DRIED GRASS SILAGE ANALYSIS BY NIR REFLECTANCE SPECTROSCOPY-A COMPARISON OF STEPWISE MULTIPLE LINEAR AND PRINCIPAL COMPONENT TECHNIQUES FOR CALIBRATION DEVELOPMENT ON RAW AND TRANSFORMED SPECTRAL DATA

Calibrations to predict crude protein (CP) and in vitro dry matter digestibility (IVDMD) in dried grasssilage from reflectance data collected at 19 wavelengths on an InfraAlyzer 400R have been developedusing stepwise multiple linear (SML) and principal component (PC) regression techniques. A directcomparison of the efficacy of each multivariate technique in this application has been possible by usingidentical calibration development and evaluation sample sets. The effect of two data transformation stepsprior to PC regression was also investigated. PC regression of raw reflectance data yielded no significantimprovement in the standard errors of prediction (SEP) for CP and IVDMD over those obtained bySMLR, viz. 0.61 vs 0.63 and 2.9 vs 3.0 respectively. Computation time for development and evaluation ofthe PC regression equation was less than for selection of the best SMLR equation, and PCR equationsmay be more robust. Data transformation to reduce granularity effects prior to PCR did not produce anyimprovement in predictive accuracy for either IVDMD or CP.     

DETECTING AND ADJUSTING FOR NON-LINEARITIES IN CALIBRATION OF NEAR-INFRARED DATA USING PRINCIPAL COMPONENTS

A new regression method for non-linear near-infrared spectroscopic data is proposed.The technique isbased on a model which is linear in the principal components and simple functions(squares and products)of them.Added variable plots are used to determine which squares and products to incorporate into themodel.The regression coefficients are estimated by a Stein estimate which shrinks towards the estimatedetermined by the first several principal components and the selected non-linear terms.The technique isnot computationally intensive and is appropriate for routine predictions of chemical concentrations.Themethod is tested on three data sets and in all cases gives more accurate predictions than does linearprincipal components regression.     

USE OF THE KALMAN FILTER FOR MULTIVARIATE CALIBRATION IN A REAL SYSTEM AND ITS COMPARISON WITH CLS AND PURE COMPONENT CALIBRATION METHODS

The usefulness of the Kalman filter as an algorithm for calibration in a real system is shown. Results arecompared with classical least squares and pure component calibration. The prediction of four prioritypollutant chlorophenols in binary, ternary and quaternary mixtures was also carried out by Kalmanfiltering. The condition number, standard deviation and prediction error have been employed to choosethe most suitable wavelength range. Comparison of the standard error of prediction in the validation setshows significant differences between the evaluated chlorophenols, the best results being obtained withKalman multivariate calibration.     

洪河自然保护区乌拉苔草生物量高光谱遥感估算模型

尝试用不同方法构建洪河自然保护区湿地植被乌拉苔草(Carex meyeriana)的高光谱植被指数,建立水上鲜/干生物量高光谱估算模型,并比较了不同模型的反演精度。通过实测不同覆盖度和水深状况下乌拉苔草的冠层高光谱反射率与水上生物量的数据,采用高光谱可见光—近红外波段及其微分光谱波段(350~1 050 nm)逐波段构建FNDVI、FRVI、FDVI、FDNDVI、FDRVI、FDDVI植被指数,分别找出与水上鲜生物量和干生物量具有最佳相关性波段组合的植被指数,建立乌拉苔草水上生物量的最佳估算模型,并对比分析了反射率光谱植被指数(FNDVI、FRVI、FDVI)模型和微分光谱植被指数(FDNDVI、FDRVI、FDDVI)模型的反演精度。结果显示,微分光谱与乌拉苔草水上生物量的相关性比反射率光谱好;微分光谱植被指数与乌拉苔草水上生物量的相关性比反射率光谱植被指数好,尤其以微分光谱植被指数FDRVI与FDNDVI建立的二次函数模型反演乌拉苔草的水上鲜生物量和干生物量的效果最好,精度分别达74.9%、71.4%,其均方根误差分别为0.074 4和0.026 2,通过了p<0.01极显著验证。这表明,采用微分光谱植被指数FDRVI、FDNDVI对乌拉苔草水上鲜生物量和干生物量的估算可以取得较高的预测精度。     

