Unravelling remote sensing signatures of plants contaminated with gasoline and diesel: An approach using the red edge spectral feature

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Pipeline systems used to transport petroleum products represent a potential source of soil pollution worldwide. The design of new techniques that may improve current monitoring of pipeline leakage is imperative. This paper assesses the remote detection of small leakages of liquid hydrocarbons indirectly, through the analysis of spectral features of contaminated plants. Leaf and canopy spectra of healthy plants were compared to spectra of plants contaminated with diesel and gasoline, at increasing rates of soil contamination. Contamination effects were observed both visually in the field and thorough changes in the spectral reflectance patterns of vegetation. Results indicate that the remote detection of small volumes of gasoline and diesel contaminations is feasible based on the red edge analysis of leaf and canopy spectra of plants. Brachiaria grass ranks as a favourable choice to be used as an indicator of HCs leakages along pipelines. (C) 2012 Elsevier Ltd. All rights reserved.1741627Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Programa Tecnologico de Transportes (PRO-TRAN) in the Centro de Pesquisas e Desenvolvimento (CENPES) of PETROBRASFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Assessing the impact of hydrocarbon leakages on vegetation using reflectance spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)This paper assesses the capability of hyperspectral remote sensing to detect hydrocarbon leakages in pipelines using vegetation status as an indicator of contamination. A field experiment in real scale and in tropical weather was conducted in which Brachiaria brizantha H.S. pasture plants were grown over soils contaminated with small volumes of liquid hydrocarbons (HCs). The contaminations involved volumes of hydrocarbons that ranged between 2 L and 12.7 L of gasoline and diesel per m(3) of soil, which were applied to the crop parcels over the course of 30 days. The leaf and canopy reflectance spectra of contaminated and control plants were acquired within 350-2500 nm wavelengths. The leaf and canopy reflectance spectra were mathematically transformed by means of first derivative (FD) and continuum removal (CR) techniques. Using principal component analysis (PCA), the spectral measurements could be grouped into either two or three contamination groups. Wavelengths in the red edge were found to contain the largest spectral differences between plants at distinct, evolving contamination stages. Wavelengths centred on water absorption bands were also important to differentiating contaminated from healthy plants. The red edge position of contaminated plants, calculated on the basis of FD spectra, shifted substantially to shorter wavelengths with increasing contamination, whereas non-contaminated plants displayed a red shift (in leaf spectra) or small blue shift (in canopy spectra). At leaf scale, contaminated plants were differentiated from healthy plants between 550-750 nm, 1380-1550 nm, 1850-2000 nm and 2006-2196 nm. At canopy scale, differences were substantial between 470-518 nm, 550-750 nm, 910-1081 nm, 1116-1284 nm, 1736-1786 nm, 2006-2196 nm and 2222-2378 nm. The results of this study suggests that remote sensing of B. brizantha H.S. at both leaf and canopy scales can be used as an indicator of gasoline and diesel contaminations for the detection of small leakages in pipelines. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.7885101Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Programa Tecnologico de Transporte (PROTRAN) in the Centro de Pesquisas e Desenvolvimento (CEN-PES) of PetrobrasUNICAMPFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP