不同大气校正方法对森林叶面积指数遥感估算影响的比较

利用TM原始图像以及经过6S模型和基于影像自身的Gilabert模型大气校正后的地面绝对反射率图像,分别计算了褒河流域阔叶林和针阔混交林2种林型的5类光谱植被指数(SR、NDVI、MNDVI、ARVI和RSR),并建立各林型森林叶面积指数与同时相的各个植被指数的相关关系。结果表明,2种大气校正模型均显著提高了各植被指数与森林叶面积指数的相关关系,除了对森林叶面积指数与植被指数SR和NDVI的相关关系影响不显著外,对森林叶面积指数与植被指数MNDVI、ARVI和RSR相关关系的影响均非常显著。说明不同大气校正模型对叶面积指数的遥感估算结果有较大影响。因此,在利用遥感数据进行定量分析、信息提取和生态遥感应用时,不仅要进行大气校正,而且还要慎重选择大气校正模型和植被指数。     

小兴安岭三种林型叶面积指数的估测

利用Winscanopy2006冠层分析仪测定2009年7月初至11月初小兴安岭白桦次生林、谷地云冷杉林、阔叶红松林的有效叶面积指数(LAI_e),并将经过木质部分所占比率、冠层水平集聚和簇内集聚校正的11月初LAI_e作为真实叶面积指数(LAI_t),结合凋落物法测定3种林型的LAI_t及其季节动态.结果表明： 调查期间,白桦次生林的LAI_e在7月达到峰值(2.21),谷地云冷杉林、阔叶红松林的LAI_e在8月达到峰值,分别为2.57、2.68.白桦次生林、谷地云冷杉林、阔叶红松林的LAI_t均在7月达到峰值,分别为3.44、3.86、6.93;相对于本文探讨的方法,光学仪器所测定的LAI_e在最高叶面积指数期分别低估33.1%、32.9%、66.0%;而在整个调查期内,谷地云冷杉林和阔叶红松林LAI_e平均低估22.8%和56.5%,白桦次生林平均高估13.2%.
     

小兴安岭三种林型叶面积指数的估测

利用Winscanopy2006冠层分析仪测定2009年7月初至11月初小兴安岭白桦次生林、谷地云冷杉林、阔叶红松林的有效叶面积指数(LAIe),并将经过木质部分所占比率、冠层水平集聚和簇内集聚校正的11月初LAIe作为真实叶面积指数(LAIt),结合凋落物法测定3种林型的LAIt及其季节动态.结果表明:调查期间,白桦次生林的LAIe在7月达到峰值(2.21),谷地云冷杉林、阔叶红松林的LAIe在8月达到峰值,分别为2.57、2.68.白桦次生林、谷地云冷杉林、阔叶红松林的LAIt均在7月达到峰值,分别为3.44、3.86、6.93;相对于本文探讨的方法,光学仪器所测定的LAIe在最高叶面积指数期分别低估33.1％、32.9％、66.0％;而在整个调查期内,谷地云冷杉林和阔叶红松林LAIe平均低估22.8％和56.5％,白桦次生林平均高估13.2％.     

广西桉树人工林叶面积指数的估测及其校正

叶面积指数(Leaf area index, LAI)是森林生态系统重要的结构参数,通过遥感技术可反演区域LAI,但其可靠性需要地面准确的实测数据进行验证。选取广西国有高峰林场不同林龄的桉树(Eucalyptus robusta)人工林为对象,以异速生长法(Allometry)为对照,综合利用植物冠层分析仪法(LAI-2200)、跟踪辐射和冠层结构分析仪法(TRAC)、半球摄影法(DHP)以及地基激光雷达法(TLS)等间接法估测样地的LAI,并考虑木质成分以及聚集效应影响,进行相应的校正处理,为地面快速、准确测量桉树人工林LAI提供参考。结果表明：桉树人工林的比叶面积为125.37±13.38 cm~2/g,通过Allometry获得的LAI变化范围在1.65—3.84,平均为2.73,不同林龄间的差异均显著(P<0.05),随着林龄的增加呈现先增加后减少的趋势。在未校正情况下,LAI-2200、TRAC、DHP、TLS估算的LAI存在显著差异(P<0.05)。与对照相比,LAI-2200在幼龄林和过熟林中估算误差最小,TRAC在成熟林中估算误差最小。相对于完全去除法,利用...     

