基于辐射传输模型的高光谱植被指数与叶绿素浓度及叶面积指数的线性关系改进

高光谱植被指数以其特有的精细光谱特征, 能够获得非常细微的植被生理状况和环境胁迫差异, 因而使遥感技术在精细农业中的应用, 尤其是在叶绿素浓度和叶面积指数的反演上面有着广阔的应用前景。然而, 现有的植被指数往往和这2个参数呈非线性关系, 且只对某一区间的数值敏感, 无法适用于其它植被覆盖程度的研究。为了寻找合适的波段位置以改善植被指数与叶绿素浓度和叶面积指数的线性关系, 去除饱和区域, 进而提高这2个参数的实际估算精度, 该文选取了叶绿素浓度和叶面积指数, 以辐射传输模型PROSPECT和SAIL为基础, 模拟了这2个参数变化对3类高光谱植被指数(归一化植被指数(NDVI)、 优化的简单比值指数(MSR)和优化的叶绿素吸收率指数(MCARI))的影响。叶绿素浓度变化敏感性分析结果表明, 对这3类植被指数而言, 750 nm 和705 nm 的叶片反射率更适合实际的叶绿素浓度反演。以750 nm 和705 nm代替 800 nm/700 nm 和670 nm成功地提高了3类植被指数与叶绿素浓度的线性相关程度, 其中MCARI705 和叶绿素浓度基本呈线性关系。叶面积指数变化敏感性分析同样显示, 以750 nm 和705 nm 组成的植被指数能够获取更可靠的叶面积指数信息, 尤其对于高植被覆盖区域。其中MCARI705 能较好地降低随叶面积指数变化的饱和程度, 相比其它植被指数, 当叶面积指数大于8时, MCARI705 才出现明显的饱和。由于冠层的尺度效应, 波段位置的选择对植被指数与叶面积指数线性关系的改善不及对叶绿素浓度明显。     

黄土高原春小麦叶面积指数与高光谱植被指数相关分析

通过田间小区试验,测定了4个春小麦品种（定西24号、陇春8139、高原602和定西38号）在不同生育期和不同种植密度下的光谱反射率及对应的叶面积指数（LAI）。综合分析比较了9个常见植被指数与春小麦LAI的相关性及预测性。结果表明：在4个不同的生育阶段,这9个植被指数与对应的LAI都有很好的相关性以及对LAI有很好预测性。其中以抽穗-开花期植被指数的表现为最好;全生育期这9个植被指数与春小麦LAI的相关性更高,对LAI的预测性更佳,并且大于任何一个生育阶段;其中以近红外与绿光波段的比值R810／R560的预测力最好,故选取R810／R560（x）作为预测全生育期春小麦LAI（y）的最佳植被指数,建立最优模型Y=0．1769x^1.5261,并采用不同品种和不同种植密度的数据对模型进行了精度分析,结果表明,模拟值和实测值之间的R^2平均为0．9280,估算的RMSE平均为0．0762,准确度平均为0．9068,说明此模型具有较好的可靠性和适用性。     

光谱植被指数与水稻叶面积指数相关性的研究

 综合分析比较了几种常见光谱植被指数与水稻（Oryza sativa）叶面积指数的相关性及其预测力。结果表明,植被指数的预测力在水稻营养生长旺盛期间最好。植被指数的预测力主要依赖于叶面积指数(LAI)的整体变化范围。因此,综合不同生育时期和氮肥处理的试验资料,光谱植被指数能准确地预测LAI的变化。LAI与各植被指数均呈曲线相关,与比值植被指数(RVI)、再归一化植被指数(RDVI)和R810/R560显著幂相关,与归一化植被指数(NDVI)、垂直植被指数(PVI)、差值植被指数(DVI)、土壤调整植被指数(SAVI)和转换型土壤调整指数(TSAVI)显著指数相关。其中,近红外与绿光波段的比值R810/R560的预测力最佳。用不同移栽秧龄、不同密度、不同水分和氮肥处理的数据对R810/R560的表现进行了检验,结果表明估算精度平均为91.22%,估计的均方差根(RMSE)平均为0.480　5,平均相对误差为-0.013。表明宽波段光谱植被指数可以准确地用来监测水稻叶面积指数。     

