Pedosphere 26(1): 130--136, 2016
ISSN 1002-0160/CN 32-1315/P
©2016 Soil Science Society of China
Published by Elsevier B.V. and Science Press
| Estimation of organic matter content in coastal soil using reflectance spectroscopy |
ZHENG Guang-Hui1
, D. RYU2
 , JIAO Cai-Xia1,2
and HONG Chang-Qiao1
|
1School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044 (China)
2Department of Infrastructure Engineering, University of Melbourne, Parkville 3010 Victoria (Australia) |
| ABSTRACT |
| Rapid determination of soil organic matter (SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. “deviation of arch”(DOA)-based regression and partial least squares regression (PLSR) are two popular modeling approaches to predict SOM. However, few studies have explored the accuracy of the DOA-based regression and PLSR models. Therefore, the DOA-based regression and PLSR were applied to the visible near-infrared (VNIR) spectra to estimate SOM content in the case of various dataset divisions. A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model. Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province, China. The results indicated that both modelling methods provided reasonable estimates of SOM, with PLSR outperforming DOA-based regression in general. However, the performance of PLSR for the validation dataset decreased more noticeably. Among the four DOA-based models, the linear model of the DOA provided the best estimation of SOM and a cutoff of SOM content (19.76 g kg-1), and the performance for calibration and validation datasets was consistent. As the SOM content exceeded 19.76 g kg-1, SOM became more effective in masking the spectral features of other soil properties to a certain extent. This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available. The DOA-based model, which requires only 3 bands in the visible spectra, also provided SOM estimation with acceptable accuracy. |
| Key Words: deviation of arch, multiple regression, partial least squares regression, reflectance spectra, soil organic matter |
| Citation: Zheng, G. H., Ryu, D., Jiao, C. X. and Hong, C. Q. 2016. Estimation of organic matter content in coastal soil using reflectance spectroscopy. Pedosphere. 26(1): 130-136. |
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