Souza Filho Talk IGARSS 2011 presentation.pptx


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Souza Filho Talk IGARSS 2011 presentation.pptx

  1. 1. LAPIG<br />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<br />Carlos Roberto Souza Filho1, Lucíola Magalhães1; Giuliana Quitério1 Marcos Nopper1 , Teodoro Almeida2 ; Wilson Olveira3; Lis Rabaco3; Renato Rocha3<br />University of Campinas, Campinas, Brazil 1<br />University of São Paulo, São Paulo, Brazil2<br />Petrobras S.A./CENPES, Rio de Janeiro, Brazil3<br />
  2. 2. INTRODUCTION & OBJECTIVES<br /><ul><li>Current methods of pipeline monitoring poses hindrances to the early detection of small hydrocarbon spills.
  3. 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).
  4. 4. The study comprises both greenhouse and real scale experiments, where we will seek the probable impacts of hydrocarbon contamination through spectral changes in 5 plant species commonly present in the vicinity of pipelines, particularly in Brazil, with focus on Brachiaria brizantha (“grass”) and Neonotonia wightii (“soybean”)</li></li></ul><li>THE EXPERIMENTS<br />
  5. 5. THE EXPERIMENT<br />2 SCALES: small scale experiment (“lysimeter”) & macro scale (real, field scale). <br />3 types of spectral analysis <br />Leaf (lysimeter) (FieldSpec Hi-Res – ASD)<br />Canopy (macro scale experiment) (FieldSpec Hi-Res – ASD)<br />Canopy (airborne hyperspectral survey) (357 bands at 5nm resolution -ProSpecTIR-VS)<br /><ul><li> 2 contaminants: diesel (DSL) and gasoline (GSL)</li></li></ul><li>THE EXPERIMENT Vegetation Species<br />Resistance (i.e. plagues) and commonness <br />Agronomic importance <br />Extensive occurrence along pipelines<br />Neonotonia wightii<br />“soybean” <br />Brachiaria brizantha<br />“perenial grass” <br />
  6. 6. THE EXPERIMENTLysimeters<br />
  7. 7. THE EXPERIMENTLysimeters<br />
  8. 8. THE EXPERIMENTLysimeters<br />
  9. 9. LYSIMETERSBrachiaria brizantha (grass)<br />Brachiaria brisantha <br /><ul><li> Experiments – timeframes of 5 months.
  10. 10. Leakage – begininning with plantation
  11. 11. Periodical spectral measurements
  12. 12. Periodical leakages
  13. 13. Controlled irrigation
  14. 14. Samples collected for biochemical analysis by the end of the experiment</li></ul>Measurement<br />Time-days<br />Vol-HC-ml<br />SWHC* <br />*Soil Water Holding Capacity<br />
  15. 15. LISYMETERNeonotonia wightii (soybean)<br />Neonotonia wightii<br /><ul><li> Experiments: timeframes of 3 months
  16. 16. Leakage – beginning 30 days after plantation
  17. 17. Periodical spectral measurements
  18. 18. Periodical leakages (once per 15 days)
  19. 19. Controlled irrigation (automatically)
  20. 20. Samples collected for biochemical analysis by the end of the experiment</li></ul>Measurement<br />Time-days<br />Vol-HC-ml<br />SWHC* <br />
  21. 21. THE EXPERIMENTMacro (real) scale <br />
  22. 22. THE EXPERIMENTMacro (real) scale <br />HC resistant matle to avoid ground contamination<br />Hydrocarbon leakage system<br />
  23. 23. THE EXPERIMENTMacro (real) scale <br />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”) . <br />
  24. 24. THE EXPERIMENTMacro (real) scale <br /><ul><li> Experiments – timeframe of 2 months (May-April/2010)
  25. 25. Periodical spectral measurements of both leaf and canopy
  26. 26. Peridiocal leakages – daily leakage of 200l of HCs
  27. 27. Controlled irrigation
  28. 28. Samples collected for biochemical analysis every week</li></ul>APRIL<br />MAY<br />
  29. 29. THE EXPERIMENTCanopy Measuments from Specifically-designed Platform<br />Platform for canopy spectral measuments<br /><ul><li> FieldSpec High Resolution (ASD);
  30. 30. Sampled area: 30cm;
  31. 31. 10 samples per parcel.</li></li></ul><li>THE EXPERIMENTProSpecTIR Airborne System <br /><ul><li>Data acquisition: MAy, 18th, 2010
  32. 32. 14 days after HC leakage began
  33. 33. 2600 L of HCs in the system = 130L per parcel
  34. 34. ProsSpecTIR Spectral resolution: VIS/NIR:125 channel; SWIR:232 channel
  35. 35. Spatial resolution: 60 cm</li></li></ul><li>RESULTS<br />