夏玉米叶片全氮、叶绿素及叶面积指数的光谱响应研究

在夏玉米的不同生长阶段,测定冠层光谱,结合农学参数(LTN、CHL．C、CHL．D、LAI),研究了农学参数的光谱响应规律及其与冠层光谱参量(反射率R、一阶微分光谱R′和红边位置REP)的相关性,并建立预测数学模型,结果表明,拔节一抽雄期,伴随着植株生长和群体壮大,红边斜率缓慢增加,红边位置呈逐渐偏向长波方向的“红移”,至抽雄期群体稳定后而停止;开花-乳熟期,随着个体衰老和群体减弱,红边斜率减小,红边位置又呈偏向短波方向的“蓝移”。利用一阶微分光谱和红边位置推算夏玉米冠层CHL．D不仅是可行的,而且反演精度较高,最适模型分别为指数(R^2=0．9487)和抛物线(R^2=0．9392)。     

华南地区亚热带树木叶面积指数的高光谱反演研究

为构建树种叶面积指数的估算模型,以NDVI、RVI、FREP、CIGreen、CIRed-edge、MSAVI2为高光谱特征变量,通过统计分析,确定反演树种叶面积指数的最佳光谱特征变量,构建华南农业大学校园内50种亚热带树木的叶片反射率和叶面积指数(LAI)模型。结果表明,6种高光谱特征变量与树种叶面积指数间都具有极显著相关性,其中红边位置反射率(FREP)和比值植被指数(RVI)与LAI的拟合方程的R2都大于0.8,决定系数分别为0.820和0.811。经过精度验证,FREP估算的均方根误差(RMSE)只有0.13,该回归模型为估测亚热带典型树种的叶片LAI最佳模型。从高光谱遥感的角度结合亚热带植被的群落结构特点来看,建立的红边位置光谱反射率与叶面积指数的回归模型普遍具有较高的拟合度,所以利用高光谱特征变量反演亚热带树木叶片的叶面积指数等植被参数的应用前景较好。     

基于辐射传输模型的叶绿素含量定量反演

利用基于叶片内部辐射传输机制的PROSPECT模型模拟大量不同生化含量和叶肉结构的叶片光谱,研究利用高光谱植被指数定量反演叶绿素含量的可行性和精度,并比较各指数的稳定性和抗干扰能力。结果显示,各指数在对叶绿素的敏感性方面相差不大,除三角植被指数(TVI)外,其它指数均随叶绿素含量的增加而减小。叶片水分含量的差异对各指数的影响很小,干物质次之,叶肉结构影响最大。在抵抗干物质影响和叶肉结构影响方面,结构无关色素指数(SIPI)明显优于其它四种指数,吸收中心波深归一化后的面积指数(ABNC)次之。通过使用叶片光学模型的模拟光谱来研究叶绿素含量变化的光谱响应及其影响因素和反演策略,具有较强的理论性和普适性。研究结果与实际观测相吻合,方法简单易行。     

烟草叶面积指数的高光谱估算模型

叶面积指数(1eaf area index,LAI)是重要的生物物理参数,亦是各种生态模型、生产力模型以及碳循环研究等的重要生物物理参量,因此具有重要的研究意义。为了探索不同高光谱模型监测烟草叶面积指数LAI的精度,在烟草伸根期,旺长期和成熟期采用ASD Fieldspec HH光谱仪测定了不同水氮条件下烟草冠层的高光谱反射率和叶面积指数数据。选用四个常用的植被指数RVI (ratio vegetation index)、NDVI (normalized difference vegetation index)、MTVI2（Modified second triangular vegetation index）、MSAVI（Modified Soil-adjusted vegetation index）和PCA (principal component analysis)、neural network (NN)三种方法对烟草LAI进行了估算,比较分析了三种方法的估算结果。研究结果表明,植被指数法,主成分分析,神经网络方法LAI都取得了较为理想的结果,其中植被指数法可以较为精确反演烟草LAI,验证模型确定性系数在0.76～0.85之间,主成分分析方法和神经网络方法精度较高,分别为0.938和0.889。主成分分析方法验证模型的稳定性更好,其验证模型的RMSE为0.172,低于四个植被指数和神经网络。MTVI2和MSAVI能较好地去除土壤、大气等条件影响,反演精度高于RVI和NDVI。与基于植被指数建立的模型相比,主成分分析和神经网络可以更好的提高LAI的反演精度。     

