Thesis (M.S.)--University of Wyoming, 2007. / Title from PDF title page (viewed on June 16, 2008). Includes bibliographical references (p. 70-78).

Thesis (M.S.)--University of Missouri-Columbia, 2004. / 1 folded map in pocket. Typescript. Includes bibliographical references (leaves 134-145). Also available on the Internet.

Thesis (M.S.)--University of Missouri-Columbia, 2004. / 1 folded map in pocket. Typescript. Includes bibliographical references (leaves 134-145). Also available on the Internet.

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).