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Field spectroscopy of plant water content in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa

dc.contributor.authorOumar, Zakariyyaa.
dc.date.accessioned2010-08-18T13:33:54Z
dc.date.available2010-08-18T13:33:54Z
dc.date.issued2008
dc.descriptionThesis (M.Sc.) - University of KwaZulu-Natal, Pietermaritzburg, 2008.en_US
dc.description.abstractThe measurement of plant water content is essential to assess stress and disturbance in forest plantations. Traditional techniques to assess plant water content are costly, time consuming and spatially restrictive. Remote sensing techniques offer the alternative of a non destructive and instantaneous method of assessing plant water content over large spatial scales where ground measurements would be impossible on a regular basis. The aim of this research was to assess the relationship between plant water content and reflectance data in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africa. Field reflectance and first derivative reflectance data were correlated with plant water content. The first derivative reflectance performed better than the field reflectance data in estimating plant water content with high correlations in the visible and mid-infrared portions of the electromagnetic spectrum. Several reflectance indices were also tested to evaluate their effectiveness in estimating plant water content and were compared to the red edge position. The red edge position calculated from the first derivative reflectance and from the linear four-point interpolation method performed better than all the water indices tested. It was therefore concluded that the red edge position can be used in association with other water indices as a stable spectral parameter to estimate plant water content on hyperspectral data. The South African satellite SumbandilaSat is due for launch in the near future and it is essential to test the utility of this satellite in estimating plant water content, a study which has not been done before. The field reflectance data from this study was resampled to the SumbandilaSat band settings and was put into a neural network to test its potential in estimating plant water content. The integrated approach involving neural networks and the resampled field spectral data successfully predicted plant water content with a correlation coefficient of 0.74 and a root mean square error (RMSE) of 1.41 on an independent test dataset outperforming the traditional multiple regression method of estimation. The potential of the SumbandilaSat wavebands to estimate plant water content was tested using a sensitivity analysis. The results from the sensitivity analysis indicated that the xanthophyll, blue and near infrared wavebands are the three most important wavebands used by the neural network in estimating plant water content. It was therefore concluded that these three bands of the SumbandilaSat are essential for plant water estimation. In general this study showed the potential of up-scaling field spectral data to the SumbandilaSat, the second South African satellite scheduled for launch in the near future.en_US
dc.identifier.urihttp://hdl.handle.net/10413/263
dc.language.isoenen_US
dc.subjectEucalyptus grandis--KwaZulu-Natal--Richmond.en_US
dc.subjectPlant-water relationships--Measurement.en_US
dc.subjectSpectrum analysis.en_US
dc.subjectEucalyptus grandis--Water requirements--KwaZulu-Natal.en_US
dc.subjectSpectral reflectance.en_US
dc.subjectForests and forestry--Remote sensing.en_US
dc.subjectForest management--KwaZulu-Natal.en_US
dc.subjectTrees--Effect of water levels on.en_US
dc.subjectTheses--Geography.en_US
dc.titleField spectroscopy of plant water content in Eucalyptus grandis forest stands in KwaZulu-Natal, South Africaen_US
dc.typeThesisen_US

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