1. Visible and Near Infrared Spectroscopy of Anthropogenic Soils
Postdok ČZU (ESF and MEYS CZ.1.07/2.3.00/ )
Visible and Near Infrared Spectroscopy of Anthropogenic Soils
on Brown Coal Mining Dumpsites
Asa Gholizadeh, Luboš Borůvka, Mohammadmehdi Saberioon, Radim Vašát, Aleš Klement, Josef Kratina
Introduction
Large-scale open-cast mining of brown coal is a commonly used method of mining in many parts of the world. This mining practice leads to the formation of permanent dumps of sterile rock which are typically heavy with clay, with little or no organic matter content. Even if soils of reclaimed dumpsites can develop a high similarity to natural soils in the close vicinity to mines, after a period of time, some of their properties, even the unfavourable ones can remain unchanged. These soils are at the beginning of their development and have certain specific characteristics, and the specific conditions for this type of soils development can be achieved only after their reclamation. For planning the future exploitation of these soils, for their conservation and the protection of other associated natural resources, it is very important to obtain and process detailed information about soils of mining regions. For the purpose of reclamation, the measurement of soil characteristics of these areas after open-cast brown coal mining is a classical approach to start the landscape restoration. Therefore, fast and accurate prediction of these soil attributes is necessary. Visible-Near Infrared (Vis-NIR) reflectance spectroscopy is a rapid, non-destructive, reproducible and cost-effective analytical method which, due to the relatively simple sample preparation procedures as well as the fast delivery of results, has become very popular in soil science. This study was performed to predict properties of anthropogenic soils in dumpsites using Vis-NIR spectroscopy and various pre-treatment and calibration algorithms and compare the performance of the algorithms for the accurate evaluation of soil condition and selection of suitable reclamation practices.
Objectives
The aim is to make use of Vis-NIR reflectance spectroscopy with different pre-treatment, calibration and validation techniques for the evaluation of reclaimed dumpsite soils.
Results and Discussion
Data Pre-treatment
A visual inspection of the spectra allowed detection of some spectral readings possibly affected by measurement errors. These were removed and the final spectral set had a total of 264 soil spectra. The characteristic wavebands of reflectance spectra were only around 1400, 1900, and 2200 nm. However, there were more features of high variability at around , 1400, and 2200 nm in the first derivative. Generally, the first and second derivatives were by far the best techniques for soil property prediction using the Vis-NIR spectroscopy and the derivatives produced better effects on the enhancement of weak signals than other techniques.
Fig. 3. Raw reflectance spectra and preprocessed spectra of soil samples
Multivariate Analysis Using Calibration Techniques and Validation Test
The modeling strategies considered in this study provided different prediction accuracy of the studied soil parameters.
Table 1: Statistics results for calibration and cross-validation of the Vis-NIR diffuse reflectance spectroscopy for each parameter
Generally, R2cv and RMESPcv for all methods were satisfactory but BT and SVMR results were more reliable which emphasizes the need of using more flexible techniques such as BT and SVMR. The study showed in addition to PLSR and ANN which showed fairly good predictions, BT and SVMR provided more accurate prediction of various soil properties; BT and SVMR’ s superior performance over PLSR can be explained by the inclusion of nonlinear and interaction effects as well as linear combinations of variables, it is able to approximate nonlinear functions between multidimensional spaces.
Materials and Methods
Study Area
The sampling was from six dumpsites which were located in mines Bílina and Tušimice, the Czech Republic.
Fig. 1. Map of the sampling locations in the Czech Republic
Reflectance Spectroscopy Measurement
Reflectance was measured in the nm wavelength range by a FieldSpec 3 spectroradiometer (Analytical Spectral Devices Inc., USA) with a contact probe in laboratory on dry soil samples.
Fig. 2. Reflectance Spectroscopy Measurement using FieldSpec 3
Spectroscopic Pre-treatment, Multivariate Calibration and Validation
Choosing the most robust pre-treatment and calibration technique can help to achieve a more reliable prediction model. Then, the performance of Vis-NIR calibration models was evaluated by minimal Root Mean Square Error (RMSE) and maximal coefficients of determination in cross-validation (R2cv). Moreover, leave-one-out cross-validation mostly gives the best results.
PLSR
ANN
Parameter n R2
RMSEP
R2CV
RMESPCV pH
264
0.67
0.43
0.61
0.51
0.69
0.50 P
0.73
4.4
0.60
5.1
4.3
0.62
5.0 K
4.0
0.58
4.6
4.1
0.57
4.8
Clay
0.75
4.2
0.77
0.68
SVMR BT
Parameter n R2
RMSEP
R2CV
RMESPCV pH
264
0.77
0.38
0.72
0.42
0.83
0.30
0.78 P
0.81
3.8
0.70
4.2
0.87
3.1
0.69 K
3.4
0.68
4.0
0.85
2.9
0.71
3.9
Clay
3.3
0.74
4.3
0.89
3.0
0.80
3.6
Conclusion
This study demonstrated the application of laboratory Vis-NIR reflectance spectroscopy for prediction of some soil properties including pH, P, K and clay, using soil samples taken from six brown coal mining dumpsites of the Czech Republic. For each parameter, Vis-NIR calibration models were created by PLSR, ANN, SVMR and BT algorithms. Moreover, different pre-treatment methods were used. The results showed obvious differences in predictability and accuracy of the different pre-treatment and calibration strategies . Soil spectroscopy in the Vis-NIR region with a SVMR and BT model is shown to be a very promising method for the determination of soil properties in anthropogenic soils. The best predictability of Vis-NIR reflectance spectroscopy was obtained by BT for Clay (R2 > 0.89), followed by P, K and pH. Generally, our results confirmed that Vis-NIR reflectance spectroscopy combined with first derivative and BT and SVMR methods have a great potential for site-specific soil monitoring in high-risk regions and lead to overoptimistic performance in the assessment of soil properties, which otherwise involves conducting large numbers of analyses in a short time.
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