冠层水平互花米草叶片光合色素含量的高光谱遥感估算模型

以闽江河口鳝鱼滩湿地互花米草(Spartina alterniflora)的实测冠层高光谱反射率和叶片光合色素含量(LPPC)为数据源,在分析LPPC与原始光谱反射率、一阶导数光谱反射率、22种已报道光谱指数和14种新构建的植被指数相关性的基础上,利用直线回归、指数回归、对数回归以及乘幂回归方法,系统地比较了36种植被指数在估算互花米草LPPC中的表现。研究表明:(1)一阶导数光谱反射率组合的植被指数用于估算互花米草的LPPC优于原始光谱反射率;(2)红边区域一阶导数光谱是估测互花米草LPPC的最佳波段;(3)对于单一色素含量的估算,叶绿素a(Chla)的最佳估算指数为FDNDVI[723,703];叶绿素b(Chlb)的最佳估算指数为FDRVI[723,525];类胡萝卜素(Cars)的最佳估算指数为FDNDVI[723,703];(4)对于使用统一参量同时估算Chla、Chlb、Cars,由FDRVI[723,703]建立的对数估算模型效果最佳。研究成果可为湿地植物生化参量反演提供参考,也可为闽江河口湿地入侵种互花米草的动态监测和生态评估管理提供有力的科学依据。     

水稻上部叶片叶绿素含量的高光谱估算模型

叶片叶绿素 (Chl) 状况是评价植株光合效率和营养胁迫的重要指标,实时无损监测Chl状况对作物生长诊断及氮素管理具有重要意义.以不同生态点、不同年份、不同施氮水平、不同类型水稻品种的4个田间试验为基础,于主要生育期同步测定了水稻主茎顶部4张叶片的高光谱反射率及Chl含量,并计算了350～2500 nm范围内任意两波段组合而成的比值(SR[λ1,λ2])和归一化(ND[λ1,λ2])光谱指数以及已报道的对Chl敏感的光谱指数,进一步系统分析了叶片Chl含量与上述光谱指数之间的定量关系.结果表明,红边波段的比值和归一化光谱指数可以较好地预测水稻上部4叶的Chl含量(R~2>0.9),但对于不同Chl指标其最佳组合波段有所差异.估算叶绿素a (Chla)、叶绿素总量(Chla+b)和叶绿素b (Chlb)的最佳比值光谱指数分别为SR(724,709)、SR(728,709)和SR(749,745),方程拟合决定系数R~2分别是0.947、0.946、0.905;最佳归一化光谱指数分别为ND(780,709)、ND(780,712)和ND(749,745),R~2分别是0.944、0.943、0.905.引入445 nm波段反射率对上述光谱指数进行修正,可以降低叶片表面反射差异的影响,提高模型的应用范围.利用不同年份独立的试验资料对所建模型进行了检验,结果表明,修正型比值光谱指数 mSR(724,709)、mSR(728,709) 和 mSR(749,745),以及修正型归一化光谱指数mND(780,709)、mND(780,712) 和 mND(749,745) 预测 Chla、Chla+b 和 Chlb 的效果更好,其测试的RMSE分别为 0.169、0.192、0.052、0.159、0.176、0.052,RE分别为8.18%、7.74%、13.01%、8.26%、7.59%、12.96%,均较修正前降低,说明修正后的光谱指数普适性更好.     

Detecting <Emphasis Type="Italic">Suaeda salsa</Emphasis> L<Emphasis Type="Italic">.</Emphasis> chlorophyll fluorescence response to salinity stress by using hyperspectral reflectance

Measurements of chlorophyll fluorescence and hyperspectral reflectance were used to detect salinity stress in Suaeda salsa L., beach of Dongtai, Jiangsu Province, China. Three experimental sites were used in our study, which belong to low salinity, middle salinity and high salinity. The results showed that leaf chlorophyll fluorescence changed along salinity gradient. To select the sensitive hyperspectral ranges of leaf chlorophyll fluorescence, the correlationship between leaf chlorophyll fluorescence and hyperspectral reflectance was regressed and analyzed. Statistical results indicated that the 680 and 935 nm were the most sensitive hyperspectral bands for estimating leaf chlorophyll fluorescence. Then, 11 relative hyperspectral indices were selected based on the sensitive bands and previous literature. (R ₆₈₀ − R ₉₃₅)/(R ₆₈₀ + R ₉₃₅) and R ₆₈₀/R ₉₃₅ have higher correlationship coefficient (R) and lower root mean square error, may be used for detecting chlorophyll fluorescence, such as F _o, F _m, F _v/F _m, qP, and ΦPSII, while NPQ may be detected by (R ₇₈₀ − R ₇₁₀)/(R ₇₈₀ − R ₆₈₀). These results suggest that chlorophyll fluorescence of halophyte response to salinity stress could be identified by remote sensing.     

