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Stellenbosch University (2019)

Regional mapping of spekboom canopy cover using very high resolution aerial imagery

Harris, Dugal Jeremy

Titre : Regional mapping of spekboom canopy cover using very high resolution aerial imagery

Auteur : Harris, Dugal Jeremy

Université de soutenance : Stellenbosch University

Grade : Doctor of Philosophy (PhD) 2019

Résumé partiel
Widespread degradation of subtropical thicket (South Africa) by poorly managed pastoralism has led to substantial decreases in ecological functioning and biodiversity. Once degraded, thicket does not recover after the removal of livestock, but requires active intervention for restoration. It has been shown that planting spekboom (Portulacaria afra), a dominant and keystone thicket species, increases biomass, improves soil health and creates conditions that support the natural regeneration of biodiversity. Spatial data, especially spekboom canopy cover maps, are required to inform and support large-scale restoration. This research aimed to develop and demonstrate a semi-automated spekboom canopy cover mapping method. A large study area in the Little Karoo in South Africa was selected to encompass the ecological heterogeneity of the wider region. Following a literature review, very high resolution (VHR) multi-spectral aerial imagery was identified as a viable data source for the fine-scale discrimination of spekboom. A set of 2228 aerial images covering the study area was subsequently acquired from Chief Directorate : National Geo-spatial Information (NGI). Techniques for (1) radiometric correction and (2) feature selection were devised to address specific challenges of regional canopy cover mapping. These techniques then formed components of the spekboom canopy cover mapping method. The need for the first technique, called radiometric homogenisation, arose from the presence of problematic radiometric variation in the aerial imagery. Radiometric homogenisation corrects for varying atmospheric and bidirectional reflectance distribution function (BRDF) effects by calibration with concurrent and collocated satellite surface reflectance data. In contrast to other radiometric correction methods, manual placement or acquisition of reflectance targets is not required. Moreover, it is not necessary to have detailed knowledge of atmospheric conditions at the time of capture. An experiment was conducted to establish the efficacy and accuracy of the technique. Homogenised images of the study area were validated by visual inspection and statistical comparison to surface reflectance reference data. Recognisable anomalies such as hot spots and seam lines were removed, and statistical results compared well to competing methods. While the technique was developed in the context of the spekboom canopy cover mapping problem, it could also be applied to general radiometric correction of VHR imagery. Radiometric homogenisation is especially applicable to large study areas where radiometric uncertainty can prevent accurate classification. The second technique, called feature clustering and ranking (FCR), was devised to address problems of sub-optimality and instability that often arise when applying feature selection to redundant data. Unlike other feature selection approaches, FCR allows for the optional inclusion of factors other than relevance (such as computation and measurement cost) in the selection criteria. An experiment was conducted to compare the effects of redundancy on popular feature selection approaches and FCR. Results confirmed that redundancy has a negative impact on commonly used ranking and greedy search (stepwise) feature selection methods. FCR provided the best accuracy and stability performance, confirming its value for selecting stable, informative features from high dimensional data containing redundancy

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