湿地松林叶面积指数测算

对湿地松（Pinus elliotii）当年生和多年生两针一束、三针一束叶片的长度、宽度、厚度和重量分别进行量测,据此探讨不同类型叶片的叶形和比叶面积差异,并结合样地调查数据对中科院千烟洲试验站湿地松人工林的叶面积指数进行计算。结果表明：湿地松三针一束叶片合拢后横切面基本呈圆形,当年生叶和多年生叶的平均直径分别为1．688mm和1.706mm;两针一束叶片合拢后从统计学上讲横切面不是圆形,而是椭圆形,叶片厚度方向直径大于宽度方向（当年生叶厚度和宽度方向直径分别为1．580ram和1．422mm,多年生叶分别为1．568mm和1.410mm）,但如果把厚度和宽度方向直径的平均值近似成圆柱体直径计算时误差在3％以内;如果只用厚度或宽度方向直径代表平均直径计算结果会有2％。10％的误差;当年生叶和多年生叶、两针一束叶和三针一束叶之间比叶面积差别很大,计算的三种比叶面积（投影比叶面积、圆柱面比叶面积和比表面积）中,当年生叶的比叶面积明显大于多年生叶,三针一束叶片的投影比叶面积和比表面积都大于两针一束叶片,但圆柱面比叶面积恰好相反。湿地松林的叶面积指数若按投影叶面积算为3．61,按圆柱面的外表面算为5．12,按总表面积的一半算为4．52,比利用冠层分析仪测量的结果略大。     

基于快鸟影像纹理特性的刺槐林叶面积指数估算

以渭北地区刺槐林为研究对象,通过计算高分辨率影像不同窗口的纹理参数,分别运用一元一次方程、一元二次方程、乘幂模型和指数模型,研究刺槐林野外实测叶面积指数（LAI）与快鸟影像纹理参数间的相关关系,遴选黄土高原地区估算刺槐林LAI最适合的纹理参数以及计算窗口大小.结果表明： 纹理指数对LAI反演精度影响显著,其中角二阶矩阵和熵的估算精度明显高于其他纹理指数;计算窗口的大小显著影响LAI反演精度,非相似度和对比度的反演精度在窗口9×9达到最大,其余纹理指数对于LAI的估算精度随着计算窗口的变大不断降低,在窗口3×3时达到最大;乘幂模型的估算精度低于其他3种方法.     

林地叶面积指数遥感估算方法适用分析

叶面积指数是与森林冠层能量和CO2交换密切相关的一个重要植被结构参数,为了探讨估算林地叶面积指数LAI的遥感适用方法和提高精度的途径,利用TRAC仪器测定北京城区森林样地的LAI,从Landsat TM遥感图像计算NDVI、SR、RSR、SAVI植被指数,分别建立估算LAI的单植被指数统计模型、多植被指数组合的改进BP神经网络,获取最有效描述LAI与植被指数非线性关系的方法并应用到TM图像估算北京城区LAI。结果表明,单植被指数非线性统计模型估算LAI的精度高于线性统计模型;多植被指数组合神经网络中,以NDVI、RSR、SAVI组合估算LAI的精度最高,估算值与观测值线性回归方程的R2最高,为0.827,而RMSE最低,为0.189,神经网络解决了多植被指数组合统计模型非线性回归方程的系数较多、较难确定的问题,可较为有效的应用于遥感图像林地LAI的估算。     

大麦叶面积指数的模拟研究

在连续观测和定量分析的基础上,采用单株叶面积最大值作为品种遗传参数,用两段非线性方程构建了大麦叶面积指数随生理发育时间（Physiological development time,PDT）变化的动态模型．模型将经验性和机理性有机结合,考虑了温度和氮素营养对叶片生长的影响,较好的解决了两段非线性方程的衔接问题;不同品种、氮肥处理、播期以及种植地域间检验结果表明,叶面积指数模拟值与观测值的绝对预测误差为0．007-1．486,RMSE为0．109-0．718．     

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。     

叶面积指数的研究和应用进展

对叶面积指数(LAI)提出50多年来,在植物光合作用、蒸腾作用、联系光合和蒸腾的关系和构成生产力基础的研究,在林分、景观以及地区尺度上对碳、能量、水分通量的研究,借助遥感技术建立森林生态系统的生长模型以及研究森林生态系统的能量和水分交换等方面的研究和应用进展进行了综述。LAI作为进行植物群体和群落生长分析的一个重要参数,已在农业、果树业、林业以及生物学、生态学等领域得到广泛应用。     

高光谱植被指数与水稻叶面积指数的定量关系

基于不同水稻品种、施氮水平和不同生育期下的大田试验,确立了水稻叶面积指数（LAI）与冠层光谱特征参数的定量关系.结果表明：水稻叶面积指数与部分高光谱植被指数存在良好的相关性,其中原始光谱组成的2波段差值指数（DI）形式相关性最好,其次为比值（RI）和归一化（NI）植被指数.相关最好的原始光谱植被指数是由近红外波段组成的差值指数DI(854,760),相关最好的一阶导数光谱植被指数是红光和近红外光组成的导数差值指数DI(D₆₇₆, D₇₇₈),但总体上导数光谱指数不如原始光谱指数与LAI关系密切.独立试验数据检验结果表明,以差值指数DI(854,760)为变量建立的水稻LAI监测模型具有较好的表现,可用于水稻LAI的估测.     