THREE-WAY METHODS FOR THE CALIBRATION OF CHROMATOGRAPHIC SYSTEMS:COMPARING PARAFAC AND THREE-WAY PLS

For the calibration of chromatographic systems,different methods can be used.One class of methodsutilizes three-way approaches.The calibration problem is stated in such a way that the decompositionof a three-way array can serve for the prediction of retention on new stationary phases.Two three-way approaches are presented:the Unfold-PCA and PARAFAC models.The theory ofboth methods is presented and the differences are highlighted,the main difference being that PARAFACis a trilinear decomposition whereas Unfold-PCA is not.Both three-way methods are evaluated on asmall data set consisting of retention measurements of eight solutes at six mobile phase compositions onsix stationary phases.The differences in performance of the two models are minor,For calibration purposes,two variants of the methods are discussed:three-way PLS and an extensionof PARAFAC.Again the theory and differences between the two methods are explained.The predictiveperformance of the two methods is compared using the same data set as earlier.The differences inpredictive performance,however,are minor.Both methods are capable of predicting 98% of thevariation in the test sets.Yet,there are other considerations when comparing methods than predictiveperformance,e.g.the quality of the predictions.     

塔里木河荒漠植被光谱可分性模拟

以塔里木河典型植被为研究对象,分析胡杨、芦苇叶片及柽柳冠层的可分性,并计算背景的影响。首先用ASD光谱仪测新鲜叶片光谱,找出光谱特征点;然后模拟EO-1高光谱数据和TM多光谱数据;最后植被与土壤光谱按比例混合,分析背景的影响。以上三步分别计算植被指数（VI）。结果显示:叶片光谱特征位置430 nm、670 nm、750 nm附近,黄边斜率和红外平台平均高度,1 080~1 280 nm、1 430~1 650 nm能够区分塔里木河流域3个主要植被类型。模拟的EO-1波谱保持了控制波形的10个特征,TM 只有绿反射峰和红吸收谷、近红外1个反射峰3个特征,大部分特征都消失了。植被指数显示(R680-R500)/R750、(R680-R550)/R705、R1430+\:+R1650、D712/D688能够区分3类,且指数值差异较大,为绿峰、红谷和近红外波峰的组合;模拟的EO-1数据(R680-R500)/R750、(R680-R550)/R705、R1430+\:+R1650能分别区分植被,TM多波谱数据不能有效区分植被。     

基于TM数据的太湖叶绿素a浓度定量遥感反演方法研究

探讨利用常规卫星遥感数据Landsat/TM定量反演太湖叶绿素a(Chl-a)浓度的方法。在对Landsat/TM影像进行几何校正、辐射定标、大气校正等预处理的基础上,选择适于太湖Chl-a浓度定量反演的最佳波段或波段组合,采用半经验回归模型和混合光谱分解模型分别建立太湖Chl-a浓度定量反演模型,并对不同模型及反演结果进行对比分析。     

基于随机森林算法的土壤有机质含量高光谱检测

为了探讨既能保留光谱信息又能准确对土壤有机质含量进行快速检测。以新疆南部渭干河—库车绿洲内部73个土壤样点及其对应的高光谱数据为研究对象,采用小波变换与数学变换进行光谱数据预处理,分析各小波分解重构光谱在不同有机质含量与不同土壤类型下光谱曲线差异,通过相关分析确定最大小波分解层并筛选敏感波段,结合灰色关联分析与随机森林预测分类模型对各小波分解特征光谱进行重要性分析,最后基于最优特征光谱建立多元线性预测模型并进行分析。结果表明：（1） 耕作土壤与林地土壤光谱曲线波段相较盐渍土壤和荒漠土壤光谱曲线变化较为平缓,同时在水分吸收波段处,盐渍土壤光谱曲线吸收谷最深。（2） 小波变换分解光谱与土壤有机质含量的相关性随着分解层数增加呈现先减后增趋势,在第6层中,特征光谱曲线与敏感波段数量变化趋于稳定,确定为小波变换最大分解层。（3） 随机森林模型相比灰色关联分析对于各小波分解层因子的筛选符合预期,按照对土壤有机质含量影响从高到低排序为L3-(1/LgR)′、L4-(1/LgR)′、L6-(1/LgR)′、L5-(1/LgR)′、L2-(1/LgR)′、L0-1/LgR、L1-1/LgR。（4）在小波分解光谱中,中频范围特征光谱对干旱区土壤有机质含量的估测能力优于高频与低频范围特征光谱,同时基于L-MC建立的模型精度最高。研究表明：基于机器学习分类方法结合小波分解的土壤光谱有机质含量监测,可以有效的减少噪声波段干扰,并提高特征波段的分类预测精度。     

