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Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Geological remote sensing is a powerful tool for lithological discrimination, especially in arid regions with minimal vegetative cover to obscure rock exposures. Commercial multispectral imaging satellites provide a broad spectral range with which to target specific rock types. Landsat ETM+ (7), ASTER, and SPOT 5 multispectral images were acquired and digitally processed: band ratioing, principle components analysis, and maximum likelihood supervised classification. The sensors were evaluated on the ability to discriminate between sedimentary rocks in a structurally complex setting. The study focusses on the formations of the Naukluft Nappe Complex, Namibia. Previous work of the area had to be consulted in order to identify the main target rock types. Dolomite, limestone, quartzite, and shale were determined to make up the majority of rock types in the area. Landsat, ASTER, and SPOT 5 imagery were acquired and pre-processed. Each was subjected to transform techniques: band ratios and PCA. Band ratios were tailored to highlighted target rock types as well as a number of control ratios to ensure the integrity of important ratios. PCA components were inspected to find the most useful ones which were combined into FCCs. Transform results, expert knowledge, and a geological map were consulted to identify training and accuracy samples for the supervised classifications. All three classifications made use of the same set of training and accuracy samples to facilitate useful comparisons. Transform results were promising for Landsat and ASTER images, while SPOT 5 struggled. The limited spectral resolution of SPOT 5 limited its use for identifying target rock types, with the superior spatial resolution contributing very little. Landsat benefitted from good spectral resolution. This allowed for good performance with highlighting limestone and dolomite, while being less successful with shale. Quartzite was a real problem as the spectral resolution of Landsat could not cover this range as well. ASTER, having the highest spectral resolution, could distinguish between all four target rock types. Landsat and ASTER results suffered in areas where formations were relatively thin (smaller than sensor spatial resolution). The supervised classification results were similar to the transforms in that both Landsat and ASTER provided useful results, while SPOT 5 failed to yield definitive results. Accuracy assessment determined that ASTER performed the best at 98.72%. Landsat produced an accuracy of 93.29% while SPOT 5 was 80.17% accuracy. Landsat completely overestimated the amount of quartzite present, while all results classified significant proportions Quaternary sediments as shale. Limestone was well represented in even the poorest results, while dolomite usually struggled in areas where it was in close association with quartzite. Silica yields relatively strong responses in the TIR spectrum which could lead to misclassification of dolomite, which also has strong TIR signatures. / AFRIKAANSE OPSOMMING: Geologiese afstandswaarneming is 'n kragtige tegniek vir litologiese diskriminasie, veral in droë streke met minimale plantbedekking om dagsome te verduister. Kommersiële multispektrale satelliete beelde bied 'n breë spektrale reeks waarmee spesifieke gesteentetipes geteiken kan word. Landsat ETM + (7), ASTER, en SPOT 5 multispektrale beelde was bekom en digitaal verwerk: bandverhoudings, hoofkomponente-ontleding, en maksimum waarskynlikheid klassifikasie. Die sensors is geëvalueer op hul vermoë om te onderskei tussen sedimentêre gesteentes in 'n struktureel komplekse omgewing. Die studie fokus op die formasies van die Naukluft Dekblad Kompleks, Namibië. Vorige werk van die area was geraadpleeg om die hoofgesteentetipes te identifiseer. Dit was bepaal dat dolomiet, kalksteen, kwartsiet, en skalie die oorgrote meerderheid van kliptipes in area opgemaak het. Landsat, ASTER, en