  36. 36. LYSIMETERSBrachiaria brizantha <br />DSL<br />GSL<br />CTR<br />CTR<br />M1 (45 days/200mL)<br />Morphological alterations<br />M4 (93 days/250mL)<br />M7 (145 days/300mL)<br />
  37. 37. M1 = 35 days/0mL<br />Morphological Alterations<br />Canopy<br />Roots<br />M4 = 64 days/100mL<br />GSL<br />DSL<br />CTR<br />M7 = 99 days/200mL<br /> GSL CTR DSL <br />Leaves<br />LYSIMETERSNeonotonia wightii<br />
  38. 38. MACRO SCALE EXPERIMENT CSe RATIO (R694/R760 )<br />GRASS <br />SOYBEAN <br />LYSIMETER<br />- Leaves -<br />Spectral Measument<br />Spectral Measument<br />PLATFORM<br />- Dossel -<br />Spectral Measument<br />Spectral Measument<br />
  39. 39. MACRO SCALE EXPERIMENT<br />Comparative photos of plant canopies when spectral alterations are perceived through CSe ratios<br />GRASS<br />GSL/M4<br />CTR/M5<br />DSL/M4<br />SOYBEAN<br />GSL/M5<br />CTR/M5<br />DSL/M4<br />
  40. 40. LYSIMETERSBrachiaria brizantha <br />SHORTWAVE INFRARED (SWIR) REGION<br />Three patterns are observed at:<br /><ul><li> 2477nm ; 2485 - 2495nm e 2440 - 2485nm</li></ul>Continuum-removed reflectance<br />Wavelength (nm)<br />Poly-Saccharides<br />
  41. 41. LYSIMETERSNeonotonia wightii<br />SHORTWAVE INFRARED (SWIR) REGION<br />Spectral pattern at 2062 nm >> association with leaf biochemical analysis (rise in monosaccharides (“sugar”) content)<br />monosaccharides<br />Normalised average (% in relation to CTR)<br />Wavelength (nm)<br />
  42. 42. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />Two step algorithm (Almeida & Souza Filho, 2004; 2008):<br />1) Production of 15 spectral indices > enhancement of specific spectral signatures of vegetation properties <br />2) Principal Component Analysis applied to three sub-stes of spectral indices<br />Indices applied to vegetation analysis <br />Group<br />Index<br />Spectral Formula<br />ProSpecTIR channels<br />-Caroten<br />Antocianin<br />a-Chlorophyll<br />b-Chlorophyll<br />Carotenoids<br />SIPI<br />CSe<br />NDVI<br />VOG1<br />WBI<br />MAC<br />Leaf water<br />Lignin<br />Cellulose<br />Nitrogen<br />
  43. 43. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />GSL<br />DSL<br />CTR<br />Degree of stress<br />CSe Ratio<br />Degree of stress based on the CSe (694nm/760nm) ratio <br />
  44. 44. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />GSL<br />DSL<br />Degree of stress<br />CTR<br />PC1 - Group 1 (VNIR)<br />a-Chlorophyll, b-Chlorophyll, Carotenoids <br />Eigenvector matrix<br />Eigenvector a-caroten antocian. a-Chlrop b-Chlorop Caroten. SIPI CSe<br />
  45. 45. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />GSL<br />Degree of stress<br />DSL<br />CTR<br />PC1 - Group 2 (NIR)<br />NDVI, VOG1 e WBI<br />Eigenvector matrix<br />Eigenvector<br />
  46. 46. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />GSL<br />Degree of stress<br />DSL<br />CTR<br />PC2 – Group 3 (NIR/SWIR)<br />Lignin<br />EigenvectorLeaf Water Lignin Cellulose Nitrogen<br />
  47. 47. INFORMATION EXTRACTION OF HYPERSPECTRAL DATA (PROSPECTIR VS)<br />PC1<br />Group 1<br />GSL<br />DSL<br />PC1<br />Group 2<br />PC2<br />Group 3<br />CTR<br />RGB Colour Composition<br />R: PC1 - Group 1 (VNIR)<br />G: PC1 - Group 2 (NIR) <br />B: PC2 - Group 3 (NIR/SWIR)<br /> <br />
  49. 49. DISCUSSIONS & CONCLUSIONS<br /><ul><li>The proposed methodology showed a high correlation between canopy spectral measurements taken at close range with the FieldSpec Hi-Res sensor and from the airborne ProspecTIR-VS sensor.
  50. 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. 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. 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. 53. The results confirm the higher toxicity of gasoline for all selected crops.
  54. 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.
  55. 55. It also makes a first step on the establishment of the initial timing (i.e., exposure time and volume of injected hydrocarbons) when the contamination effects are more perceptible remotely.</li></li></ul><li>LAPIG<br />Thank you !<br />Geosciences Institute<br />University of Campinas (UNICAMP)<br /><br /><br /><br />