基于小波分析的大豆叶面积高光谱反演

实测了不同水肥耦合、经营制度及有效营养面积条件下的大豆(Glycinemax)冠层高光谱反射率与叶面积指数(LAI),并对光谱反射率、微分光谱与LAI的关系进行了分析;采用比值植被指数(RVI)与归一化植被指数(NDVI)建立了大豆LAI反演模型;采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LAI进行估算。结果表明:大豆LAI与光谱反射率在可见光波段呈负相关;在近红外波段呈正相关;微分光谱在红边处与大豆LAI密切相关(R2=0.92);RVI与NDVI可以提高大豆LAI的估算精度(R2分别达0.79、0.84);各植被指数各有优缺点,应根据需要进行选择;小波能量系数回归模型可以进一步提高大豆叶面积的估算水平,以一个特定小波能量系数作为自变量的回归模型,大豆LAI回归确定系数R2高达0.884;以4个和6个小波能量系数建立LAI回归分析模型(R2分别达0.92、0.93),2个模型LAI预测值与大豆LAI实测值线性回归确定性系数R2分别为0.90、0.92。比较可知,小波分析可以对高光谱进行特征变量提取,进而反演大豆生理参数,并且反演的LAI精度较光谱反射率、微分光谱及植被指数都有明显提高,小波分析在植被生理参数的高光谱提取方面有着广阔的应用前景。     

基于神经网络的马尾松叶绿素含量高光谱估算模型

分析不同生长期的马尾松冠层反射光谱特征与相应叶绿素含量的相关关系.利用36个红边参数逐一筛选,最终确定7个与叶绿素含量相关性较高的红边参数作为光谱特征参数,分别应用逐步分析法与BP神经网络构建叶绿素含量的高光谱估算模型;同样,筛选出4个植被指数作为光谱特征参数,同时,将对原始光谱进行主成分分析降维后的前4个主成分作为BP神经网络的输入变量,分别应用逐步分析法与BP神经网络构建叶绿素含量的高光谱估算模型.结果表明: 将红边参数作为输入变量建立的逐步回归模型和BP神经网络模型的决定系数(R²)分别为0.5205、0.7253,均方根误差(RMSE)分别为0.1004、0.0848,相对误差分别为6.3%、5.7%.将植被指数作为输入变量建立的逐步回归模型和BP神经网络模型的R²分别为0.5392、0.7064,RMSE分别为0.0978、0.0871,相对误差分别为6.2%、6.0%.基于主成分分析的BP神经网络模型的预测效果最好,R²为0.7475,RMSE为0.0540,相对误差为4.8%.     

基于高光谱遥感的小麦叶干重和叶面积指数监测

生物量和叶面积指数(LAI)是描述作物长势的重要参数, 叶干重和LAI的实时动态监测对小麦(Triticum aestivum)生长诊断和管理调控具有重要意义。为分析多种高光谱参数估算小麦叶干重和LAI的效果, 建立小麦叶干重和LAI的定量监测模型, 该研究连续3年采用不同小麦品种进行不同施氮水平的大田试验, 于小麦不同生育期采集田间冠层高光谱数据并测定叶片叶干重和LAI。试验结果显示, 小麦叶干重和LAI随施氮水平的提高而增加, 随生育进程呈单峰动态变化模式。小麦叶干重和LAI与光谱反射率间相关性较好的区域主要位于红光波段(590~710 nm, r<-0.60)和近红外波段(745~1 130 nm, r>0.69)。对于不同试验条件下的叶干重和LAI, 可以使用统一的光谱参数进行定量反演, 其中基于RVI (810, 560)、FD755、GM1、SARVI (MSS)和TC3等光谱参数的方程拟合效果较好。经不同年际独立试验数据的检验表明, 以参数RVI (810, 560)、GM1、SARVI (MSS)、PSSRb、(R_750-800/R_695-740) -1、VOG2和MSR705为变量建立的叶干重和LAI监测模型均给出较好的检验结果。因此, 利用关键特征光谱参数可以有效地评价小麦叶片生长状况, 尤其是光谱参数RVI (810, 560)、GM1和SARVI (MSS)可以对不同条件下小麦叶干重和LAI进行准确可靠的监测。     

Effects of Season and Successional Stage on Leaf Area Index and Spectral Vegetation Indices in Three Mesoamerican Tropical Dry Forests1