SPOT 5 beelde is verkry en voorverwerk. Elke beeld was onderwerp aan transformasietegnieke: bandverhoudings en hoofkomponente-ontleding. Bandverhoudings is aangepas om teiken rotstipes uit te lig asook 'n aantal kontrole bandverhoudings om die integriteit van belangrike verhoudings te verseker. Hoofkomponente-ontleding komponente is ondersoek om die mees bruikbares te vind en dié was gekombineer in valse kleur samestellings. Transformasie resultate, deskundige kennis, en 'n geologiese kaart was geraadpleeg om opleidings- en verwysingsmonsters was verkry vanaf die beelde vir die klassifikasies. Al drie klassifikasies gebruik gemaak van dieselfde stel van die opleiding- en akkuraatheidsmonsters om sodoende betekenisvolle vergelykings te verseker. Transformasie resultate is belowend vir Landsat en ASTER beelde, terwyl SPOT 5 minder bruikbaar was. Die noue spektrale resolusie van SPOT 5 beperk die gebruik daarvan vir die identifisering van teiken gesteentetipes terwyl die hoë ruimtelike resolusie baie min bydra. Landsat het voordeel getrek uit goeie spektrale resolusie. Dit goeie resultate opgelwer met die klem op kalksteen en dolomiet, terwyl skalie aansienlik swakker resultate opgelewer het. Kwartsiet was 'n werklike probleem omdat die spektrale resolusie van Landsat nie breed genoeg was om hierdie kliptipe te onderskei nie. ASTER, met die hoogste spektrale resolusie, kon onderskei tussen al vier teiken rotstipes. Landsat en ASTER resultate was baie negatief beïnvloed in gebiede waar formasies relatief dun was (kleiner as sensor ruimtelike resolusie). Die klassifikasie resultate was soortgelyk aan die transformasies in dat beide Landsat en ASTER nuttige resultate opgelewer het, terwyl SPOT 5 misluk het. Akkuraatheids assessering het bepaal dat ASTER die beste gevaar het met 98,72%. Landsat het 'n akkuraatheid van 93,29% opgelewer, terwyl SPOT 5 80,17% akkuraat was. Landsat het die hoeveelheid kwartsiet heeltemal oorskat, terwyl al die resultate groot hoeveelhede Kwaternêre sedimente as skalie geklassifiseer het. Kalksteen is goed verteenwoordig in tot die armste resultate, terwyl resultate gewoonlik afgeneem het waar dolomiet in noue verband met kwartsiet was. Dit is moontlik asgevolg van silika se relatiewe sterk reaksies in die termiese infra-rooi spektrum wat kan lei tot die foutiewe klassifisering met dolomiet (wat ook sterk reageer in die TIR spektrum).

Thesis (MSc)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Anthropological influences are threatening the state of many savanna ecosystems in most rural landscapes around the world. Effective monitoring and management of these landscapes requires up to date maps and data on the state of the environment. Degradation data over a range of scales is often not readily available due to a lack of financial resources, time and technical capabilities. The aim of this research was to use a medium resolution multispectral SPOT 5 image from 2010 and Landsat 8 images from 2014 to map habitat intactness in the Bushbuckridge and Kruger National Park (KNP) region. The images were pre-processed and segmented into meaningful image objects using an object based image analysis (OBIA) approach. Five image derivatives namely: brightness, compactness, NIR standard deviation, area and the normalised difference vegetation index (NDVI) were evaluated for their capability to model habitat intactness. A habitat intactness index was generated by combining the five derivatives and rescaling them to a data range of 0 to 10, with 0 representing completely transformed areas, 10 being undisturbed natural vegetation. Field data were collected in October 2014 using a field assessment form consisting of 10 questions related to ecosystem state, in order to facilitate comparisons with the remote sensing habitat intactness index. Both satellite data sets yielded low overall accuracies below 30%. The results were improved by applying a correction factor to the reference data. The results significantly improved with SPOT 5 producing the