The use of full range spectroradiometer data to assess properties of a heterogeneous soil set in a regional scale survey
The use of full range spectroradiometer data to assess properties of a heterogeneous soil set in a regional scale survey
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使用全范围光谱辐射计数据评估区域规模调查中异质土壤组的特性
DOI：
10.1117/12.2067457
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Thiele-Bruhn S.
中科院分区：
文献类型：
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作者：
Harbich M;Udelhoven T;Jung A;Vohland M;Ludwig M;Thiele-Bruhn S.
土壤性质的光谱评估是一个障碍，光谱预测机制往往不同，从一个人口到另一个。在景观方法中，必须考虑光谱活跃因素的各种组合的异质条件。然而，异质性是光谱数据预测不佳的一个主要原因，因为最佳校准需要有限但足够的集合异质性。在我们的研究中，调查的地块位于一个面积约600平方公里的区域;地质条件和采样土壤类型差异很大。总共从农田的顶层采集了172个土壤样品，然后在实验室中分析了总有机碳（OC）和黑碳（BC），并使用全范围ASD FieldSpec-instrument进行了测量。分析的土壤参数和测量的土壤光谱都反映了样本集的异质性。因此，一个“全球”的校准模型（PLSR）只提供了温和的结果，研究土壤变量。在下文中，我们重点讨论了两个问题，即i）用局部校准程序取代全局校准，以及ii）研究光谱变量选择对校准成功的影响。对于汽车选择程序（“竞争性自适应重加权采样”），结果表明，使用选定的变量，而不是全谱，可以获得更准确的估计。
The spectral assessment of soil properties is handicapped by the fact that spectral predictive mechanisms often vary from one population to another. In a landscape approach, heterogeneous conditions with a wide variety of combinations of spectrally active factors have to be considered. Heterogeneity, however, is one main reason for poor predictions from spectroscopic data, as an optimal calibration needs limited but sufficient set heterogeneity. For our study, the investigated plots were located in an area that covered about 600 km²; geologic conditions and sampled soil types were highly variable. In total, 172 soil samples were taken from the top horizon of agricultural fields, afterwards analysed in the laboratory for total organic carbon (OC) and black carbon (BC) and additionally measured with a full range ASD FieldSpec-instrument. The heterogeneity of the sample set was reflected by both the analysed soil parameters and the measured soil spectra. As a consequence, one “global” calibration model (with PLSR) provided only moderate results for the studied soil variables. In the following we focused on two issues, which were i) to replace the global calibration by local calibration procedures, and ii) to study the effect of spectral variable selection for calibration success. For the CARS selection procedure (“competitive adaptive reweighted sampling”), the results demonstrated that more accurate estimates can be obtained using selected variables instead of the full spectrum.
NIRS 土壤参数量化作为“Chimiométrie 2006”的化学计量学挑战
DOI：
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发表时间：
2008
期刊：
影响因子：
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作者：
J. Pierna;P. Dardenne
通讯作者：
P. Dardenne