Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518562
Title: Remote sensing of grassland with contaminated soil using the spectral red-edge
Author: Llewellyn, Gary Michael
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2009
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Abstract:
In most cases contaminants are concealed in soil and under vegetation and therefore can not be measured directly by remote sensing. However, soil contaminants were detected using the spectral red-edge to indicate vegetation stress caused by the presence of the contaminants. An improved red-edge position (REP) was developed and gave a slight improvement in the predictive capability over existing indices and an effective additional diagnostic indicator of soil contamination was found to be the spatial pattern of the REP. Where an area had high levels of hydrocarbon in the soil it also had a high level of variation. The indication was that spatial variation of spectral indices (especially the REP) may be more useful than the spectral index value for the detection and mapping of soil contamination. Field analysis and radiative transfer modelling (using a coupled leaf and canopy model, LIBSAIL) showed the influence of vertical layering in the grassland canopy. The influence of a vegetated under-storey on the red-edge was found to be greatest when different absorption spectra were present and high within-the-leaf scattering. The former defined wavelength positions of features while the later determined if they were resolvable in a spectrum. This greater understanding of the grassland canopy identified the importance of fully surveying vegetation canopy structure, especially in complex, multi-layered canopies such as those found with contamination. With this understanding of what the red-edge can reveal, remote sensing is an effective tool for the detection of contamination.
Supervisor: Curran, Paul ; Milton, Edward Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.518562  DOI: Not available
Keywords: GB Physical geography
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