highest overall accuracy of 62.6%. The Landsat 8 image for May 2014 achieved an improved accuracy of 60.2%. The SPOT 5 results showed to be a better predictor of habitat intactness as it assigned natural vegetation with better accuracy, while Landsat 8 correctly assigned mostly degraded areas. These findings suggest that the method was not easily transferable between the different satellite sensors in this savanna landscape, with a high occurrence of forest plantations and rural settlements too. These areas caused high omission errors in the reference data, resulting in the moderate overall accuracies obtained. It is recommended that these sites be clipped out of the analysis in order to obtain acceptable accuracies for non-transformed areas. The study nevertheless demonstrated that the habitat intactness index maps derived can be a useful data source for mapping general patterns of degradation especially on a regional scale. Therefore, the methods tested in this study can be integrated in habitat mapping projects for effective conservation planning. / AFRIKAANSE OPSOMMING: Antropologiese invloede bedreig die toestand van savanna-ekostelsels in die meeste landelike landskappe regoor die wêreld. Doeltreffende monitering en bestuur van hierdie landskappe vereis op datum kaarte en inligting oor die toestand van die omgewing. Agteruitgangsdata van verskillende skale is dikwels nie geredelik beskikbaar nie weens 'n gebrek aan finansiële hulpbronne, tyd en tegniese vermoëns. Die doel van hierdie navorsing was om ‘n hoë resolusie multispektrale SPOT 5 beeld van 2010 en Landsat 8 beelde van 2014 te gebruik om die habitatongeskondenheid in die Bushbuckridge en Kruger Nasionale Park (KNP) streek te karteer. Die beelde is voorverwerk en gesegmenteer om sinvolle beeldvoorwerpe te skep deur die gebruik van ‘n voorwerp gebaseerde beeldanalise (OBIA) benadering. Vyf beeldafgeleides naamlik: helderheid, kompaktheid, NIR standaardafwyking, area en die genormaliseerde verskil plantegroei-indeks (NDVI) is geëvalueer vir hul vermoë om habitat ongeskondenheid te modelleer. ‘n Habitatongeskondenheidsindeks is gegenereer deur die kombinasie van die vyf afgeleides wat herskaal is na 'n datareeks van 0 tot 10, met 0 om totaal getransformeerde gebiede te verteenwoordig en 10 om ongestoorde natuurlike plantegroei voor te stel. Velddata is versamel in Oktober 2014 met gebruik van 'n veldassesseringsvorm, bestaande uit 10 vrae wat verband hou met die toestand van die ekostelsel, om vergelykings met die afstandswaarneming habitatongeskondenheidsindeks te fasiliteer. Beide satellietdatastelle het lae algehele akkuraatheid onder 30% opgelewer. Die resultate is deur die toepassing van 'n regstellingsfaktor tot die verwysing data verbeter. Die resultate het aansienlik verbeter met SPOT 5 wat die hoogste algehele akkuraatheid van 62.6% gelewer het. Die Landsat 8 beeld vir Mei 2014 bereik 'n verbeterde akkuraatheid van 60.2%. Die SPOT 5 resultate het geblyk om ‘n beter voorspeller van habitatongeskondenheid te wees as gevolg van ‘n beter akkuraatheid vir natuurlike plantegroei, terwyl Landsat meestal gedegradeerde gebiede kon voorspel. Hierdie bevindinge dui daarop dat die metode nie maklik oordraagbaar was tussen die verskillende satelliet sensors in hierdie savanna landskap nie, veral as gevolg van ‘n hoë voorkoms van bosbouplantasies en landelike nedersettings. Hierdie gebiede veroorsaak hoë weglatingsfoute in die verwysing data, wat lei tot gematigde algehele akkuraatheid. Dit word aanbeveel dat hierdie areas gemasker word tydens die ontleding om aanvaarbare akkuraatheid te verkry vir nie-getransformeerde gebiede. Nogtans het die studie getoon dat die afgeleide habitatongeskondenheidsindekskaarte ‘n nuttige bron van data kan wees vir die kartering van algemene patrone van agteruitgang, veral op 'n plaaslike skaal. Daarom kan die getoetsde metodes in die studie in habitatkarteringsprojekte vir doeltreffende bewaring beplanning geïntegreer word. Stellenbosch University https://scholar.sun.ac.za