Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/55196
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dc.contributor.authorWhite, D.-
dc.contributor.authorWilliams, M.-
dc.contributor.authorBarr, S.-
dc.date.issued2008-
dc.identifier.citationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008; 37(B7):243-248-
dc.identifier.issn1682-1750-
dc.identifier.urihttp://hdl.handle.net/2440/55196-
dc.descriptionAlso cited as: Silk Road for information from imagery: proceedings of the XXIst ISPRS Congress, 3 to 11 July 2008 in Beijing, China; Commission VII papers, pp. 243-248-
dc.description.abstractPrevious studies conducted under controlled laboratory and controlled field conditions have demonstrated the ability of hyperspectral techniques to detect vegetation stress associated with elevated levels of soil gas and associated soil oxygen depletion. This paper investigates the capability and transferability of these hyperspectral techniques, in particular the Smith et al. (2004) 725:702 nm ratio, to identify vegetation stress features associated with sub-soil disturbance resulting from gas pipeline earthworks under heterogeneous field conditions. Field spectroradiometry data of barley were acquired in 2005 and 2006 at selected transects perpendicular to a stretch of buried gas pipeline in Aberdeenshire. Spectral reflectance and absorption features in the VIS-NIR are evaluated through first derivate analysis to establish their position, shape and magnitude and used to determine narrow waveband ratios which are tightly coupled to changes in photosynthetic function resulting from vegetation stress. First derivative ratios, 723:700 and 725:702 nm, detected vegetation stress above the gas pipeline where soil had been disturbed and were the same order of magnitude for the 2005 and 2006 data. Ratio values were similar to those conducted under controlled conditions by Smith et al. (2004), with differences of up to 56 % for spring barley between locations of soil disturbance and locations away from the pipeline, R2 accounting for up to 62 % of the variance in the ratios of the regression. Student’s T-tests revealed that the ratios were statistically significantly different between stress and no known stress within zones of soil disturbance at the 0.05 confidence level.-
dc.description.statementofresponsibilityD. C. White, M. Williams and S. L. Barr-
dc.description.urihttp://www.isprs.org/congresses/beijing2008/proceedings/tc7.aspx-
dc.language.isoen-
dc.publisherInternational Society for Photogrammetry and Remote Sensing-
dc.source.urihttp://www.isprs.org/proceedings/XXXVII/congress/7_pdf/3_WG-VII-3/06.pdf-
dc.subjectHyperspectral-
dc.subjectVegetation-
dc.subjectSoil-
dc.subjectRadiometry-
dc.subjectSpectral-
dc.subjectEnvironment-
dc.subjectAnalysis-
dc.subjectDetection-
dc.titleDetecting sub-surface soil disturbance using hyperspectral first derivative band ratios of associated vegetation stress-
dc.typeJournal article-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest
Earth and Environmental Sciences publications
Environment Institute publications

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