Best hyperspectral indices for tracing leaf water status as determined from leaf dehydration experiments

Leaf water status information is highly needed for monitoring plant physiological processes and assessing drought stress. Retrieval of leaf water status based on hyperspectral indices has been shown to be easy and rapid. However, a universal index that is applicable to various plants remains a considerable challenge, primarily due to the limited range of field-measured datasets. In this study, a leaf dehydration experiment was designed to obtain a relatively comprehensive dataset with ranges that are difficult to obtain in field measurements. The relative water content (RWC) and equivalent water thickness (EWT) were chosen as the surrogates of leaf water status. Moreover, five common types of hyperspectral indices including: single reflectance (R), wavelength difference (D), simple ratio (SR), normalized ratio (ND) and double difference (DDn) were applied to determine the best indices. The results indicate that values of original reflectance, reflectance difference and reflectance sensitivity increased significantly, particularly within the 350–700 nm and 1300–2500 nm domains, with a decrease in leaf water. The identified best indices for RWC and EWT, when all the species were considered together, were the first derivative reflectance based ND type index of dND (1415, 1530) and SR type index of dSR (1530, 1895), with R² values of 0.95 (p < 0.001) and 0.97 (p < 0.001), respectively, better than previously published indices. Even so, different best indices for different species were identified, most probably due to the differences in leaf anatomy and physiological processes during leaf dehydration. Although more plant species and field-measured datasets are still needed in future studies, the recommend indices based on derivative spectra provide a means to monitor drought-induced plant mortality in temperate climate regions.     

基于光谱指数的喀斯特植物叶片叶绿素含量定量估算

为了探讨适合于喀斯特植物叶片叶绿素含量估算的光谱指数,在总结以往基于光谱指数的植物生化参数估算研究基础上发现,常用光谱指数通常采用差值、比值、归一化以及倒数差值方式来构建。因此,我们通过上述4种光谱指数构建方式对所采集的4种典型喀斯特植物——黄荆(Vitex negundo)、盐麸木(Rhus chinensis)、朴树(Celtis sinensis)和红背山麻杆(Alchornea trewioides)叶片原始光谱反射率及其一阶导数值与同步测定的叶片叶绿素含量进行遍历分析,以期获得最优光谱指数并将其应用于喀斯特植物叶片叶绿素含量定量估算研究。结果表明：(1)常用光谱指数中,改良红边归一化指数(modified red-edge normalized difference vegetation index, mND705)对喀斯特植物叶片叶绿素含量估算效果较好(决定系数为0.45,均方根误差为0.26 mg·g^-1)。(2)虽然荧光比值(fluorescence ratio index, FRI1)和叶绿素吸收面积光谱指数(chlorophyll absorp...     

Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply

Plant nitrogen (N)deficiency often limits crop productivity. Early detection of plant N deficiency is important for improving fertilizer N-use efficiency and crop yield. An experiment was conducted in sunlit, controlled environment chambers in the 2001 growing season to determine responses of corn (Zea mays L. cv. 33A14) growth and leaf hyperspectral reflectance properties to varying N supply. Four N treatments were: (1) half-strength Hoagland's nutrient solution applied throughout the experiment (control); (2) 20% of control N starting 15 days after emergence (DAE); (3) 0% N starting 15 DAE; and (4) 0% N starting 23 DAE (0% NL). Plant height, the number of leaves, and leaf lengths were examined for nine plants per treatment every 3–4 days. Leaf hyperspectral reflectance, concentrations of chlorophyll a, chlorophyll b,and carotenoids, leaf and canopy photosynthesis, leaf area, and leaf N concentration were also determined during the experiment. The various N treatments led to a wide range of N concentrations (11 – 48 g kg^–1 DW) in uppermost fully expanded leaves. Nitrogen deficiency suppressed plant growth rate and leaf photosynthesis. At final harvest (42 DAE), plant height, leaf area and shoot biomass were 64–66% of control values for the 20% N treatment, and 46-56% of control values for the 0% N treatment. Nitrogen deficit treatments of 20% N and 0% N (Treatment 3) could be distinguished by changes in leaf spectral reflectance in wavelengths of 552 and 710 nm 7 days after treatment. Leaf reflectance at these two wavebands was negatively correlated with either leaf N (r = –0.72 and –0.75^**) or chlorophyll (r = –0.60 and –0.72^**) concentrations. In addition, higher correlations were found between leaf N concentration and reflectance ratios. The identified N-specific spectral algorithms may be used for image interpretation and diagnosis of corn N status for site-specific N management.     

