This study investigated the use of reflectance and imaging spectroscopy to indirectly detect liquid hydrocarbon leakages in soil-vegetation systems contaminated by gasoline and diesel. A greenhouse experiment and field study measured the spectral responses of leaves and canopies of different plant species exposed to hydrocarbon contamination. The greenhouse experiment found that gasoline caused more prominent morphological and spectral alterations than diesel in the plants. Analysis of hyperspectral imagery from the field study identified spectral indices and principal components that differentiated between contaminated and control plots. The results support the potential of spectroscopy to detect small hydrocarbon spills and identify more susceptible crop species for pipeline monitoring.

1. LAPIG INDIRECT DETECTION OF LIQUID HYDROCARBON LEAKAGES ON CONTAMINED SOIL-VEGETATION SYSTEMS THROUGH REFLECTANCE AND IMAGING (PROSPECTIR-VS) SPECTROSCOPY: A POTENTIAL TOOL FOR EXTENSIVE PIPELINE MONITORING Carlos Roberto Souza Filho1, Lucíola Magalhães1; Giuliana Quitério1 Marcos Nopper1 , Teodoro Almeida2 ; Wilson Olveira3; Lis Rabaco3; Renato Rocha3 University of Campinas, Campinas, Brazil 1 University of São Paulo, São Paulo, Brazil2 Petrobras S.A./CENPES, Rio de Janeiro, Brazil3

3. Assuming that liquid fuels (gasoline and diesel) are potential vegetation stressors, this study investigates the spectral characteristics of agricultural crops subjected to daily contamination of liquid hydrocarbons, using reflectance spectroscopy (portable FieldSpec Hi-Res sensor, with 2150 bands in the VNIR-SWIR range) and imaging spectroscopy (airborne ProSpecTIR-VS hyperspectral sensor, with 357 bands in the VNIR-SWIR range).

6. THE EXPERIMENTLysimeters

7. THE EXPERIMENTLysimeters

8. THE EXPERIMENTLysimeters

10. Leakage – begininning with plantation

11. Periodical spectral measuments

12. Peridiocal leakages

13. Controlled irrigation

14. Samples collected for biochemical analysis by the end of the experimentMeasument Time-days Vol-HC-ml SWHC* *Soil Water Holding Capacity

16. Leakage – begininning 30 days after plantation

17. Periodical spectral measuments

18. Peridiocal leakages (once per 15 days)

19. Controlled irrigation (automatically)

20. Samples collected for biochemical analysis by the end of the experimentMeasument Time-days Vol-HC-ml SWHC*

21. THE EXPERIMENTMacro (real) scale

22. THE EXPERIMENTMacro (real) scale HC resistant matle to avoid ground contatmination Hydrocarbon leakage system

23. THE EXPERIMENTMacro (real) scale Five plant species: Brachiaria brizantha (BR) (“grass”), Neonotonia wightii (SJ) (“soybean”),Saccharum spp (CA) (“sugar cane”), Phaseolus vulgaris (FE) (“bean”), and Zea mays (MI) (“maize”) .

25. Periodical spectral measuments of both leaf and canopy

26. Peridiocal leakages – daily leakage of 200l of HCs

27. Controlled irrigation

28. Samples collected for biochemical analysis every weekAPRIL MAY

30. Sampled area: 30cm;

32. 14 days after HC leakage began

33. 2600 L of HCs in the system = 130L per parcel

34. ProsSpecTIR Spectral resolution: VIS/NIR:125 channel; SWIR:232 channel

36. LYSIMETERSBrachiaria brizantha DSL GSL CTR CTR M1 (45 days/200mL) Morphological alterations M4 (93 days/250mL) M7 (145 days/300mL)

37. M1 = 35 days/0mL Morphological Alterations Canopy Roots M4 = 64 days/100mL GSL DSL CTR M7 = 99 days/200mL GSL CTR DSL Leaves LYSIMETERSNeonotonia wightii

38. MACRO SCALE EXPERIMENT CSe RATIO (R694/R760 ) GRASS SOYBEAN LYSIMETER - Leaves - Spectral Measument Spectral Measument PLATFORM - Dossel - Spectral Measument Spectral Measument

39. MACRO SCALE EXPERIMENT Comparative photos of plant canopies when spectral alterations are perceived through CSe ratios GRASS GSL/M4 CTR/M5 DSL/M4 SOYBEAN GSL/M5 CTR/M5 DSL/M4

41. LYSIMETERSNeonotonia wightii SHORTWAVE INFRARED (SWIR) REGION Spectral pattern at 2062 nm >> association with leaf biochemical analysis (rise in monosaccharides (“sugar”) content) monosaccharides Normalised average (% in relation to CTR) Wavelength (nm)

42. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) Two step algorithm (Almeida & Souza Filho, 2004; 2008): 1) Production of 15 spectral indices > enhancement of specific spectral signatures of vegetation properties 2) Principal Component Analysis applied to three sub-stes of spectral indices Indices applied to vegetation analysis Group Index Spectral Formula ProSpecTIR channels -Caroten Antocianin a-Chlorophyll b-Chlorophyll Carotenoids SIPI CSe NDVI VOG1 WBI MAC Leaf water Lignin Cellulose Nitrogen

43. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) GSL DSL CTR Degree of stress CSe Ratio Degree of stress based on the CSe (694nm/760nm) ratio

44. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) GSL DSL Degree of stress CTR PC1 - Group 1 (VNIR) a-Chlorophyll, b-Chlorophyll, Carotenoids Eigenvector matrix Eigenvector a-caroten antocian. a-Chlrop b-Chlorop Caroten. SIPI CSe

45. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) GSL Degree of stress DSL CTR PC1 - Group 2 (NIR) NDVI, VOG1 e WBI Eigenvector matrix Eigenvector

46. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) GSL Degree of stress DSL CTR PC2 – Group 3 (NIR/SWIR) Lignin EigenvectorLeaf Water Lignin Cellulose Nitrogen

47. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS) PC1 Group 1 GSL DSL PC1 Group 2 PC2 Group 3 CTR RGB Colour Composition R: PC1 - Group 1 (VNIR) G: PC1 - Group 2 (NIR) B: PC2 - Group 3 (NIR/SWIR)

48. DISCUSSIONS & CONCLUSIONS

50. It was possible to characterize the reflectance of leaves grown in soils contaminated by low concentrations of gasoline and diesel and differentiate them from plants grown on soil without HCs.

51. The use of selected vegetation indices showed a high correlation with the behavior of vegetation stressed by the presence of HCs in all three scales of observations.

52. The spectral changes were similar among species but more prominent for gasoline (GSL) than diesel (DSL), occurring at different timeframes and under different doses of HCs

53. The results confirm the higher toxicity of gasoline for all selected crops.

54. The development of this work supports the possibility to preserve certain crops along pipelines that can be used as a bio-indicator of small leakages and the types of crops more susceptible to stress-induced leakage.