We compared plant area index (PAI) and canopy openness for different successional stages in three tropical dry forest sites: Chamela, Mexico; Santa Rosa, Costa Rica; and Palo Verde, Costa Rica, in the wet and dry seasons. We also compared leaf area index (LAI) for the Costa Rican sites during the wet and dry seasons. In addition, we examined differences in canopy structure to ascertain the most influential factors on PAI/LAI. Subsequently, we explored relationships between spectral vegetation indices derived from Landsat 7 ETM+ satellite imagery and PAI/LAI to create maps of PAI/LAI for the wet season for the three sites. Specific forest structure characteristics with the greatest influence on PAI/LAI varied among the sites and were linked to climatic differences. The differences in PAI/LAI and canopy openness among the sites were explained by both the past land‐use history and forest management practices. For all sites, the best‐fit regression model between the spectral vegetation indices and PAI/LAI was a Lorentzian Cumulative Function. Overall, this study aimed to further research linkages between PAI/LAI and remotely sensed data while exploring unique challenges posed by this ecosystem.     

黄甜竹笋用林的生物量、叶面积指数和叶绿素含量

黄甜竹笋用林生物量高达30375 kg/ha,地上和地下部分的比值变幅在1.2~1.5之间;杆的生物量最大,约为枝和叶的两倍;各器官含水量随年龄增加而减少;叶面积指数与其胸径、竹高、枝下高、冠幅相关,与植株年龄呈现抛物线关系;叶绿素含量除1年生外,随年龄增加而减少,且与叶片接受光照的程度有关,即接受光照越充分,叶绿素含量越高,但由于这些叶片生长较旺盛,衰老亦快,其叶绿素含量最终亦下降。     

The Relationship between the critical Leaf Area, Total Chlorophyll Content, and Maximum Growth-rate of some Pasture and Crop Planst

The amounts of leaf and of chlorophyll per unit area of landexposed to light above 400–500 f.c. on sunny days at localnoon were determined for pure stands of red clover, white clover,perennial ryegrass, short-rotation ryegrass, maize, kale, cocksfoot,and watercress, growing under near-optimum conditions. The valuesobtained for the grass species and maize were significantlyhigher than those of the dicotyledon species There was a highly significant correlation (r = + 0?912) betweenthe maximum growth-rates¹ of the different species and the amountsof chlorophyll above the measurement level per unit area ofland. However, the index was higher for species in which the leaves were disposed horizontally or whereflagging occurred (clovers, kale, and maize) than for the grassspecies, suggesting either that the chlorophyll of the firstgroup of species was more active or efficient in photosynthesisthan the chlorophyll in the species with erect leaves, or thata greater proportion of dry matter produced was accumulatedin underground organs of these erect-leaved species. Growth-ratedata were not available for cocksfoot or watercress. There was a significant correlation (r = + 0?815) between theleaf-area index absorbing 95 per cent. of the light and themaximum growth-rates of the different species, but this relationshipdid not take account of the photosynthetic activity of otherparts of the plant or of species differences in chlorophyllcontent. The results are discussed in relation to the availability andutilization of light energy and carbon dioxide by the speciesexamined.     

A Generic Equation for Nitrogen-limited Leaf Area Index and its Application in Crop Growth Models for Predicting Leaf Senescence

Appropriate quantification of leaf area index (LAI) is importantfor accurate prediction of photosynthetic productivity by cropgrowth models. Estimation of LAI requires accurate modellingof leaf senescence. Many models use empirical turnover coefficients,the relative leaf-death rate determined from frequent fieldsamplings, to describe senescence during growth. In this paper,we first derive a generic equation for nitrogen-determined photosyntheticallyactive LAI (LAI_N), and then describe a method of using thisequation in crop growth models to predict leaf senescence. Basedon the theory that leaf-nitrogen at different horizons of acanopy declines exponentially, LAI_N, which is counted from thetop of the canopy to the depth at which leaf-nitrogen equalsthe minimum value for leaf photosynthesis, is calculated analyticallyas a function of canopy leaf-nitrogen content. At each time-stepof crop growth modelling, LAI_Nis compared to an independentcalculation of the non-nitrogen-limited LAI assuming no leafdeath during that time-step (LAI_NLD). In early stages, LAI_Nishigher than LAI_NLD; but with the advancement of crop growth,LAI_Nwill become smaller than LAI_NLD. The difference betweenLAI_NLDand LAI_N, whenever LAI_Nis smaller than LAI_NLD, gives theestimate of leaf area senesced at the time-step; the senescedleaf area divided by specific leaf area (SLA) gives the estimateof senesced leaf mass. The method was incorporated into twocrop models and the models adequately accounted for the LAIobserved in field experiments for rice and barley. The novelfeatures of the approach are that: (1) it suggests a coherent,biologically reasonable picture of leaf senescence based onthe link with photosynthesis and leaf nitrogen content; (2)it avoids the use of empirical leaf-turnover coefficients; (3)it avoids over-sensitivity of LAI prediction to SLA; and (4)it is presumably of sufficient generality as to be applicableto plant types other than crops. The method can be applied tomodels where leaf-nitrogen is used as an input variable or issimulated explicitly. Copyright 2000 Annals of Botany Company Leaf area index, leaf senescence, canopy nitrogen, modelling     