利用高光谱参数反演水稻叶片类胡萝卜素含量

为了探讨快速、准确预测水稻(Oryza sativa)叶片类胡萝卜素(Car)含量的敏感光谱波段和光谱指数, 通过实施涉及不同年份、不同生态点、不同施氮水平和不同品种类型的4个田间试验, 于主要生育期同步测定了水稻顶部4张叶片的光谱反射率及Car含量, 系统分析了350-2 500 nm范围内任意两波段组合而成的比值(SR (λ1, λ2))、归一化(ND (λ1, λ2))及已报道的对Car敏感的光谱指数与水稻叶片Car含量间的定量关系。结果表明, 不同Car含量水平下水稻叶片光谱反射率存在着明显变化, 以绿光及红边波段对水稻叶片Car含量变化最为敏感。723 nm附近的波段与近红外波段的比值组合以及713 nm附近的波段与近红外波段的归一化组合可以较好地预测水稻叶片Car含量, 以SR (723, 770)和ND (770, 713)表现最好, 线性拟合R²分别达到0.897和0.898。基于独立的试验资料的检验表明, 预测值和实测值的拟合R²分别为0.856和0.858, 均方根差RMSE均为0.072, 平均相对误差RE分别为11.9%和12.0%, 表明SR (723,770)和ND (770, 713)可有效地估算水稻上部叶片的Car含量。     

Nondestructive determination of leaf chlorophyll content in two flowering cherries using reflectance and absorptance spectra

Leaf chlorophyll quantification is a key technique in tree vigor assessment. Although many studies have been conducted on nondestructive and in-field spectroscopic determination, it is reasonable to develop species-specific chlorophyll indices for accurate determination, because leaf spectra can vary independently of chlorophyll content due to leaf surface and structural differences among species. The present study aimed to develop optimal reflectance and absorptance indices for estimating the leaf chlorophyll content of Cerasus jamasakura (Siebold ex Koidz.) H. Ohba var. jamasakura and Cerasus × yedoensis ‘Somei-yoshino,’ and to examine their performance by comparing them with 46 published chlorophyll indices and SPAD. For 96 and 100 leaf samples, measurements were taken using a spectroradiometer with a leaf-clip attachment and a SPAD-502 chlorophyll meter, and chlorophyll content was determined by extraction with N,N′-dimethylformamide. The optimal leaf chlorophyll indices were then developed systematically by testing eight types of indices. As a result, we confirmed that the optimal chlorophyll indices performed better than any of the published leaf chlorophyll indices or SPAD, giving RMSEs that were approximately twice as good as those for SPAD, and found that the newly proposed index type—a difference and ratio combination type—may be a useful form of chlorophyll content estimation. We also found that absorptance indices achieved equivalent results to reflectance indices despite the hypothesis that absorptance measurement is direct and has more potential. Among the published indices, the reflectance ratio index of Datt [Datt B (1999) Int J Remote Sens 20(14):2741–2759] and the red edge chlorophyll index of Ciganda et al. [Ciganda V, Gitelson A, Schepers J (2009) J Plant Physiol 166:157–167] were effective at estimating the leaf chlorophyll contents of both flowering cherries.     