Defining leaf area index for non-flat leaves

To eliminate the confusion in the definition of leaf area index (L) for non-flat leaves, the projection coefficients of several objects including spheres, cylinders, hemicircular cylinders, and triangular and square bars are investigated through mathematical derivation and numerical calculation for a range of ellipsoidal angular distributions. It is shown that the projection coefficient calculated based on half the total intercepting area is close to a constant of 0.5 when the inclination angle of the objects is randomly (spherically) distributed, whereas the calculated results based on the object's largest projected area are strongly dependent on the shape of the objects. Therefore, it is suggested that the leaf area index of non-flat leaves be defined as half the total intercepting area per unit ground surface area and that the definition of L based on the projected leaf area be abandoned.     

大麦叶面积指数模拟模型

准确模拟叶面积指数是作物生长模拟模型预测作物生长和产量的关键.本文通过系统分析扬州和武汉地区不同大麦品种高产群体叶面积指数变化动态,建立了大麦群体的叶面积指数模拟模型.大麦叶面积指数是品种叶面积指数扩展的遗传参数和气温日较差、日照时数、辐射量等气候因子及水肥丰缺因子的函数.孕穗抽穗期最大叶面积指数与该期最适叶面积指数是不同的概念,二者之间存在着极显著差异.利用扬州、南京和昆明地区不同品种的播期试验及氮肥试验资料对模型进行了检验,结果表明,模型对大麦叶面积指数的模拟效果较好,模拟值与观测值吻合度高,根均方差RMSE介于0.742～2.865,平均值为1.348.对模拟值与观测值进行y=x的线性回归分析,相关系数R²介于0.511～0.954,均呈极显著正相关.     

利用冠层光谱估测烟草叶面积指数和地上生物量

综合多种烟草类型、品种及肥料处理因素,分析了17种光谱参数与烟草叶面积指数（LAI）、地上鲜生物重（AFW）、地上干生物重（ADW）的关系,建立逐步回归模型对烟草LAI、AFW、ADW进行估测并结合相关分析筛选出相应的特征变量。结果表明：5个回归方程的复确定系数R^2、回归系数相伴概率均达到显著水平。包含17个光谱参量的逐步回归方程筛选出的第一自变量均为Rg／Rr,相关分析及散点图分析亦得出Rg／Rr与LAI、AFW、ADW相关系数分别为0．759、0．611、0．647,R^2为0．576、0．3727、0．4184,均达到极显著水平,证明烟草LAI、AFW、ADW的特征变量为Rg／Rr。仅采用8种植被指数建立模型,证明利用比值植被指数（RVI）估测LAI、ADW亦是可行的。经过统计检验,建立的模型估测效果均较好,估测值与实测值的相关性均达到显著水平,其中包含特征变量Rg／Rr的回归模型估测效果优于RVI构建的模型。表明采用高分辨率光谱或宽波段光谱提取光谱变量可对烟草LAI、AFW、ADW进行监测,并可根据数据条件选择有效的估测模型,为烟草遥感数据分析提供方法。     

Estimation of plant and leaf area index using three techniques in a mature native eucalypt canopy

Abstract Leaf area index (L) is a critical variable in monitoring and modelling forest condition and growth and is therefore important for foresters and environmental scientists to measure routinely and accurately. We compared three different methods for estimating L: a plant canopy analyser (PCA), a point‐quadrat camera method and digital hemispherical photography at a native eucalypt forest canopy at Tumbarumba in southern New South Wales, Australia. All of these methods produced indirect estimates of L based on the close coupling between radiation penetration and canopy structure. The individual L estimates were compared, and the potential advantages and disadvantages of each method were discussed in relation to use in forest inventory and in field data collection programmes for remote sensing calibration and verification. The comparison indicated that all three methods, PCA, digital hemispherical photography and the modified point‐quadrat camera method, produced similar estimates with a standard error between techniques of less than 0.2 L units. All methods, however, provided biased estimates of L and calibration is required to derive true stand L. A key benefit, however, of all of these estimation methods is that observations can be collected in a short period of time (1–2 h of field‐work per plot).     