Simulation Models of Leaf Area Index and Yield for Cotton Grown with Different Soil Conditioners

Simulation models of leaf area index (LAI) and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modified Gaussian, log normal, and cubic polynomial models. Universal models for simulating the relative leaf area index (RLAI) were established in which the application rate of soil conditioner was used to estimate the maximum LAI (LAI_m). In addition, the relationships between LAI_m and dry matter mass, yield, and the harvest index were investigated, and a simulation model for yield is proposed. A feasibility analysis of the models indicated that the cubic polynomial and Gaussian models were less accurate than the other three models for simulating increases in RLAI. Despite significant differences in LAIs under the type and amount of soil conditioner applied, LAI_m could be described by aboveground dry matter using Michaelis-Menten kinetics. Moreover, the simulation model for cotton yield based on LAI_m and the harvest index presented in this work provided important theoretical insights for improving water use efficiency in cotton cultivation and for identifying optimal application rates of soil conditioners.     

Growth Rate, Photosynthesis and Respiration in Relation to Leaf Area Index

This work examined three possible explanations of growth rateresponses to leaf area index (LAI) in which growth rate perunit of ground area (crop growth rate, CGR) increased to a plateaurather than decreasing above an optimum LAI at which all lightwas intercepted. Single leaf photosynthetic measurements, andwhole plant 24 h photosynthesis and respiration measurementswere made for isolated plants and plants in stands using Amaranlhushybridus, Chenopodium album, and two cultivars of Glycine maxgrown at 500 and 1000 µimol m^–2 S^–1 photosyntheticphoton flux density at 25 °C. CGR, relative growth rate(RGR), and LAI were determined from 24 h carbon dioxide exchangeand leaf area and biomass measurements. Respiration increasedrelative to photosynthesis with crowding in A. hybridus andthere was an optimum LAI for CGR. In contrast, the ratio ofrespiration to photosynthesis was constant across plant arrangementin the other species and they had a plateau response of CGRto LAI. Neither increased leaf photosynthetic capacity at highLAI nor a large change in biomass compared to the change inLAI could account for the plateau responses. It was calculatedthat maintenance respiration per unit of biomass decreased withdecreasing RGR in C. album and G. max, but not A. hybridus,and accounted for the plateau response of CGR to LAI. Sincesimilar decreases in maintenance respiration per biomass atlow RGR have been reported for several other species, a constantratio of respiration to photosynthesis may occur in more speciesthan constant maintenance respiration per unit of biomass. Amaranlhus hybridus L., Chenopodium album L., Glycine max L Merr, soybean, photosynthesis, respiration, growth, leaf area index     

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。     

不同海拔对七子花叶片色素含量、含水量及比叶面积的影响

通过比较浙江大盘山不同海拔(A1:550~660 m,A2:700~800 m,A3:900~990 m,A4:1 000~1 015 m,A5:1 020~1 100 m)七子花(Heptacodium miconioides)叶片色素含量、含水量及比叶面积变化,探讨不同海拔对七子花生长的影响。结果表明,随着海拔的升高,叶绿素含量(包括叶绿素a、叶绿素b、叶绿素a+b)先增加后减少,在A3达最高值;叶绿素a/b比值、类胡萝卜素含量变化呈先低后高,在A3降至最低;比叶面积及叶片含水量,在较高海拔A4、A5都明显下降。七子花通过叶片色素、比叶面积、干重和含水量的变化以适应高海拔环境。