Journal
GEODERMA
Volume 289, Issue -, Pages 72-81Publisher
ELSEVIER
DOI: 10.1016/j.geoderma.2016.11.024
Keywords
Elastic net; Diffuse reflectance spectroscopy; Landfill; Soil arsenic; Visible near infrared
Categories
Funding
- Department of Science and Technology-Science & Engineering Research Board (DST-SERB) [SR/FTP/ES-52/2013]
- BL Allen Endowment in Pedology at Texas Tech University
Ask authors/readers for more resources
Soil arsenic (As) contamination by anthropogenic and industrial activities is a problem of global concern. This pilot study demonstrates the feasibility of adapting the diffuse reflectance spectroscopy (DRS) approach using the visible near infrared (VisNIR) spectra for detecting soil As pollution. Further, spatial variability of soil As contamination was evaluated combining DRS based predictions and two geostatistical algorithms. The raw reflectance spectra were preprocessed using three spectral transformations for predicting soil As contamination using three multivariate algorithms. Quantitatively, better accuracy was produced by the elastic net-first derivative model (R-2 = 0.97, residual prediction deviation = 632, RPIQ= 733, RMSE = 0.24 mg kg(-1)). The prediction of soil As was dependent on the close association between soil As and spectrally active soil organic matter and Fe-/Al-oxides. Moreover, the As pollution risks hotspots were reasonably identified using ordinary kriging and indicator kriging interpolations based on DRS predicted As values. (C) 2016 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available