Spectral reflectance indices and pigment functions during leaf ontogenesis in six subtropical landscape plants

Pigment combinations are regulated during leaf ontogenesis. To better understand pigment function, alterations in chlorophyll, carotenoid and anthocyanin concentrations were investigated during different leaf development stages in six subtropical landscape plants, namely Ixora chinensis Lam, Camellia japonica Linn, Eugenia oleina Wight, Mangifera indica L., Osmanthus fragrans Lowr and Saraca dives Pierre. High concentrations of anthocyanin were associated with reduced chlorophyll in juvenile leaves. As leaves developed, the photosynthetic pigments (chlorophyll and carotenoid) of all six species increased while anthocyanin concentration declined. Chlorophyll fluorescence imaging of Φ_PSII (effective quantum yield of PSII) and of NPQ (non-photochemical fluorescence quenching) and determination of electron transport rate-rapid light curve (RLC) showed that maximum ETR (leaf electron transport rate), Φ_PSII and the saturation point in RLC increased during leaf development but declined as they aged. Juvenile leaves displayed higher values of NPQ and Car/Chl ratios than leaves at other developmental stages. Leaf reflectance spectra (400–800 nm) were measured to provide an in vivo non-destructive assessment of pigments in leaves during ontogenesis. Four reflectance indices, related to pigment characters, were compared with data obtained quantitatively from biochemical analysis. The results showed that the ARI (anthocyanin reflectance index) was linearly correlated to anthocyanin concentration in juvenile leaves, while a positive correlation of Chl NDI (chlorophyll normalized difference vegetation index) to chlorophyll a concentration was species dependent. Photosynthetic reflectance index was not closely related to Car/Chl ratio, while a structural-independent pigment index was not greatly altered by leaf development or species. Accordingly, it is suggested that the high concentration of anthocyanin, higher NPQ and Car/Chl ratio in juvenile leaves are important functional responses to cope with high radiation when the photosynthetic apparatus is not fully developed. Another two leaf reflectance indices, ARI and Chl NDI, are valuable for in vivo pigment evaluation during leaf development.     

Spatial patterning of pigmentation in evergreen leaves in response to freezing stress

Evergreen leaves of temperate climate plants are often subject to frosts. Changes in carbon gain patterns arise from freezing‐related tissue damage, and from interactions between light and temperature stress. We examined relationships between spatial patterns in freezing and concentrations of chlorophyll. Spatial patterns in pigmentation in leaves that had or had not been exposed to naturally occurring frosts were determined by conventional extraction techniques combined with high‐resolution hyperspectral imaging of reflectance from intact leaves. Predictive indices were developed to relate reflectance to chlorophyll content and chlorophyll a/b ratios within intact leaves. Leaves exposed to frosts had lower chlorophyll contents and more variable a/b ratios than protected leaves. In frost‐affected leaves, chlorophyll content was highest near leaf centres and decreased toward leaf tips and margins. Decline in chlorophyll content was associated with shifts in chlorophyll a/b ratios and increases in red pigmentation due to anthocyanin, with effects being greater on leaf sides exposed directly to the sun. These altered pigmentation patterns were consistent with patterns in freezing. The present results illustrate the fine scale of spatial variation in leaf response to freezing, and raise important questions about impacts of freezing on photosynthetic function in over‐wintering evergreens.     

Hyperspectral discrimination of coral reef benthic communities in the western Caribbean

Determining a subset of wavelengths that best discriminates reef benthic habitats and their associated communities is essential for the development of remote sensing techniques to monitor them. This study measured spectral reflectance from 17 species of western Caribbean reef biota including coral, algae, seagrasses, and sediments, as well as healthy and diseased coral. It sought to extend the spectral library of reef-associated species found in the literature and to test the spectral discrimination of a hierarchy of habitats, community groups, and species. We compared results from hyperspectral reflectance and derivative datasets to those simulated for the three visible multispectral wavebands of the IKONOS sensor. The best discriminating subset of wavelengths was identified by multivariate stepwise selection procedure (discriminant function analysis). Best discrimination at all levels was obtained using the derivative dataset based on 6–15 non-contiguous wavebands depending on the level of the classification, followed by the hyperspectral reflectance dataset which was based on as few as 2–4 non-contiguous wavebands. IKONOS wavebands performed worst. The best discriminating subset of wavelengths in the three classification resolutions, and particularly those of the medium resolution, was in agreement with those identified by Hochberg and Atkinson (2003) and Hochberg et al. (2003) for reef communities worldwide. At all levels of classification, reflectance wavebands selected by the analysis were similar to those reported in recent studies carried out elsewhere, confirming their applicability in different biogeographical regions. However the greater accuracies achieved using the derivative datasets suggests that hyperspectral data is required for the most accurate classification of reef biotic systems.     