基于HJ-1B数据的雪盖提取方法研究——以军塘湖流域为例

 HJ-1A、1B卫星具有较高的时间和空间分辨率,适合小流域尺度的积雪动态监测研究。本文基于HJ-1B数据,选取军塘湖流域,针对同时具有HJ-1B/CCD、IRS数据和只有HJ-1B/CCD数据两种情况展开雪盖提取方法研究。对于第一种情况,因研究区南端有大面积森林覆盖,会影响雪像元识别,选用[WTBX]NDSI[WTBZ]和[WTBX][STBX]S3[WTBZ][STBZ]两种雪盖指数,并利用[WTBX]NDVI[WTBZ]或TM影像反演的林区辅助判识积雪。结果表明:当有植被信息辅助分类时,两种雪盖指数均能较好提取出森林覆盖区的积雪,且提取结果基本一致,精度较高。对于第二种情况,因无法计算雪盖指数,采用光谱与纹理信息结合的SVM法提取雪盖,提取的面积和精度与上述方法相比略低,但很接近,说明在缺少[WTBX]IRS[WTBZ]数据的情况下,仅利用CCD仍可提取出较为准确的雪盖,满足实际应用需求。     

Evaluation of various satellite sensors for waterline extraction in a coral reef environment: Majuro Atoll, Marshall Islands

The ability of five satellite sensor bands (IKONOS band 4, Terra ASTER bands 3 and 4, and Landsat ETM+ bands 4 and 5) was examined to extract the waterline at coral reef coasts (Majuro Atoll, Marshall Islands) using different wavelength regions (near infrared [NIR] and shortwave infrared [SWIR]) and different spatial resolutions (4, 15, and 30 m). After performing georeferencing and normalization of the images, density slicing was used to extract the waterline. Comparisons of extracted waterline positions with ground-level data for eight transects and global positioning system (GPS) tracks of the island shorelines showed that NIR bands were superior to SWIR bands because of the characteristics of the coral reef coasts, including a lack of foam and suspended sediments (which can affect the NIR wavelength region, if present) and the presence of remnant water on reef flats during low tide (which can affect the SWIR wavelength region). A linear relationship was found between the estimation errors of waterline positions and the spatial resolutions of the NIR sensors. Analysis on estimation errors and image costs showed that Terra ASTER band 3 was the most cost-effective sensor for extracting waterlines with reasonable accuracy. The results serve as general guidelines for using satellite-derived data to estimate intertidal topography and detect and monitor shorelines in coral reef environments.     

水分胁迫条件下棉花生理变化及其高光谱响应分析

利用ASD地物光谱仪,测定水分胁迫条件下棉花不同生育时期内叶片的光谱反射率,应用微分技术处理棉花的反射光谱,并结合棉花叶面积指数(LAI)、叶绿素(a b)含量(Chlt)、叶片全氮(TN)含量等生物参数进行分析,研究棉花水分胁迫情况下的高光谱特征,结果表明,一阶微分光谱720nm波段的数值与LAI的正相关(R=0．7656);750nm处一阶微分值与叶绿素含量呈显著正相关关系(R=0．7774);微分光谱690nm～740nm数值积分面积与TN含量呈正相关(R=0．7669),采用比值反射率对反射光谱1300nm～1500nm波段范围内最小值与棉花叶片的含水量作相关分析,达到极显著水平(R^2=0．8298),验证了一阶微分光谱数据与棉花的生理参数有很好的相关性,可见光和近红外波段光谱反射率能够反映出棉花生长发育的动态特征;证明了棉花的花铃期是高光谱遥感对棉花长势和生理参数定量诊断的最佳时期。本研究通过建立一系列线性光谱模型对棉花生理参数进行估测,为基于高光谱数据的棉花生长模型和棉花长势的遥感监测提供了理论依据。     

