TY - JOUR
T1 - Removing Moisture Effect on Soil Reflectance Properties
T2 - A Case Study of Clay Content Prediction
AU - FAIGENBAUM-GOLOVIN, Shira
AU - GRANOT, Amihai
AU - SHKOLNISKY, Yoel
AU - GOLDSHLEGER, Naftaly
AU - BEN-DOR, Eyal
N1 - Publisher Copyright: © 2019 Soil Science Society of China
PY - 2019/8
Y1 - 2019/8
N2 - 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.
AB - 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.
KW - dry spectral fingerprint
KW - nearest neighbor spectral correction
KW - partial least squares
KW - reflectance spectra
KW - soil moisture
KW - soil property
KW - spectroscopy
KW - wet soil
UR - http://www.scopus.com/inward/record.url?scp=85069555241&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/S1002-0160(19)60811-8
DO - https://doi.org/10.1016/S1002-0160(19)60811-8
M3 - مقالة
SN - 1002-0160
VL - 29
SP - 421
EP - 431
JO - Pedosphere
JF - Pedosphere
IS - 4
ER -