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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Testing the utility of multi-angle spectral data for reducing the effects of background spectral variations in forest reflectance model inversion
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Testing the utility of multi-angle spectral data for reducing the effects of background spectral variations in forest reflectance model inversion

机译:测试多角度光谱数据在减少森林光谱反射模型反演中背景光谱变化的影响方面的效用

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This investigation uses multiple-view-angle spectral data to estimate forest characteristics by inverting a geometric-optical reflectance model. The emphasis of the work was to assess to what extent multi-angle data can be used to help reduce the difficulties in model inversion, caused by variations in the background spectral reflectances. Inversions were tested with both simulated reflectance data and multi-angle Advanced Solid-state Array Spectrometer (ASAS) data. The background reflectances were included in the inversion process, with the assumptions that these are independent of viewing geometry, and the multi-angle data were acquired on a single date, with a constant solar zenith angle. Inversions using multi-angle data gave more accurate retrieval of stand characteristics than inversions using only nadir data; multi-angle data helped to reduce the problem of local minima in the inversion by providing additional information, with uncorrelated samples having the greatest utility. The utility of inversion was dependent on specification of the correct general range of background reflectances as constraints in the inversion process. Evaluation of the effects of errors in both the reflectance data and the ancillary data highlighted some important difficulties encountered in practice. The results indicate that multi-angle data have potential for improving the accuracy of forest characteristics derived by inversion, but further testing seems essential to better understand the limits of the method in practice. (C)Elsevier Science Inc., 2000. [References: 44]
机译:这项研究使用多视角光谱数据通过反转几何光学反射率模型来估算森林特征。这项工作的重点是评估多角度数据可在多大程度上用于帮助减少背景光谱反射率变化所引起的模型反演困难。使用模拟反射率数据和多角度高级固态阵列光谱仪(ASAS)数据测试了反演。假设背景反射率不依赖于观察几何体,并且背景反射率包含在反演过程中,并且多角度数据是在单个日期以恒定的太阳天顶角获取的。与仅使用最低点数据进行的反演相比,使用多角度数据进行的反演能更准确地获得林分特征。多角度数据通过提供附加信息帮助减少反演中的局部极小值问题,其中不相关的样本具有最大的效用。反转的效用取决于正确的背景反射率一般范围的指定,作为反转过程中的约束条件。对反射率数据和辅助数据中误差影响的评估突出了实践中遇到的一些重要困难。结果表明,多角度数据具有提高反演所得森林特征准确性的潜力,但进一步的测试似乎对于更好地了解该方法在实践中的局限性至关重要。 (C)Elsevier Science Inc.,2000年。[参考:44]

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