No description available.

This study describes the use of Landsat MSS and TM for geological applications in two Scottish areas: Lochindorb and Loch Tuel; and one Malaysian area: Kedah-Perak. The areas are poorly exposed and highly vegetated. The data were digitally processed with the objective of producing more interpretable images. The processes include contrast enhancement, ratioing, subtraction, principal component analysis, discriminant analysis, filtering, the combination of images as colour composites, and producing negative images of the data. Geological interpretation of the most informative images was undertaken by visual interpretation. In the Lochindorb area, Landsat MSS imagery did not prove useful for superficial deposits mapping, and the resolution offers by the TM is still not sufficient for semi-detailed mapping at scale 1: 50,000. The combination of TM imagery and aerial photographs, however, made the mapping task easier and produced "better" map. In the Kedah-Perak area, textural information is more important than spectral information for lithological interpretation and many image units correlate well with major mapped rocks. Lineaments are well expressed on Landsat imagery and are mapped for the Loch Tummel and Kedäh-Perak areas. The lineament maps for both areas confirm many mapped faults and reveal a new prominent lineaments (probably faults). For the Loch Tummel area, the relative merits of TM versus MSS data were examined. Both produced similar results regarding major lineament orientations, but the TM provides a good improvement over the MSS in the ability to map lineaments. For both areas, lineaments appear to be correlated with geomorphology (lithology), and with the occurrence of ore deposits and probably geologic structure for the Kedah-Perak area. Landsat imagery can be used to aid lithological mapping in Malaysia, but has not proved useful for Scotland (U. K. ) because of different objectives and constraints. However, Landsat imagery is an effective tool in mapping lineaments for both areas.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, in fulfilment of the requirements for the Degree of Master of Science. Johannesburg, 20 January 2017. / Sand dune movements can be effectively monitored through the comparison of multitemporal satellite images. However, not all remote sensing platforms are suitable to study sand dunes. This study compares coarse (Landsat 7 and 8) and fine (Worldview 2) resolution platforms, specifically focussing on sand dunes within the Ubārī Sand Sea (Libya), and identified the average migration rate and direction for the linear dunes within a section of the Ubārī sand sea for the time period from 2002-2015 with the use of Landsat imagery. Two band combinations were compared with the use of two supervised classifications. The best combination was found to be red, green, blue and near-infrared band combination and the maximum likelihood classifier. The dune features, namely the crest, slope and interdunal areas were successfully classified based on both the coarse and fine resolution imagery, but the accuracy with which it can be classified are different between the two resolutions. The classifications based on the Worldview 2 imagery had overall accuracies ranging from 55.43 - 60.83% with kappa values of 0.3486 – 0.4225 compared to the overall accuracies and kappa values of the classifications based on the Landsat 8 imagery ranging from 52.11 – 64.67% and 0.3878 – 0.4927 respectively. An average migration rate of 8.64 (± 4.65) m/yr in a generally north western direction was calculated based on the analysis of remote sensing data with some variations in this rate and the size and shape of the dunes. It was found that although Worldview 2 imagery provides more accurate and precise mensuration data, and smaller dunes identified from Worldview data were not delineated clearly on the Landsat imagery. Landsat imagery is sufficient for the studying of dunes at a regional scale. This means that for studies concerned with the dune patterns and movements within sand seas, Landsat is sufficient. In studies where the specific dynamics of specific dunes are to be selected, a finer resolution is required; platforms such as Worldview are needed in order to gain more detailed insight and to link the past and present day climate and environmental change. / MT2017

published_or_final_version / Geography and Geology / Master / Master of Philosophy

No description available.

Thesis (M.S.)--Oregon State University, 1993. / Typescript (photocopy). Includes bibliographical references. Also available on the World Wide Web.

Thèse (Ph.D.)--Université de Sherbrooke (Canada), 2007. / Titre de l'écran-titre (visionné le 11 mars 2009). In ProQuest dissertations and theses. Publié aussi en version papier.

Thèse (Ph.D.)--Université de Sherbrooke (Canada), 2008. / Titre de l'écran-titre (visionné le 29 sept. 2009). In ProQuest dissertations and theses. Publié aussi en version papier.

