Spectral and growth characteristics of willows and maize in soil contaminated with a layer of crude or refined oil

Raquel Serrano-Calvo (Lead / Corresponding author), Mark E. J. Cutler, Anthony Glyn Bengough

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Abstract

Remote sensing holds great potential for detecting stress in vegetation caused by hydrocarbons but we need to better understand the effects of hydrocarbons on plant growth, and specific spectral expression. Willow (Salix viminalis var. Tora) cuttings and maize (Zea mays var. Lapriora) seedlings were grown in pots of loam soil containing a hydrocarbon-contaminated layer at the base of the pot (crude or refined oil) at concentrations of 0.5, 5, or 50 g ·kg-1. Chlorophyll concentration, biomass and growth of plants were determined through destructive and non-destructive sampling, whilst reflectance measurements were made using portable hyperspectral spectrometers. All biophysical (chlorophyll concentration and growth) variables decreased in the presence of high concentrations of hydrocarbons, but at lower concentrations an increase in growth and chlorophyll were often observed with respect to non-polluted plants, suggesting a biphasic response to hydrocarbon presence. Absorption features were identified that related strongly to pigment concentration and biomass. Variations in absorption feature characteristics (band depth, band area and band width) were dependent upon the hydrocarbon concentration, type, and showed the same biphasic pattern noted in the biophysical measurements. This study demonstrates that the response of plants to hydrocarbon pollution varies according to hydrocarbon concentration and that remote sensing has the potential to both detect and monitor the variable impacts of pollution in the landscape.
Original languageEnglish
Article number3376
Number of pages25
JournalRemote Sensing
Volume13
Issue number17
DOIs
Publication statusPublished - 25 Aug 2021

Keywords

  • Hydrocarbon pollution
  • hyperspectral remote sensing
  • vegetation indices
  • absorption features
  • reflectance spectra
  • plant stress
  • Plant stress
  • Vegetation indices
  • Absorption features
  • Reflectance spectra
  • Hyperspectral remote sensing

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