叶面降尘的高光谱定量遥感模型

利用自主设计的叶面降尘量测定方法,测定了榆树叶面的降尘量数据,结合地面高光谱遥感数据,研究了叶面降尘对榆树叶片高光谱特征的影响及叶面降尘量的高光谱定量反演.研究结果表明,叶面降尘可提高可见光波段的反射率,降低近红外波段的反射率,且对可见光波段的影响要大于近红外波段; 叶面降尘对三边位置没有影响,对三边幅值和面积有明显影响; 利用降尘光谱指数和三边参数建立的叶面降尘量模型,只具备粗略预测能力,而采用多元线性回归、主成分回归、偏最小二乘回归建立的模型,均具有很强的预测能力,其中以一阶微分建立的偏最小二乘回归模型的效果最佳,预测决定系数为0.92,预测均方根误差为1.06,样本标准差与预测均方根误差比为8.2.     

基于室内高光谱激光雷达的典型树种叶片光谱观测和分类

高光谱激光雷达综合了高光谱和激光雷达特征,可为植被生理生化参数提取提供更加精确的遥感探测,但其应用潜力尚未得到充分挖掘。以北京10个典型树种的单叶为样本,开展室内高光谱激光雷达的叶片观测试验,并进行树种分类研究,为未来高光谱激光雷达的林业应用提供基础。首先进行可调谐高光谱激光雷达(Hyperspectral LiDAR,HSL)叶片高光谱测量,并完成与ASD地物光谱仪所测数据对比实验;其次,应用随机森林方法实现10种叶片的分类研究,其输入的特征指数为融合全部波段、部分敏感波段的光谱指数。结果表明:(a)HSL在波段650～1000 nm (71个通道)内观测的叶片高光谱和ASD光谱一致(R~2=0.9525～0.9932,RMSE=0.0587);(b)只用原始波段反射率分类精度为78.31%,其中分类贡献率最大波段的是650～750 nm,使用此波段进行分类精度为94.18%,表明利用红边波段(650～750nm)进行树种分类是十分有效的;(c)对树种敏感的波段为680 nm、685 nm、690 nm、715 nm、720 nm、725 nm、730 nm;(d)结合敏感波段光谱指数与植被指数分类精度82.65%。该研究结果表明在单叶级别,利用高光谱激光雷达能够准确地反映目标叶片的光谱特征并且能有效进行树种分类;未来将可能在野外应用中精确提取目标的生理生化参数。     

用于高光谱图像分类的归一化光谱指数的构建与应用

成像高光谱的近地田间应用为农业定量遥感的发展提供了新的契机。如何发挥其图谱合一的数据优势,尤其在解析土壤、阴影等背景地物对作物养分反演模型的影响需要关注。该研究借助可见/近红外成像高光仪,在近地田间采集小麦群体的成像立方体,根据影像中光照裸土、阴影裸土、光照叶片和阴影叶片的反射光谱特征建立了归一化光谱分类指数,并应用该指数提取大豆影像中不同类型地物的光谱,分析了背景土壤剔除前后的大豆植被归一化光谱与叶绿素密度的决定系数变化情况。结果表明:土壤和阴影叶片光谱去除后,反演叶绿素密度的敏感波段由红-近红外区间（727 nm,922 nm）向蓝、绿,尤其是红波段（710 nm,711 nm）移动。对叶绿素密度敏感的波段区间表现为可见光增加,近红外减少,且红边波段决定系数最高。由此说明,基于归一化光谱指数的植被光谱提纯对定量遥感反演研究具有重要意义。     

利用图谱特征解析和反演作物叶绿素密度

地面成像光谱仪可对作物个体及群体信息进行图谱同步解析,因此在农业定量化研究中具有巨大的应用潜力。利用可见-近红外成像光谱仪采集不同生育期玉米和大豆的冠层图谱数据,在逐步提取影像中光照土壤、阴影土壤、光照植被、阴影植被四种组分光谱的基础上,通过选取的敏感波段构建光谱植被指数和叶绿素密度进行波段自相关分析,探讨各个分量对作物叶绿素密度反演的影响。研究发现:当植被与土壤混合存在时,对叶绿素密度敏感的波段基本在红光与近红外波段;当植被光谱提纯后（剔除土壤光谱）,对叶绿素密度敏感的波段范围增大,表现在蓝、绿波段;当阴影叶片光谱剔除后,对叶绿素密度敏感的波段表现为可见光波段增加,近红外波段减少,红边波段决定系数最高。上述变化特征在不同作物中有相同的趋势,为探索地面成像光谱仪图谱协同反演作物生化参数进行了有意义的探索。     

