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Not AvailableUsing 108 petroleum contaminated soil samples, this pilot study proposed a new analytical approach of combining visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) and portable X-ray fluorescence spectrometry (PXRF) for rapid and improved quantification of soil petroleumcontamination. Results indicated that an advanced fused model where VisNIR DRS spectra-based penalized spline regression (PSR) was used to predict total petroleum hydrocarbon followed by PXRF elemental data-based random forest regression was used to model the PSR residuals, it outperformed (R2 = 0.78, residual prediction deviation (RPD) = 2.19) all other models tested, even producing better generalization than using VisNIR DRS alone (RPD's of 1.64, 1.86, and 1.96 for random forest, penalized spline regression, and partial least squares regression, respectively). Additionally, unsupervised principal component analysis using the PXRF + VisNIR DRS system qualitatively separated contaminated soils from control samples. Capsule: Fusion of PXRF elemental data and VisNIR derivative spectra produced an optimized model for total petroleum hydrocarbon quantification in soils.Not Availabl

Lithologic Discontinuity Assessment in Soils via Portable X-ray Fluorescence Spectrometry and Visible Near-Infrared Diffuse Reflectance Spectroscopy

Lithologic discontinuity identification can be arduous and erroneous in instances where distinct morphological differences between parent materials are absent. Often, investigators must wait for laboratory data to help differentiate parent materials via physicochemical properties. This study used visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) and portable X-ray fluorescence (PXRF) spectrometry for establishing parent material differentia more quickly. Ten pedons containing 135 samples were scanned in situ in the United States, Italy, and Hungary, morphologically described by trained pedologists, then sampled for standard laboratory characterization. Compared with laboratory data and/or morphologically described discontinuities, PXRF data were associated with large, abrupt changes in standardized PXRF differences of elements (DEs), noted in data plots as DE maxima and minima—areas of likely discontinuity. Standardized VisNIR DRS calculated differences (CDs) in reflectance spectra (350–2500 nm) were also associated with discontinuities based on CD reflectance maxima and minima. Notably within both types of data plots, lithologic discontinuities were not well captured by the proximal sensors when CD or DE values fell in the data plot midsection (i.e., not at maxima or minima within the data plots). Across the pedons evaluated, PXRF was more useful for detecting discontinuities than VisNIR DRS. Summarily, PXRF showed good alignment with morphologically established discontinuities in eight out of 10 pedons, while VisNIR DRS showed good alignment in only five pedons. Both PXRF and VisNIR DRS provided useful information for lithologic discontinuity recognition, especially in soils with nondescript morphology

Review of soil salinity assessment for agriculture across multiple scales using proximal and/or remote sensors

Mapping and monitoring soil spatial variability is particularly problematic for temporally and spatially dynamic properties such as soil salinity. The tools necessary to address this classic problem only reached maturity within the past 2 decades to enable field- to regional-scale salinity assessment of the root zone, including GPS, GIS, geophysical techniques involving proximal and remote sensors, and a greater understanding of apparent soil electrical conductivity (ECa) and multi- and hyperspectral imagery. The concurrent development and application of these tools have made it possible to map soil salinity across multiple scales, which back in the 1980s was prohibitively expensive and impractical even at field scale. The combination of ECa-directed soil sampling and remote imagery has played a key role in mapping and monitoring soil salinity at large spatial extents with accuracy sufficient for applications ranging from field-scale site-specific management to statewide water allocation management to control salinity within irrigation districts. The objective of this paper is: (i) to present a review of the geophysical and remote imagery techniques used to assess soil salinity variability within the root zone from field to regional scales; (ii) to elucidate gaps in our knowledge and understanding of mapping soil salinity; and (iii) to synthesize existing knowledge to give new insight into the direction soil salinity mapping is heading to benefit policy makers, land resource managers, producers, agriculture consultants, extension specialists, and resource conservation field staff. The review covers the need and justification for mapping and monitoring salinity, basic concepts of soil salinity and its measurement, past geophysical and remote imagery research critical to salinity assessment, current approaches for mapping salinity at different scales, milestones in multi-scale salinity assessment, and future direction of field- to regional-scale salinity assessment