Pedosphere 22(3): 351--366, 2012
ISSN 1002-0160/CN 32-1315/P
©2012 Soil Science Society of China
Published by Elsevier B.V. and Science Press
| Visible and near-infrared diffuse reflectance spectroscopy for prediction of soil properties near a copper smelter |
XIE Xian-Li1, PAN Xian-Zhang1 and SUN Bo 2 |
1 Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China)
2 State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China) |
| ABSTRACT |
| Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam-ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared diffuse reflectance spectroscopy (VNIR-DRS) provides a rapid and inexpensive tool to predict various soil properties simultaneously. This study evaluated the suitability of VNIR-DRS for predicting soil properties, including organic matter (OM), pH, and heavy metals (Cu, Pb, Zn, Cd, and Fe), using a total of 254 samples collected in soil profiles near a large copper smelter in China. Partial least square regression (PLSR) with cross-validation was used to relate soil property data to the reflectance spectral data by applying different preprocessing strategies. The performance of VNIR-DRS calibration models was evaluated using the coefficient of determination in cross-validation (Rcv2) and the ratio of standard deviation to the root mean standard error of cross-validation (SD/RMSEcv). The models provided fairly accurate predictions for OM and Fe (Rcv2 > 0.80, SD/RMSEcv > 2.00), less accurate but acceptable for screening purposes for pH, Cu, Pb, and Cd (0.50 lt; Rcv2 < 0.80, 1.40 < SD/RMSEcv < 2.00), and poor accuracy for Zn (Rcv2 < 0.50, SD/RMSEcv < 1.40). Because soil properties in conta-minated areas generally show large variation, a comparative large number of calibrating samples, which are variable enough and uniformly distributed, are necessary to create more accurate and robust VNIR-DRS calibration models. This study indicated that VNIR-DRS technique combined with continuously enriched soil spectral library could be a nondestructive alternative for soil environment monitoring. |
| Key Words: heavy metal, organic matter, partial least squares regression, soil environment monitoring, spectral preprocessing |
| Citation: Xie, X. L., Pan, X. Z. and Sun, B. 2012. Visible and near-infrared diffuse reflectance spectroscopy for prediction of soil properties near a copper smelter. Pedosphere. 22(3): 351-366. |
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