Pedosphere 29(4): 421--431, 2019
ISSN 1002-0160/CN 32-1315/P
©2019 Soil Science Society of China
Published by Elsevier B.V. and Science Press
| Removing Moisture Effect on Soil Reflectance Properties: A Case Study of Clay Content Prediction |
Yaron OGEN1,3 , Shira FAIGENBAUM-GOLOVIN2, Amihai GRANOT3, Yoel SHKOLNISKY2, Naftaly GOLDSHLEGER4, Eyal BEN-DOR3 |
1The Porter School of Environmental Studies, Tel Aviv University, Tel Aviv 6997801(Israel)
2Department of Applied Mathematics, Tel Aviv University, Tel Aviv 6997801(Israel)
3Remote Sensing Laboratory, Department of Geography and the Human Environment, Tel Aviv University, Tel Aviv 6997801(Israel)
4Department of Civil Engineering, Ariel University, Ariel 407000(Israel) |
| Corresponding Author:Yaron OGEN |
| ABSTRACT |
| Visible, near-infrared and shortwave-infrared (VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares (PLS) and nearest neighbor spectral correction (NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper (SAM) and the average sum of deviations squared (ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R2 of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization (EPO) and direct standardization (DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification, and soil properties assessment. |
| Key Words: dry spectral fingerprint,nearest neighbor spectral correction,partial least squares,reflectance spectra,soil moisture,soil property,spectroscopy,wet soil |
| Citation: Ogen Y, Faigenbaum-Golovin S, Granot A, Shkolnisky Y, Goldshleger N, Ben-Dor E. 2019. Removing moisture effect on soil reflectance properties:A case study of clay content prediction. Pedosphere. 29(4):421-431. |
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