基于可见光/近红外光谱技术的倒伏水稻识别研究

运用可见光/近红外光谱仪获取正常的和受稻飞虱、穗颈瘟危害而倒伏的水稻冠层光谱反射率,采用主成分分析(PCA)方法对反射率光谱进行降维处理,提取2个主分量光谱.其中,第一主分量PC1代表了水稻冠层的光谱特性,第二主分量PC2反映了倒伏水稻的冠层光谱变化信息.将前2个主分量作为支持向量分类机(SVC)的输入向量,建立分类模型.结果表明,对受稻飞虱危害倒伏的水稻验证数据的识别精度为100%,对受穗颈瘟危害倒伏的水稻验证数据的识别精度为90.9%.研究表明可见光/近红外光谱可能是一种有效的倒伏水稻识别方法.     

基于高光谱数据的叶面积指数遥感反演

文中耦合叶片辐射传输模型（PROSPECT）和冠层辐射传输模型（SAILH）,基于高光谱载荷通道设置,模拟高光谱冠层反射率数据;利用模拟数据深入分析了不同植被指数与叶面积指数之间的敏感性;通过敏感性分析发现改进型叶绿素吸收植被指数（MCARI2）具备抗土壤背景因素的影响能力,而且对叶面积指数较为敏感,因此该研究建立植被指数MCARI2 与叶面积指数之间的经验统计模型,并用于高光谱数据进行叶面积指数反演;最后利用飞行同步测量的叶面积指数对反演模型进行精度分析。结果表明:相比实测叶面积指数,文中建立的反演模型约低估0.42,该反演模型能够较好的反映出地物真实叶面积指数。     

基于可见/近红外光谱技术的黄瓜叶片SPAD值检测

为了快速准确检测黄瓜叶片的SPAD值,采用可见/近红外光谱技术并结合化学计量学方法建立了黄瓜叶片SPAD值校正模型.并用不同建模方法对全波段光谱进行建模,结果表明用最小二乘支持向量机(LSSVM)建模得到的预测效果最好,其相关系数r和预测均方根误差RMSEP分别为0.9583和0.9732.通过分析黄瓜叶片的光谱反射率与SPAD值的相关系数和PLS建模回归系数,得到了531~581nm和696~716nm 2个特征波段以及556nm、581nm、698nm和715nm 4个特征波长,应用LSSVM分别对特征波段和特征波长建模.分析表明,采用特征波段建模,其预测相关系数r和预测均方根误差分别为0.9338和1.1370,与全波段建模结果相近,而采用特征波长建模效果稍差.特征波段建模大大减少了建模中的运算量,提高了建模速度,便于相应检测仪器的开发,所以,采用光谱特征波段建模对黄瓜叶片SPAD值的检测更为有效.     

短波红外垂直失水指数对大气效应的敏感性分析

在业务应用中,用光学遥感方法反演地表土壤水分时常常会因受到大气效应的影响而降低精度。利用中分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer.MODIS)的卫星观测数据、相应的地表反射率产品以及辐射传输模型模拟方法,评估了短波红外垂直失水指数(Shortwave Infrared Perpendicular Water Stress Index,SPSI)对大气效应的敏感性。结果表明,大气效应会使近红外和短波红外波段的反射率呈线性增加,但对由近红外和短波红外波段组成的光谱特征空间中的典型三角形分布以及像元间几何关系影响较小,能够在一定程度上补偿大气效应对土壤水分反演的影响。因此,在实际的区域化应用中,可以不考虑大气效应给SPSI指数计算及土壤水分反演带来的不确定性,从而简化业务流程。     

可见近红外波段碲镉汞材料光学常数测定与宽谱增透设计

将碲镉汞(Hg_(1-x)Cd_xTe)红外焦平面器件衬底去除后,其响应波段可拓展到可见光波段,在高光谱成像应用中可显著减小系统的尺寸和重量,对光电探测系统的小型化和微型化具有重要实用价值.而明确碲镉汞材料在可见近红外波段的光学常数,对碲镉汞器件在这一响应波段的性能研究具有重要意义.分别测量了不同组分碲镉汞材料的椭圆偏振光谱,拟合得到了其在400~1 600 nm波段范围内的光学常数值,并利用反射光谱对获得的光学常数进行了验证.采用这些碲镉汞外延材料光学常数测量值,并选用Zn S和YF3分别作为高低折射率的增透膜材料,针对不同响应波段的背入射可见近红外碲镉汞焦平面器件,设计了不同的宽谱增透膜系,响应波段范围内的平均透过率高于90%.     

