1. Authors: Asa Gholizadeh, Nimrod Carmon, Aleš Klement, Luboš Borůvka, Eyal Ben-Dor, Sabine Chabrillat
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Effects of Measurement Protocols and Data Mining Techniques on Soil Proxy Model Extraction: A Czech Case Study
Soil spectroscopy has shown to be a fast, cost-effective, environmentally-friendly, nondestructive, reproducible, and repeatable analytical technique. Soil components, as well as types of instruments, protocols, sampling methods, sample preparation, spectral acquisition techniques, and analytical algorithms have a combined influence on the final performance. Therefore, it’s important to characterize these differences and to establish a simple common standardization procedure in order to minimize the technical factors that alter reflectance spectra. To quantify this alteration, a joint project between Czech University of Life Sciences (CULS) and Tel-Aviv University (TAU) was conducted to estimate Cox, pH-H2O, pH-KCl, Fe-d, Fe-ox, Mn-d, and Mn-ox. Seventy-eight (78) soil samples from five agricultural lands in different parts of the Czech Republic, two different protocols for soil spectral and chemical measurement, as well as two data mining techniques were examined. The results showed that spectra based on the CULS setup demonstrated significantly higher albedo intensity and reflectance values relative to the TAU setup reflectance. The TAU protocol using Internal Soil Standard (ISS) also improved the analytical results as compared to the CULS (NON-ISS) protocol. Such initiative is not only a way to unlock current limitations of soil spectroscopy, but also helps the soil community in developing an agreed-upon protocol to contribute to the construction of the Soil Spectral Libraries (SSLs).
Abstract
Study Areas and Sampling Points
Geographical position of the study area
CULS Protocol
TAU Protocol
Modelling
(PARACUDA II®)
Modelling
(PLSR)
120 preprocessing sequences using 8 different algorithms
developing of 512 individual models
Raw Spectra
2nd Derivative
1st Derivative
+ ISS
Validation
(k-fold cross-validation)
Validation
(Based on internal
validation 25% technique)
Results
Soil Spectral Reflectance
Comparison of Protocols and Data Mining Techniques
Coefficient of determination (R2) of PLSR and PARACUDA II® performance
for CULS and TAU spectral datasets
The spectra of soil samples as measured by CULS (left) and TAU (right) setups
Conclusions
ISS aligned the TAU protocol to be more stable, and thus the protocol slightly improved the analytical results as compared to the CULS (NON-ISS) protocol.
PARACUDA II® data mining engine provided better performance and proved to be a powerful and reliable tool in achieving the best prediction model.
Adherence to a well-agreed-upon standardization quality, a common protocol, and a reliable data mining technique will enable the reliability and the comparability of results, in order to contribute to the construction of the SSLs in a newly beneficial way.
Ongoing Research Based on GFZ Protocol
Modelling
Different pre-processing: Continuum Removal (CR), 1st and 2nd derivatives
PLSR
Spectral Features
References
Presented at Pedometrics 2017
26 June-1 July 2017, Wageningen, Netherlands