The independent detection of drought stress and leaf density using hyperspectral resolution data

Measurement of vegetation drought stress or leaf density is essential in ecosystem and agronomic studies. The normalized differential vegetation index (NDVI), a widely used vegetation index in remote sensing, seems to have some limitations as it is known to be affected by both drought stress and leaf density. A field experiment was conducted, using two-year-old potted Quercus serrata (a deciduous tree) and Q. glauca (an evergreen tree), to determine the optimal indices of vegetation drought stress or leaf density that have the least a simultaneous effect, and to test if the existing vegetation indices are useful for independently detecting drought stress or leaf density. The results showed that NDVI and similar indices, which utilize the difference or ratio between the reflectance of red and near infrared bands, such as the ratio vegetation index (RVI), the difference vegetation index (DVI), the atmospherically resistant vegetation index (ARVI), the renormalized difference vegetation index (RDVI), the enhanced vegetation index (EVI), the perpendicular vegetation index (PVI), soil-adjusted vegetation index (SAVI) and the improved variants of SAVI, were effective for the independent detection of leaf density but relatively ineffective for drought stress because they were significantly affected by leaf area index (LAI). Similarly, vegetation indices developed as detectors of vegetation stress, such as the water index (WI), the stress index (SI) and the derivative chlorophyll index (DCI), showed weak correlation (r) and partial correlation (r _p) with leaf water content (LWC). The optimal hyperspectral indices were proposed as (F _502.8 − F _852.0)/(F _502.8 + F _852.0) for LWC (r = 0.847, r _p = 0.849) and R ₇₅₀/R ₅₅₀ (R750R550; Lichtenthaler et al. in J Plant Physiol 148:483–493, 1996) for LAI (r = 0.926, r _p = 0.940) where R _λ and F _λ represent reflectance and first derivatives at wavelength λ nm, respectively. A simulation of lower spectral sampling intervals (ca. 3-nm intervals of original to 10-nm intervals) indicated that it will be necessary to check the appropriateness of the derivative indices approximate to the proposed indices before application because derivative spectra are less smooth as a function of wavelength than reflectance spectra.     

基于实地调查和高光谱数据的浑善达克沙地中部植物alpha多样性遥感估测

植物群落物种多样性的快速无损估测一直是近几十年生态学领域的热点研究问题。相对于大尺度的卫星遥感数据,高光谱遥感数据具有光谱和空间分辨率高的优势。采用ASD HH2便携式高光谱仪,收集浑善达克沙地中部120个样方的高光谱数据,并对样方的alpha多样性指数进行同步测定。对高光谱遥感数据进行预处理,采用相关性分析、主成分分析和经验波段筛选法,从数百个波段中选择敏感波段。采用90个样方的高光谱数据作为训练样本,对筛选的敏感波段进行多元线性逐步回归分析,获得12个回归模型。采用另外30个样方的高光谱数据作为验证样本,对回归模型的拟合效果进行检验。结果发现,采用主成分分析法提取敏感波段的回归模型拟合效果最好,Pielou指数、Shannon-Wiener指数和Simpson指数拟合均达到显著水平。对我国植物物种多样性微尺度的快速评估和高光谱遥感具有一定参考意义,并对未来植物多样性高光谱遥感研究提出了建议。     

铝胁迫对蓼科植物生长和光合、蒸腾特性的影响

采用水培试验,设置5种铝处理浓度,研究了铝对3种蓼科植物酸模叶蓼、杠板归和辣蓼叶片光合、蒸腾和叶绿素荧光参数的影响。结果表明,高铝处理(400μmol.L-1)显著抑制3种蓼科植物地上部和根系生长,并且导致3种蓼科植物叶片叶绿素含量、Chla/Chlb、净光合速率(Pn)、水分利用效率(WUE)、PSII光合电子传递量子效率(φPSII)和光化学猝灭系数(qP)显著下降。中低铝处理(25~100μmol.L-1)时,与对照相比,酸模叶蓼生物量显著增加,杠板归显著减少,辣蓼先增加后减少。其中,酸模叶蓼和辣蓼叶绿素含量、Chla/Chlb、Pn、蒸腾速率(Tr)、胞间CO2浓度(Ci)、PSII最大光化学效率(Fv/Fm)、qP均未发生显著变化,但辣蓼WUE、φPSII和非光化学猝灭系数(NPQ)显著下降,酸模叶蓼无显著变化;而杠板归除Ci、Fv/Fm外,其余叶片光合、蒸腾及叶绿素荧光参数均出现显著下降。上述结果表明,酸模叶蓼在中低铝处理条件下可通过保持较高的叶绿素含量、Chla/Chlb、WUE、Pn、PSII反应中心光化学反应效率以及提高非辐射能量耗散来增强其对铝的耐性。     

