reflectance in the case of soybean and groundnut was found to be higher than that of maize by 11% and 2%, respectively. This was attributed to canopy cover of soybean and groundnut crops, where the soil was fully covered with vegetation. In case of maize, due to wider spacing, the soil exposure is greater, which results in low reflectance values of the NIR band. Normalized Difference Vegetation Index (NDVI) is linearly related to total chlorophyll content and the growth stages of a crop up to flowering. The NDVI differs significantly during the peak vegetative growth period among the three crop types. The study revealed that the significant differences in reflectance of maize, groundnut and soybean in the red and NIR bands were influenced by concentrations of chlorophyll- a, chlorophyll- b and carotenoids, which indicates the photosynthetic behaviour of the crops.     

Variations of ocean colour parameters with nonuniform vertical profiles of chlorophyll concentration

Based on radiative transfer simulations, the effects of nonuniform chlorophyll profiles in case 1 waters on the penetration depth, the above‐surface spectral remote‐sensing reflectance, and the optically weighted chlorophyll concentration are investigated. The simulations for nonuniform chlorophyll profiles are compared with those for homogeneous ocean whose chlorophyll concentrations are identical to the surface chlorophyll concentrations in the inhomogeneous ocean. Due to influence of the nonuniformity of chlorophyll profile, the maximum relative error for the penetration depth at 445 nm is more than 60%, the spectral remote‐sensing reflectance is about 40% and the optically weighted chlorophyll concentration is about 40% within the range of our simulations. However, the simulation shows that there is always a spectral band where the value of above‐surface remote‐sensing reflectance is not influenced by the nonuniformity. Depending on this band, a new model for retrieving sea surface chlorophyll concentration is designed by adding a compensation term into the variable in SeaWiFS OC2V4 algorithm. By using an iterative method with this new model, sea surface chlorophyll concentration can be well retrieved even in an area where the vertical chlorophyll distribution is unknown.     

Reflectance assessment of mite effects on apple trees

Reflectance measurements were conducted in field plots of Golden Smoothee 2038 apple cultivar subjected to different levels of mite attack (from 0 to 500 cumulative mite days) over a 2-year period. Chlorophyll concentration decreased and carotenoid/chlorophyll a ratio increased with increasing level of attack. Classical reflectance indices such as red edge wavelength or the Normalized Difference Vegetation Index were unable to distinguish among treatments. On the other hand, spectral indices based on carotenoid/chlorophyll a (SRPI R430/R680) and chlorophyll degradation (Normalized Phaeophytinization Index calculated as (R415-R435)/(R435 +R415)) were correlated with the level of attack. These reflectance indices show potential uses of visible reflectance as non-invasive, non-destructive techniques for detection of mite effects.     

Remote estimation of chlorophyll content in higher plant leaves

Indices for the non-destructive estimation of chlorophyll content were formulated using various instruments to measure reflectance and absorption spectra in visible and near-infrared ranges, as well as chlorophyll contents from several non-related species from different climatic regions. The proposed new algorithms are simple ratios between percentage reflectance at spectral regions that are highly sensitive (540 to 630nm and around 700nm) and insensitive (nearinfrared) to variations in chlorophyll content: R NIR / R 700 and R NIR / R 550. The developed algorithms predicting leaf chemistry from the leaf optics were validated for nine plant species in the range of chlorophyll content from 0.27 to 62.9mug cm -2. An error of less than 4.2 mugcm -2 in chlorophyll prediction was achieved. The use of green and red (near 700nm) channels increases the sensitivity of NDVI to chlorophyll content by about five-fold.