Simulation of leaf area development based on dry matter partitioning and specific leaf area for cut chrysanthemum

This work aims to predict time courses of leaf area index (LAI) based on dry matter partitioning into the leaves and on specific leaf area of newly formed leaf biomass (SLA(n)) for year-round cut chrysanthemum crops. In five glasshouse experiments, each consisting of several plant densities and planted throughout the year, periodic destructive measurements were conducted to develop empirical models for partitioning and for SLA(n). Dry matter partitioning into leaves, calculated as incremental leaf dry mass divided by incremental shoot dry mass between two destructive harvests, could be described accurately (R(2 )= 0.93) by a Gompertz function of relative time, R(t). R(t) is 0 at planting date, 1 at the start of short-days, and 2 at final harvest. SLA(n), calculated as the slope of a linear regression between periodic measurements of leaf dry mass (LDM) and LAI, showed a significant linear increase with the inverse of the daily incident photosynthetically active radiation (incident PAR, MJ m(-2 )d(-1)), averaged over the whole growing period, the average glasshouse temperature and plant density (R(2 )= 0.74). The models were validated by two independent experiments and with data from three commercial growers, each with four planting dates. Measured shoot dry mass increase, initial LAI and LDM, plant density, daily temperature and incident PAR were input into the model. Dynamics of LDM and LAI were predicted accurately by the model, although in the last part of the cultivation LAI was often overestimated. The slope of the linear regression of simulated against measured LDM varied between 0.95 and 1.09. For LAI this slope varied between 1.01 and 1.12. The models presented in this study are important for the development of a photosynthesis-driven crop growth model for cut chrysanthemum crops.     

利用数字植物冠层图象分析仪测定南亚热带森林叶面积指数的初步报道

介绍了当今较先进的数字植物冠层图象分析仪的理论基础、实际应用的特点 ,测定了南亚热带丘陵地区 8种森林类型 (包括人工林和自然次生林 )的叶面积指数、太阳直射透过系数等群落冠层特征 ,同时测定一由荒坡草地自然发育而成的灌木草坡群落的叶面积指数。根据测定数据比较分析了不同人工林群落 1 1a发展这些特征的变化 ,并与次生自然林的测定数据进行比较 ,同时还对 1 1a与 1 4a树龄马占相思林林冠变化进行比较分析。     

玉米叶面积指数动态模拟的最适野外观测资料

基于锦州农田生态系统野外观测站2005-2011年多个品种的玉米大田试验资料,结合已经建立的玉米叶面积指数动态普适模型,探讨了准确模拟玉米叶面积指数动态所需的最适野外观测资料.结果表明: 准确模拟玉米叶面积指数动态至少需要3年的野外观测数据,且每年在生育期内至少需要进行4次观测.玉米生育期内的理想观测应为在出苗后20 d左右进行第1次观测,此后每月观测1次.
     

Improving the accuracy of indirect methods in estimating leaf area index using three correction schemes in a Larix gmelinii plantation

Aims Woody materials and clumping effects are key error sources in estimating leaf area index (LAI) by optical methods. However, how to correct the error caused by woody materials has not reached consensus. The aims of this study are (1) to evaluate the accuracy of optical methods for estimating effective LAI (L_e) in a deciduous needle leaf forest stand, and (2) to develop a practical correction scheme to improve the accuracy of optical methods in estimating LAI.Methods L_ewas estimated by two indirect methods (i.e., digital hemispherical photography (DHP) and LAI-2000 plant canopy analyzer method (LAI-2000 method) in an annual maximum leaf area period in a Larix gmelinii plantation. Then, we developed three correction schemes to improve the accuracy of indirect methods in estimating LAI. Meanwhile, two direct methods (i.e., litter collection and allometry methods) were used to estimate LAI. Taking LAI from litter collection as a reference, we evaluated the effectiveness of three correction schemes and tested the influence of zenith angle ranges on the correction results.Important findings With zenith angle ranges of 0-45° (rings 1-3), 0-60° (rings 1-4), 45°-60° (ring 4) and 0-75° (rings 1-5), L_eobtained from DHP underestimated LAI from both litter collection and allometry by 19%-32% and 18%-29%, respectively. L_efrom LAI-2000 method with four zenith angles also underestimated LAI from both litter collection and allometry by 9%-30% and 8%-28%, respectively. Although the contribution of woody materials to LAI was overestimated in correction scheme A, it was effective in correcting L_efrom DHP with zenith angles of 45º-60º (ring 4), and also effective for L_efrom LAI-2000 method with zenith angles of rings both 1-3 and 1-4. Correction scheme B was all effective in correcting L_efrom DHP with four zenith angle ranges. Generally, correction scheme C was more effective than other two schemes in correcting L_efrom both DHP and LAI-2000 method with four zenith angle ranges. These results indicate that the zenith angle range is a key factor for determining the accuracy of optical methods in estimating LAI besides woody materials and clumping effects.