福建梅花山57种常绿树叶片叶绿素特征分析

选取福建梅花山海拔1200m和455m地区57种常绿植物为研究对象,测定两海拔的植物叶片叶绿素a和叶绿素b含量,并计算叶绿素a/b、总叶绿素含量。结果表明:(1)植物叶绿素a、b,叶绿素a+b及叶绿素a/b值大多分布在一个相对集中的区域。(2)多数植物新叶叶绿素含量高于老叶,叶绿素a/b值低于老叶,但是新、老叶无显著差异。(3)不同海拔的植物叶片总叶绿素含量和叶绿素a/b值有明显差异,低海拔地区明显高于高海拔地区。植物通过总叶绿素含量和a/b值的变化以适应不同环境条件。     

<Emphasis Type="Italic">Petunia</Emphasis> × <Emphasis Type="Italic">hybrida</Emphasis> during transition to flowering as affected by light intensity and quality treatments

Petunia × hybrida was grown under high (H), medium (M) and low (L) light intensity [photoperiod; 16 h d⁻¹, photosynthetic photon flux density (PPFD); 360, 120 and 40 μmol m⁻² s⁻¹, respectively] as well as under end-of-day (EOD) red (R) and far-red (FR) light quality treatments [photoperiod; 14.5 h d⁻¹, PPFD; 30 μmol m⁻² s⁻¹ EOD; 15 min, Control (C) light; without EOD light treatment]. Shoot growth, leaf anatomical and photosynthetic responses as well as the responses of peroxidase (POD) isoforms and their specific activities following transition to flowering (1–6 weeks) were evaluated. Flower bud formation of Petunia × hybrida was achieved at the end of the 4th week for H light treatment and on the end of the 6th week for FR light treatment. No flower bud formation was noticed in the C and R light treatments. H and M light treatments induced lower chlorophyll (Chla, Chlb, Chla+b) concentrations in comparison to L light. On the other hand R and FR light chlorophyll content were similar to C light. Photosynthetic parameters [CO₂ assimilation rate (A), transpiration rate (E) and stomatal conductance (g _s) values] were higher in the H light treated plants in comparison to M and L light treated plants. A, E and g _s values of R and FR light were similar to C light plants. Leaf anatomy revealed that total leaf thickness, thickness of the contained tissues (epidermis, palisade and spongy parenchyma) and relative volume percentages of the leaf histological components were differently affected within the light intensity and the light quality treatments. POD specific activities increased from the 1st to the 6th week during transition to flowering. Native-PAGE analysis revealed the appearance of four anionic POD (A₁–A₄) isoforms in all light treatments. On the basis of the leaf anatomical, photosynthetic and plant morphological responses, the production of high quality Petunia × hybrida plants with optimal flowering times could be achieved through the control of both light intensity and light quality. The appearance of A₁ and A₂ anionic POD isoforms could be also used for successful scheduling under light treatments.     

Estimating biophysical parameters of rice with remote sensing data using support vector machines

Hyperspectral reflectance (350–2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application. Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters, comprising leaf area index (LAI; m² green leaf area m⁻² soil) and green leaf chlorophyll density (GLCD; mg chlorophyll m⁻² soil), using stepwise multiple regression (SMR) models and support vector machines (SVMs). Four transformations of the rice canopy data were made, comprising reflectances (R), first-order derivative reflectances (D1), second-order derivative reflectances (D2), and logarithm transformation of reflectances (LOG). The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI, with a root mean square error (RMSE) of 1.0496 LAI units. The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD, with an RMSE of 523.0741 mg m⁻². The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters, but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.     

