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Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery

机译:机载高光谱遥感影像中叶绿素含量的反演

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Hyperspectral remote sensing has great potential for accurate retrieval of forest biochemical parameters. In this paper, a hyperspectral remote sensing algorithm is developed to retrieve total leaf chlorophyll content for both open spruce and closed forests, and tested for open forest canopies. Ten black spruce (Picea mariana (Mill.)) stands near Sudbury, Ontario, Canada, were selected as study sites, where extensive field and laboratory measurements were carried out to collect forest structural parameters, needle and forest background optical properties, and needle biophysical parameters and biochemical contents chlorophyll a and b. Airborne hyperspectral remote sensing imagery was acquired, within one week of ground measurements, by the Compact Airborne Spectrographic Imager (CASI) in a hyperspectral mode, with 72 bands and half bandwidth 4.25-4.36 nm in the visible and near-infrared region and a 2 m spatial resolution. The geometrical-optical model 4-Scale and the modified leaf optical model PROSPECT were combined to estimate leaf chlorophyll content from the CASI imagery. Forest canopy reflectance was first estimated with the measured leaf reflectance and transmittance spectra, forest background reflectance, CASI acquisition parameters, and a set of stand parameters as inputs to 4-Scale. The estimated canopy reflectance agrees well with the CASI measured reflectance in the chlorophyll absorption sensitive regions, with discrepancies of 0,06%-1.07% and 0.36%-1.63%, respectively, in the average reflectances of the red and red-edge region. A look-up-table approach was developed to provide the probabilities of viewing the sunlit foliage and background, and to determine a spectral multiple scattering factor as functions of leaf area index, view zenith angle, and solar zenith angle. With the look-up tables, the 4-Scale model was inverted to estimate leaf reflectance spectra from hyperspectral remote sensing imagery. Good agreements were obtained between the inverted and measured leaf reflectance spectra across the visible and near-infrared region, with R-2 =0.89 to R-2 = 0.97 and discrepancies of 0.02%-3.63% and 0.24%-7.88% in the average red and red-edge reflectances, respectively. Leaf chlorophyll content was estimated from the retrieved leaf reflectance spectra using the modified PROSPECT inversion model, with R-2 = 0.47, RMSE =4.34 mu g/cm(2), and jackknifed RMSE of 5.69 mu g/cm(2) for needle chlorophyll content ranging from 24.9 mu g/cm(2) to 37.6 mu g/cm(2). The estimates were also assessed at leaf and canopy scales using chlorophyll spectral indices TCARI/OSAVI and MTCI. An empirical relationship of simple ratio derived from the CASI imagery to the ground-measured leaf area index was developed (R-2=0.88) to map leaf area index. Canopy chlorophyll content per unit ground surface area was then estimated, based on the spatial distributions of leaf chlorophyll content per unit leaf area and the leaf area index. (c) 2008 Elsevier Inc. All rights reserved.
机译:高光谱遥感具有准确检索森林生化参数的巨大潜力。本文提出了一种高光谱遥感算法来检索开放云杉和封闭林的总叶绿素含量,并测试了开放林冠层。选择了加拿大安大略省萨德伯里附近的十个黑云杉(Picea mariana(密西根州))作为研究地点,在这里进行了广泛的野外和实验室测量,以收集森林的结构参数,针叶和森林背景的光学特性以及针叶的生物物理特性。叶绿素a和b的参数和生化含量。紧凑型机载光谱成像仪(CASI)以高光谱模式在地面测量后一周内获取了机载高光谱遥感影像,在可见和近红外区域有72个波段,半带宽为4.25-4.36 nm,2个为2 m空间分辨率。结合几何光学模型4-Scale和改进的叶片光学模型PROSPECT,从CASI图像中估算叶片的叶绿素含量。首先用测得的叶片反射率和透射光谱,森林背景反射率,CASI采集参数以及一组林分参数作为4尺度的输入来估算森林冠层反射率。估算的冠层反射率与CASI在叶绿素吸收敏感区域中测得的反射率非常吻合,红色和红色边缘区域的平均反射率分别分别为0.06%-1.07%和0.36%-1.63%。开发了一种查找表方法来提供查看阳光照射的树叶和背景的可能性,并确定光谱多重散射因子作为叶面积指数,视图天顶角和太阳天顶角的函数。通过查找表,将4比例模型反转,以从高光谱遥感影像估算叶片反射光谱。在可见光和近红外区域的倒置和反射叶片反射光谱之间获得了良好的一致性,R-2 = 0.89至R-2 = 0.97,平均差异为0.02%-3.63%和0.24%-7.88%红色和红色边缘反射率分别。使用改良的PROSPECT反演模型从检索到的叶片反射光谱中估算叶片叶绿素含量,其中R-2 = 0.47,RMSE = 4.34μg / cm(2),顶针的RMSE为5.69μg / cm(2)。叶绿素含量范围从24.9μg / cm(2)到37.6μg / cm(2)。还使用叶绿素光谱指数TCARI / OSAVI和MTCI在叶和冠层尺度上评估了估计值。建立了从CASI图像得出的简单比率与地面测量的叶面积指数的经验关系(R-2 = 0.88)以绘制叶面积指数。然后,根据每单位叶面积的叶绿素含量的空间分布和叶面积指数,估算单位地面表面积的冠层叶绿素含量。 (c)2008 Elsevier Inc.保留所有权利。

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