莱州湾海岸带土壤光谱分析与有机质反演研究

利用土壤光谱反射率预测海岸带典型土壤有机质含量。对莱州湾海岸带典型地区97个土壤样本的光谱反射率特性进行分析,把光谱曲线划分为4个区域,提取每个区域的代表性特征参数,与土壤有机质含量进行相关性分析,最终选用458～587.1nm区间的挠度(相关系数达0.87)作为自变量进行模型回归,并利用均方根误差(RMSE)和预测残差(RPD)进行模型检验与评价。结果表明,以458～587.1nm区间的挠度作为自变量建立的对数函数预测模型具有较高的精度和稳定性,经验证计算出其RMSE为0.39,RPD为2.5,该模型应用效果较好。     

反射光谱技术:研究南极企鹅古生态演化的一种新方法

为探求快速、廉价、无损和同步的光谱技术在南极生态环境研究中的可能性,本文利用南极阿德雷岛的四根企鹅粪土沉积柱样品的反射光谱,通过逐步多元线性回归和主成分回归两种数学运算方法,建立了反射光谱数据与企鹅粪九种标型元素浓度之间的关系,并探讨了南极企鹅粪土沉积物光谱数据的古生态意义。结果表明:南极粪土沉积样品反射率光谱与企鹅粪九种标型元素(P、Ca、Cu、F、Ba、S、Zn、Sr、Se)含量之间存在良好的相关性,预测值与实测值之间的相关系数R都达到了0.9以上,在深度剖面上预测浓度与实测浓度具有非常一致的变化趋势;南极粪土沉积物光谱数据包含有明确的古生态变化信息,可利用主成分分析快速恢复历史时期企鹅数量演化过程。本研究结果为在偏远的南极地区开展古生态环境研究提供了一种新的快捷方法和技术途径。     

Evaluation of a curve-fitting method for diffuse reflectance spectra in the UV–Visible–NIR wavelength region

The Modified Gaussian Method (MGM) proposed by Sunshine et al. [Sunshine, J.M., Pieters, C.M., Pratt, S.F., 1990. Deconvolution of mineral absorption bands: an improved approach. Journal of Geophysical Research 95, 6955–6966.] is generally used to decompose spectra in the UV–Visible–NIR wavelength region into the characteristic absorption bands of minerals. Here, we compare the optimized results obtained using different curve-fitting methods for this spectrum. The result obtained using the Gaussian function for the absorption band shows a better fit than that obtained using the Lorentzian function. The background continuum of a quadratic polynomial for the wavenumber provides a better result than does the linear function for the wavenumber. We successfully decomposed the spectra of ordinary chondrites and eucrites into the absorption bands of olivine and pyroxene. The wavelength positions of these absorption bands are broadly consistent with the Fe contents of olivine and pyroxene. Although the present results are derived from a limited number of spectra, they are of use in terms of the decomposition of diffuse reflectance spectra.     

荒漠-绿洲交错带土壤N、P、K含量的高光谱反演模型

利用新疆奇台县荒漠-绿洲交错带的75个土壤样本,选取土壤可见光-近红外光谱的反射率（R）、光谱反射率倒数之对数（lg（1/R））、光谱反射率一阶导数（FDR）和光谱波段深度（Depth）4个指标,分析了其与土壤N、P、K元素含量的关系,分别建立了反演模型并对其精度进行了检验。结果表明：可见光-近红外反射光谱快速估算荒漠-绿洲交错带土壤N、P、K元素含量的潜力大,其预测精度由高到低的排列顺序为：N>P>K。不同光谱指标反演模型的精度各异,指标Depth和FDR的预测效果明显优于lg（1/R）和R,对N和P元素的拟合效果为：lg（1/R）相似文献   

基于HJ1A-HSI超光谱影像的耕地有机质遥感定量反演

以环境小卫星超光谱影像为主要数据源,在耕地有机质实测样本的支持下,开展光谱反射率及其变化形式与有机质的相关性分析,筛选耕地有机质响应的敏感波段与特征组合算法,利用多元回归分析方法,建立基于HSI影像的耕地有机质定量反演模型。研究结果表明,耕地有机质的HSI影像响应波段均位于可见光与近红外波段间,其中以540～860nm范围最佳,相关系数均在0.5左右;HSI反射率对数一阶微分预测模型精度最高,模型及其检验的决定系数都在0.7以上,均方根误差在0.2%左右,可用于顺义区耕地有机质全覆盖空间填图。因此,环境小卫星的超光谱影像对耕地有机质含量具有较好的光谱响应能力,其空间覆盖能力有助于开展县域尺度的耕地有机质遥感反演和空间填图。     