基于小波分析的大豆叶绿素a含量高光谱反演模型

 2003和2004年分别在长春市良种场和中国科学院海伦黑土生态实验站实测了大田耕作与水肥耦合作用下大豆（Glycine max）冠层高光谱反射率 与叶绿素a含量数据,对光谱反射率、微分光谱与叶绿素a含量进行了相关分析;采用归一化植被指数(Normalized diffe rence vegetation index, NDVI)、土壤调和植被指数(Soil-adjusted vegetation index, SAVI)、再归一植被指数(Renormalized difference vegetation index, RDVI)、第二修正比值植被指数(Modified second ratio index, MSRI)等建立了大豆叶绿素a反演模型;应用小波分析对采集的光谱反 射率数据进行了能量系数提取,并以小波能量系数作为自变量进行了单变量与多变量回归分析,对大豆叶绿素a进行了估算。研究结果表明,大 豆叶绿素a 与可见光光谱反射率相关性较好,并在红光波段取得最大值(R²>0.70),但在红边处,微分光谱与大豆叶绿素a的相关性较反射率好 得多,在其它波段则相反;由NDVI、SAVI、RDVI、MSRI等植被指数建立的估算模型可以提高大豆叶绿素a的估算精度（R²>0.75）;小波能量系 数回归模型可以进一步提高大豆叶绿素a含量的估算水平,以一个特定小波能量系数作为自变量的回归模型,大豆叶绿素a回归决定系数R²高达 0.78;多变量回归分析结果表明,大豆叶绿素a实测值与预测值的线性回归决定系数R²均高达0.85。以上结果表明, 小波分析可以对高光谱进 行特征变量提取,并可在一定程度上提高大豆生理参数反演精度。     

Spectral discrimination of coral reef benthic communities

Effective identification and mapping of coral reef benthic communities using high-spatial and -spectral resolution digital imaging spectrometry requires that the different communities are distinguishable by their spectral reflectance characteristics. In Kaneohe Bay, Oahu, Hawaii, USA, we collected in situ a total of 247 spectral reflectances of three coral species (Montipora capitata, Porites compressa, Porites lobata), five algal species (Dictyosphaeria cavernosa, Gracilaria salicornia, Halimeda sp., Porolithon sp., Sargassum echinocarpum) and three sand benthic communities (fine-grained carbonate sand, sand mixed with coral rubble, coral rubble). Major reflectance features were identified by peaks in fourth derivative reflectance spectra of coral (at 573, 604, 652, 675 nm), algae (at 556, 601, 649 nm) and sand (at 416, 448, 585, 652, 696 nm). Stepwise wavelength selection and linear discriminant function analysis revealed that spectral separation of the communities is possible with as few as four non-contiguous wavebands. These linear discriminant functions were applied to an airborne hyperspectral image of a patch reef in Kaneohe Bay. The results demonstrate the ability of spectral reflectance characteristics, determined in situ, to discriminate the three basic benthic community types: coral, algae and sand. Accepted: 12 January 2000     

基于高光谱遥感的小麦冠层叶片色素密度监测

作物叶片色素状况是评价植株光合效率和营养胁迫的重要指标,冠层叶片色素密度（单位土地面积叶片色素总量）的实时无损监测对作物生长诊断、产量估算及氮素管理具有重要意义。以包括不同品质类型（高蛋白、中蛋白和低蛋白）的多个小麦品种在不同施氮水平下的连续2a大田试验为基础,研究了小麦叶片色素密度与冠层高光谱参数的定量关系。结果表明,叶片色素（叶绿素a、叶绿素b、叶绿素a＋b和类胡萝卜素）密度随施氮水平增加而提高,不施氮处理的叶片色素密度随生育进程而下降,施氮处理的叶片色素密度呈单峰曲线,品种间存在明显差异。群体叶片色素密度的敏感波段主要分布在可见光区,而红边区域导数光谱表现更显著。光谱参数VOG2、VOG3、RVI（810,560）、SRE／SBE和SDr／SDb等与叶绿素密度关系较为密切,线性方程决定系数R^2均在0．858以上,而与类胡萝卜素密度关系减弱,决定系数R^2低于0．780,且参数间差异较小。经独立试验资料的检验表明,VOG2、VOG3、SRE／SBE和SDr／SDb对不同色素的估测结果较好,预测相对误差RE低于17．6％,虽然对叶绿素b的准确性稍低。总体上,光谱参数VOG2、VOG3、SRE／SBE和SDr／SDb与小麦群体叶片色素密度关系密切,特别是对叶片叶绿素a和叶绿素a＋b的密度可以进行准确可靠的实时监测。