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首页> 外文期刊>Geoderma: An International Journal of Soil Science >Estimation of soil organic carbon and total nitrogen in different soil layers using VNIR spectroscopy: Effects of spiking on model applicability
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Estimation of soil organic carbon and total nitrogen in different soil layers using VNIR spectroscopy: Effects of spiking on model applicability

机译:使用VNIR光谱估计不同土层中的土壤有机碳和总氮气的探测:尖峰对模型适用性的影响

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摘要

Soil organic carbon (SOC) and total nitrogen (TN) play major roles in soil quality and the global carbon budget. They can be measured rapidly and cost-effectively via visible and near-infrared reflectance (VNIR) spectroscopy. However, the reliability of this method is questionable because of the effects of heterogeneity. At present, only a few publications have addressed the effect of soil layers on model applicability, especially for highly heterogeneous soils in forest ecosystems. In the current work, we evaluated the performance of VNIR spectroscopy in estimating SOC and TN contents of soils collected from a mixed mountain forest in Central China. We also investigated the applicability of spectroscopic models between soil layers. We then further explored the possibility of using spiking with extra-weighting to improve model applicability. To achieve such objectives, we evaluated the applicability accuracy of the initial models (global and layered models) and modified models (spiked models with and without extra-weighting). Results showed that all the initial models successfully predicted SOC and TN. That is, for SOC, R-p(2) ranged from 0.79 to 0.90, ratio of performance to inter-quartile range (RPIQ) ranged from 3.07 to 3.97, and the root mean square error (RMSEp) ranged from 0.54% to 0.88%; for TN, R-p(2) ranged from 0.66 to 0.86, RPIQ ranged from 2.12 to 3.78, and RMSEP ranged from 0.05% to 0.08%. However, the prediction accuracies were seriously reduced when the model constructed from the top soil layer was used to predict the sub-surface soil properties, and vice versa. In terms of model applicability, our results demonstrated that spiking improved the applicability of the initial calibrations (RMSEp and absolute prediction bias were obviously reduced) and that the accuracy was further improved when the spiking subset was extra-weighted. When the extra-weighting reached a certain level, the accuracies remained stable or slightly reduced. Our results illustrated that spiking alone and spiking with extra-weighing are effective approaches to improve model applicability in the VNIR estimation of SOC and TN between different soil layers in a highly heterogeneous forest. This approach is potentially useful in rapidly quantifying and monitoring soil carbon and nitrogen pools in heterogeneous landscapes. (C) 2017 Elsevier B.V. All rights reserved.
机译:土壤有机碳(SOC)和总氮(TN)在土壤质量和全球碳预算中起主要作用。通过可见和近红外反射率(VNIR)光谱,可以快速且成本有效地测量它们。然而,由于异质性的影响,这种方法的可靠性是可疑的。目前,只有少数出版物已经解决了土壤层对模型适用性的影响,特别是对于森林生态系统中的高度异质土壤。在目前的工作中,我们评估了VNIR光谱在中部混合山地森林中估算的SoC和TN含量的性能。我们还研究了土壤层之间的光谱模型的适用性。然后,我们进一步探索了使用尖刺的可能性,以提高型号适用性。为了实现这样的目标,我们评估了初始模型(全局和分层模型)和修改模型的适用性准确性(具有和无需加权的尖刺式型号)。结果表明,所有初始模型都成功预测了SOC和TN。即,对于SOC,R-P(2)的范围为0.79至0.90,性能与四分位数(RPIQ)的比率范围为3.07至3.97,根均方误差(RMSEP)的范围为0.54%至0.88%;对于TN,R-P(2)范围为0.66至0.86,RPIQ范围为2.12至3.78,RMSEP范围为0.05%至0.08%。然而,当从顶部土层构成的模型预测亚表面土壤性质时,预测精度被严重降低,反之亦然。在模型适用性方面,我们的结果表明,尖峰改善了初始校准的适用性(RMSEP和绝对预测偏差明显降低),并且当尖刺子集重量时,准确性进一步改善。当额外加权达到一定水平时,精度保持稳定或略微减少。我们的结果表明,单独的尖峰和具有超重的尖峰是改善高度异质森林中不同土壤层和TN的SOC和TN的VNIR估计中的模型适用性的有效方法。这种方法潜在可用于在异构景观中快速定量和监测土壤碳和氮气池。 (c)2017 Elsevier B.v.保留所有权利。

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