Application of AVIRIS data in detection of oil-induced vegetation stress and cover change at Jornada, New Mexico

TitleApplication of AVIRIS data in detection of oil-induced vegetation stress and cover change at Jornada, New Mexico
Publication TypeJournal Article
Year of Publication2005
AuthorsLi L, Ustin SL, Lay M
JournalRemote Sensing of Environment
Date Published2005
Accession NumberJRN00423
Call Number00847
Keywordsarticle, AVIRIS data, journal, oil spill, spectral mixture analysis, vegetation stress
AbstractOn June 1, 2000, an oil spill accident occurred along transportation pipeline located in the Jornada Experimental Range (USDA), Jornada,New Mexico, a long-term ecological research (LTER). In order to detect potential vegetation stress caused by the accident, two AVIRIS datasets of the oil spill area, before and after the oil release, are analyzed and the reliability of several techniques in the detection of vegetationstress is examined. The polynomial fitting and Lagrangian interpolation, and spectral mixture analysis (SMA) are applied to the AVIRIS data sets. The firsttwo methods are applied for the detection of the bred-edgeQ shift in vegetation reflectance spectra, and the last for the detection of change invegetation fraction. The results indicate that the polynomial fitting and Lagrangian interpolation both are able to detect a red-shift of thevegetation bred-edgeQ, but the latter’s performance depends on the band combination used and is sensitive to data noise. The polynomialfitting results are inconsistent in detection of bthe red-edgeQ shift, while Lagrangian interpolation is not. Within the oil spill area, the fractionestimates of vegetation resulting from SMA demonstrate a decrease (10–30%) of the vegetation fraction after the accident, indicating stressedvegetation and cover change. The result also indicates that areas of extremely large decrease (N40%) in plant cover outside of the oil spill areais due to the response of grasses due to the water stress in 2000, and that the integration of some auxiliary data on ecological andclimatological data with the analysis of remotely sensed data is thus very important to the interpretation of the detection results. A sensitivityanalysis indicates that the detected vegetation cover change is insensitive to the noise introduced by the radiometric normalization.@2004 Elsevier Inc. All rights reserved.
Reprint EditionIn File (12/15/2005)