Hydrocarbon Spectra Slope (HYSS): A Spectra Index for Quantifying and Characterizing Hydrocarbon oil on Different Substrates Using Spectra Data

Authors

  • Kamorudeen Tunde Olagunju University of Lagos
  • Callen Scott Allen Department of Geography, University of Mary Washington, Fredericksburg, VA, USA.
  • Samuel Bamidele Olobaniyi Department of Geosciences, University of Lagos, Lagos, Nigeria
  • Kayode Festus Oyedele Department of Geosciences, University of Lagos, Lagos, Nigeria

DOI:

https://doi.org/10.25299/jgeet.2023.8.2.9741

Keywords:

Hydrocarbon, Oil spill, Hyperspectral, Multispectral

Abstract

Many sensors in Optical domain allow for detection of hydrocarbons in oil spills study. However, high resolution laboratory and airborne imaging spectrometers have shown potential for quantification and characterization of hydrocarbon. Available methods in literature for quantifying and characterizing  hydrocarbons on these data relies mainly on shapes and positions of hydrocarbon key absorption features, mainly at 1.73 µm and 2.30 µm. Shapes formed by these absorption features are often influenced by spectral features of background substrates, thereby limiting the quality of results. Furthermore, multispectral sensors cannot resolve the shapes of key absorption features, a strong limitation for methods used in previous works. In this study, we present Hydrocarbon Spectra Slope (HYSS), a new spectra index that offers predictive quantification and characterization of common hydrocarbon oils. Slope values for the studied hydrocarbon oils enable clear discrimination for relative quantitative analysis of oil abundance classes and qualitative discrimination for common hydrocarbons on common background substrates. Data from ground-based spectrometers and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are resampled to AVIRIS, Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and LANDSAT 7 Enhanced Thematic Mapper’s (ETM+) Full Width at Half Maximum (FWHM), in order to compute spectra slope values for hydrocarbon abundance /hydrocarbon-substrate characterization. Despite limitations of nonconformity of central wavelengths and/or band widths of multispectral sensors to key hydrocarbon band, statistical significance for both quantitative and qualitative analysis at 95% confidence level (P-value ˂0.01) suggests strong potential of the use of HYSS, multispectral and hyperspectral sensors as emergency response tools for hydrocarbon mapping.

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Author Biographies

Callen Scott Allen , Department of Geography, University of Mary Washington, Fredericksburg, VA, USA.

collection of data and major review of the manuscript

Samuel Bamidele Olobaniyi, Department of Geosciences, University of Lagos, Lagos, Nigeria

The first supervisor of the PhD study and reviwer of manucript

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Published

2023-06-28

Issue

Vol. 8 No. 2 (2023): JGEET Vol 08 No 02 : June (2023)

Section

Research Articles

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