Using a mobile real-time soil visible-near infrared sensor for high resolution soil property mapping
Using a mobile real-time soil visible-near infrared sensor for high resolution soil property mapping
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DOI：
10.1016/j.geoderma.2012.09.007
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发表时间：
2013-05-01
期刊：
影响因子：
6.1
通讯作者：
Shibusawa, Sakae
中科院分区：
文献类型：
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作者：
Kodaira, Masakazu;Shibusawa, Sakae
在这项研究中，我们开发了十二种基于可见光和近红外（Vis-NIR：305-1700 nm）土壤反射光谱的光谱模型，以高空间分辨率预测和绘制土壤特性，这对于特定地点的土壤管理和精准农业很有用。我们使用实时土壤传感器（RTSS）和差分全球定位系统（DGPS）进行收集。调查的土壤性质包括水分含量（MC）、土壤有机质（SOM）、pH、电导率（EC）、阳离子交换量（CEC）、总碳（C-t）、铵态氮（N-a）、热水可提取氮（N-h）、硝态氮（N-n）、全氮（N-t）、速效磷（P-a）和吸磷量。 系数（PAC）。试验地点是位于日本北海道的冲积土商业高地。为了开发校准模型，使用 RTSS 中的可见光近红外光谱仪收集了 144 个土壤光谱。偏最小二乘回归（PLSR）与完全（留一）交叉验证相结合，用于建立可见光-近红外土壤反射光谱与土壤特性之间的关系，其值通过土壤化学分析获得。我们显示相关系数、确定系数 (R-2)、均方根误差和残差预测偏差 (RPD)。光谱模型的精度范围为 R-2 0.45 至 0.93，RPD 范围为 1.0 至 3.6。我们的结果与之前的研究进行了比较，其中包括基于现场和实验室的结果。我们通过 MC、SOM、CEC、C-t、N-a、N-n、N-t、P-a 和 PAC 的 RPD 测量的预测准确性与之前的研究中获得的结果相似或更好。 pH、EC 和 N-h 的 RPD 结果仅稍差一些。 (C) 2012 Elsevier B.V. 保留所有权利。
In this study, we developed twelve spectroscopic models based on visible and near-infrared (Vis-NIR: 305-1700 nm) soil reflectance spectra to predict and map at a high spatial resolution soil properties that are useful for site-specific soil management and precision agriculture. We collected using a real-time soil sensor (RTSS) with a differential global positioning system (DGPS). The investigated soil properties were moisture content (MC), soil organic matter (SOM), pH, electrical conductivity (EC), cation exchange capacity (CEC), total carbon (C-t), ammonium nitrogen (N-a), hot water extractable nitrogen (N-h), nitrate nitrogen (N-n), total nitrogen (N-t), available phosphorus (P-a), and phosphorus absorptive coefficient (PAC).The experimental site is a commercial upland field with alluvial soil located in Hokkaido, Japan. To develop the calibration models, 144 soil spectra were collected with the Vis-NIR spectrometer in the RTSS. Partial least squares regression (PLSR) coupled with full (leave-one-out) cross-validation were used to establish the relationships between the Vis-NIR soil reflectance spectra and the soil properties, whose values were obtained by soil chemical analysis. We show the coefficient of correlation, coefficient of determination (R-2), root mean square error and residual prediction deviation (RPD). The accuracy of the spectroscopic models ranged from R-2 0.45 to 0.93 and RPD from 1.0 to 3.6. Our results were compared with previous studies, which include field-based and lab-based results. The accuracy of our predictions as measured by the RPD for MC, SOM, CEC, C-t, N-a, N-n, N-t, P-a, and PAC was similar or better than those obtained in previous studies. RPD results for pH, EC and N-h were only slightly poorer. (C) 2012 Elsevier B.V. All rights reserved.