Sediment yield and spurious correlation—toward a better portrayal of the annual suspendend-sediment load of rivers

Bivariate relations between annual sediment yield (tons per year per unit drainage area) and drainage-basin area are spurious because drainage-basin area is common to both axes. Two alternative methods for portraying the annual suspended-sediment load of a river are suggested. One method consists of plotting suspended-sediment load (tons per year) against distance downstream. Such plots indicate that annual suspended-sediment load does not necessarily have a linear relationship with distance. The second method consists of plotting annual suspended-sediment load against drainage-basin area. Both methods more accurately portray fundamental relations between annual sediment load and drainage-basin characteristics than does the yield-area relation because spurious correlation is avoided. Plots were made of annual suspended-sediment load versus time for several stations along each of eight rivers for the 10–15 years of available data. The plots are in-phase with respect to relative magnitude of annual sediment loads.     

REMOTE SENSING FOREST BIOMASS: AN EVALUATION USING HIGH RESOLUTION REMOTE SENSOR DATA AND LOBLOLLY PINE PLOTS

Eight-year-old Loblolly pine (Pinus taeda) plots located in South Carolina were evaluated using high resolution aircraft multispectral scanner data to determine if biomass could be accurately measured. Sixteen pine plots located on both sandy and clay soils were treated with 0, 180, or 360 kg. (approximately 0, 400, or 800 lb.) of nitrogen per plot. Indices of biomass from remote sensing data were significantly correlated with in situ biomass measurements made in each plot. A ratio of infrared (.9–1.1 μm) and red (.65–.70 μm) channels yielded the best correlation. The indices were not sensitive to differences in soil type (sandy or clay).     

Effect of canopy cover and canopy background variables on spectral profiles of savanna rangeland bush encroachment species based on selected Acacia species (mellifera,tortilis, karroo) and Dichrostachys cinerea at Mokopane,South Africa

The proliferation of woody plant species on savanna rangelands (i.e. bush encroachment) degrades rangeland quality, thereby threatening the biodiversity conservation effort as well as pastoral farming. Hyperspectral remote sensing offers possibilities for discriminating encroaching bush species in support of management of semi-arid savanna rangelands. As a preliminary step towards establishing a spectral library of common encroaching species on savanna rangelands, the effect of canopy leaf cover, background dry soil and grass on the spectral profiles of the common encroaching species Acacia karroo, Acacia mellifera, Acacia tortilis and Dichrostachys cinerea was analysed. A sample of healthy mature plants in prime, full leaf condition was utilised at an encroached rangeland in Mokopane, South Africa. The spectral signatures were collected in-situ, using a field spectrometer pointed above the sample specimen canopies. The canopy and canopy background variables tended to modify the reflectance of the encroaching bush species in the near infrared (800–1300 nm) in which they were spectrally most separable. Canopy background dry grass tended to increase near infrared reflectance, while dry soil tended to reduce the spectral contrast among the species. These effects were reduced by high leaf content. In a thicket canopy structure, the overall reflectance tended towards the spectral profile of the more dominant species.     

腾格里沙漠典型植物含水率与地物光谱的关系分析

地物光谱特征不仅是遥感机理研究的重要内容,亦是遥感应用分析的重要依据。用ASD手持式光谱仪测定了腾格里沙漠10种典型植物的冠层光谱,对测得光谱数据进行包络线去除和一阶微分处理,并在实验室采用烘干法得到植物的含水率,运用相关系数法分析植物含水率与经包络线去除的光谱数据之间的关系,同时分析了不同含水率植物的红边特征。结果表明：研究区植物最大含水率为88.19%,最小含水率为37.34%;含水率与包络线去除的光谱数据在可见光（561~718 nm）和近红外（861 nm,894 nm）波段均存在极显著相关性,并建立了两者之间的回归模型,说明可见光近红外波段可以反映沙漠植物的水分状况;不同含水率植物的红边参数有所差异。