基于可见光-近红外新光谱特征和最优组合原理的大麦叶片氮含量监测

提出新的作物冠层叶片氮含量(LNC)高光谱遥感监测方法,以对氮素要求较高的大麦LNC监测为例,利用田间实测数据,从可见光－近红外区域的高光谱反射曲线中提取包含丰富多波段信息的斜率、夹角等新型特征参数,应用组合预测领域中的权重最优组合原理及其算法,实现对作物LNC的高光谱监测.研究表明,提出的高光谱反射曲线斜率和夹角等新型特征参数与作物LNC显著相关,并具有较好的定量响应关系,其中关键斜率参数(Kre/Kpb)和Kpb以及夹角参数(Aδ/Aα)和(Aδ/Aθ)较好地描述了LNC的动态变化; 而权重最优组合分析则表明(Kre/Kpb)和Knir1两个参数的组合最能响应LNC的光谱信息,有助于增强监测的稳定性并提高估测的精度.     

Remote sensing and the optical properties of the narrow cylindrical leaves of juncus roemerianus

To develop a more complete foundation for remote sensing of the marsh grass Juncus roemerianus, we measured the optical properties of its cylindrical leaves at sites of different canopy height, biomass composition and amount, and connectivity to ocean flushing. To measure the leaf optical properties, we adapted a technique used for conifer needles. After establishing the reliability and limits of the adapted technique to the wider J.roemerianus leaves, mean transmittance and reflectance spectra were compared to associated leaf diameters from two dates in 1999 and 2002 and at each site. Transmittance was inversely related to leaf diameter. Mean transmittance and reflectance generated from reoccupation of many field sites in 2002 indicated little or no difference in transmittance between years, a slight reflectance difference in the visible (<2%) and a slightly higher reflectance difference in the near infrared (NIR) (<4%). Site comparison indicated limited ability to separate leaf transmittance but not reflectance by marsh type (e.g., low, medium, high) or biomass. Excluding one outlier, we found leaf transmittances could be adequately represented as 1% /spl plusmn/ 0.2% in the visible and 9% /spl plusmn/ 1% in the NIR and leaf reflectances represented from 14% to 16% in the visible and 71% to 75% in the NIR (the reflectance ranges represent 1999 and 2002 means). Reflectance and transmittance spectra associated with the dead J. roemerianus leaves displayed a spectrally flat increase from the visible to the NIR wavelengths. In total, we documented the atypical optical properties of the cylindrical J. roemerianus leaves and showed that to a first approximation, single means could represent leaf transmittance and visible leaf reflectance across all marsh zones and, after accounting for sample standardization, possibly the NIR reflectance as well.     

长白山牡丹岭典型阔叶树叶变色期高光谱及红边特性研究

以长白山牡丹岭典型阔叶木本植被为研究对象, 通过冠层高光谱和微分光谱数据确定叶变色期, 利用红边参数建立光谱与叶变色期的反演模型.研究结果表明：冠层高光谱反射比曲线可以准确反映植被秋季叶变色期的变化, 并表现为三种基本类型：叶开始变色期——叶全部变色期——干枯但不落叶, 叶开始变色期——部分变黄并开始落叶——未完全变黄但落叶结束, 叶开始变色期——叶全部变色期——落叶; 一阶微分光谱曲线与高光谱曲线线能够更清晰的显示出叶开始变色期和叶完全变色期的具体日期; 建立红边参数—叶变色期的反演模型, R2均在0.9以上, 且不同植被适合不同形式的拟合方程.对利用遥感方法定量监测山地秋季物候具有重要理论意义和广泛应用前景.     

Detection of forests using mid-IR reflectance: an application foraerosol studies

The detection of dark, dense vegetation is an important step in the remote sensing of aerosol loading. Current methods that employ the red (0.64 μm) and the near-IR (0.84 μm) regions are unsatisfactory in that the presence of aerosols in the scene distorts the apparent reflectance in the visible and near-IR ranges of the spectrum. The mid-IR spectral region is also sensitive to vegetation due to the absorption of liquid water in the foliage, but is not sensitive to the presence of most aerosols (except for dust). Therefore, mid-IR channels on the AVHRR and EOS-MODIS (e.g., the 3.75 μm or the 3.95 μm channels) have a unique potential for the remote sensing of dark, dense vegetation, particularly in the presence of biomass burning smoke or industrial/urban haze. The reflective part of the 3.75 μm channel (ρ_3.75) is applied to images of the AVHRR over the eastern United States. This channel was found to be correlated to reflectance at 0.64 μm (ρ_0.64), less sensitive to haze than the visible channel and superior to both the 0.64 μm reflectance and the normalized difference vegetation index (NDVI) to determine forest pixels in an image. However, its application to monitor the seasonal evolution of vegetation is presently questionable. For the purpose of the remote sensing of aerosol over dark, dense vegetation, it is proposed that the dark, dense vegetation be determined from ρ_3.75<0.025. These findings may have further implications for other specific applications of the remote sensing of vegetation in hazy atmospheres     

The role of canopy structure in the spectral variation oftransmission and absorption of solar radiation in vegetation canopies

This paper presents empirical and theoretical analyses of spectral hemispherical reflectances and transmittances of individual leaves and the entire canopy sampled at two sites representative of equatorial rainforests and temperate coniferous forests. The empirical analysis indicates that some simple algebraic combinations of leaf and canopy spectral transmittances and reflectances eliminate their dependencies on wavelength through the specification of two canopy-specific wavelength-independent variables. These variables and leaf optical properties govern the energy conservation in vegetation canopies at any given wavelength of the solar spectrum. The presented theoretical development indicates these canopy-specific wavelength-independent variables characterize the capacity of the canopy to intercept and transmit solar radiation under two extreme situations, namely, when individual leaves 1) are completely absorptive and 2) totally reflect and/or transmit the incident radiation. The interactions of photons with the canopy at red and near-infrared (IR) spectral bands approximate these extreme situations well. One can treat the vegetation canopy as a dynamical system and the canopy spectral interception and transmission as dynamical variables. The system has two independent states: canopies with totally absorbing and totally scattering leaves. Intermediate states are a superposition of these pure states. Such an interpretation provides powerful means to accurately specify changes in canopy structure both from ground-based measurements and remotely sensed data. This concept underlies the operational algorithm of global leaf area index (LAI), and the fraction of photosynthetically active radiation absorbed by vegetation developed for the moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments of the Earth Observing System (EOS) Terra mission     

Analysis of interannual changes in northern vegetation activityobserved in AVHRR data from 1981 to 1994

This paper reports on the analysis of Pathfinder AVHRR land (PAL) data set that spans the period July 1981 to September 1994. The time series of normalized difference vegetation index (NDVI) data for land areas north of 45° N assembled by correcting the PAL data with spectral methods confirms the northerly greening trend and extension of the photosynthetically active growing season. Analysis of the channel reflectance data indicates that the interannual changes in red and near-infrared reflectances are similar to seasonal changes in the spring time period when green leaf area increases and photosynthetic activity ramps up. Model calculations and theoretical analysis of the sensitivity of NDVI to background reflectance variations confirm the hypothesis that warming driven reductions in snow cover extent and earlier onset of greening are responsible for the observed changes in spectral reflectances over vegetated land areas     

WorldView-2影像的湿地典型挺水植物群落含水量估算研究——以北京野鸭湖湿地为例

利用多光谱遥感技术定量估算野鸭湖湿地挺水植物的含水量.基于典型挺水植物的实测冠层光谱及其对应样方的叶片含水量和叶面积指数LAI数据,首先对芦苇和香蒲的地面实测光谱进行重采样,以模拟WorldView-2影像的光谱,然后利用模拟光谱分别构建芦苇和香蒲任意两波段反射率组合而成的比值(SR)和归一化差值植被指数(NDVI),通过分析植被指数与CWC(冠层含水量,Canopy Water Content)的相关关系,选择与CWC显著相关的植被指数,并通过单变量线性与非线性拟合的分析方法确定监测不同挺水植物群落的最佳植被指数,建立估算模型;结合覆盖研究区的WorldView-2高分辨率多光谱影像,对研究区的挺水植物群落CWC进行反演及制图.结果表明,基于模拟WorldView-2影像光谱构建的比值(SR)和归一化差值植被指数(NDVI)与CWC的总体相关性较高;SR(8,3)芦苇为估算CWC芦苇的最优植被指数,估算模型为y=0.005x+0.003,NDVI(8,3)香蒲为估算CWC香蒲的最优植被指数,估算模型为y=2.461x2-0.313x+0.032,通过交叉检验,CWC芦苇和CWC香蒲的预测精度分别为87.42%和82.12%,预测精度较为理想;利用实测数据对反演的CWC空间分布图进行了验证,通过验证,芦苇和香蒲影像估算CWC的均方根差(RMSE)分别为0.0048和0.0052,估算精度分别为83.56%和80.31%,表明利用WorldView-2高分辨率多光谱影像反演湿地挺水植物群落CWC具有较高的可行性.