M.Sc. (Geography) / Landsat TM and SPOTMSS data were analysed and classified using two different procedures and the resulting maps were evaluated with respect to land use in the Sandton urban-rural fringe. The Landsat TM data consisted of 6 spectral bands (0,45-0,52, 0,52-0,60, 0,63-0,69, 0,760,90, 1,55-1,75, 2,08-2,35 IJm). The SPOT MSS data (one image taken in summer and one in winter) consisted of 3 spectral bands (0,50-0,59, 0,61-0,68, 0,79-0,89 IJm). The data from the two systems were stretched statistically so that all bands showed similar spread on both sides of the median. A ground truth map was obtained from the Sandton Town Council against which the final land use maps derived from Landsat and SPOT were compared for accuracy. The satellite data were analysed in two steps to compile the land use maps: The first step was a cluster analysis based on ISODATA of Ball and Hall (Ball, m..al, 1965). The result were 3 maps with 34, 30 and 35 spectral classes for Landsat TM and the SPOT seasonal images. The next step was a combination of cluster analysis and nearest-neighbour analysis. Examples of the land uses required for the final maps were chosen and for each a histogram of spectral classes was compiled. A nearest-neighbour analysis was done to determine how many pixels of the same class lie next to each other. All the pixels in the spectrally classified image were viewed in conjunction with the surrounding pixels; a histogram and nearest-neighbour analysis was done for each. The results were then compared to that of the land use examples and each pixel was allocated to the land use class which it most resembled. The evaluation involved a computerised comparison of the land use maps with the ground truth map obtained from the Sandton Town Council. The final results were three different land use maps, each created with one image (Landsat TM, SPOTsummer, or winter images). The land use classes identified on each map were: agricultural holdings; high density residential areas; low density residential areas; townhouses (only from the SPOTimages); a combination of commercial and industrial areas; parks; unused land; recreational areas. Comparative use of the two satellite based data acquisition systems leads the author to conclude that: Landsat TM was best for mapping agricultural holdings and high density residential areas; the SPOT summer image was best for mapping townhouses, parks, unused land and recreational areas, the SPOT winter image was best for mapping low density residential areas and commercial/industrial areas. Both systems may be regarded as data sources for urban research, for the mapping of land use in urban-rural fringes. The result of this study is the provision of an easily updated land use map of the Sandton urban-rural fringe to aid effective planning and control where future development will take place.

Geographic Information System technology today allows for the rapid analysis of vast amounts of spatial and non-spatial data. The power of a GIS can only be effected with the rapid collection of accurate input data. This is particularly true in the case of the South African National Working for Water (WFW) Programme where large volumes of spatial data on alien vegetation infestations are captured throughout the country. Alien vegetation clearing contracts cannot be generated, for WFW, without this data, so that the accurate capture of such data is crucial to the success of the programme. Mapping Invasive Alien Plant (IAP) data within WFW is a perennial problem (Coetzee, pers com, 2002), because not enough mapping is being done to meet the annual requirements of the programme in the various provinces. This is re-iterated by Richardson, 2004, who states that there is a shortage of accurate data on IAP abundance in South Africa. Therefore there is a need to investigate alternate methods of data capture; such as remote sensing, whilst working within the existing WFW data capture standards. The aim of this research was to investigate the use of Landsat ETM imagery as a data capture source for mapping alien vegetation for the WFW Programme in terms of their approved mapping methods, for both automated and manual classification techniques. The automated and manual classification results were compared to control data captured by differential Global Positioning Systems (DGPS). The research tested the various methods of data capture using Landsat ETM images over a range of study sites of varying complexity: a simple grassland area, a medium complexity grassy fynbos site and a complicated indigenous forest site. An important component of the research was to develop a mapping (classification) Ranking System based upon variables identified by WFW as fundamental in data capture decision making: spatial and positional accuracy, time constraints and cost constraints for three typical alien invaded areas. The mapping Ranking System compared the results of the various mapping methods for each factor for the study sites against each other. This provided an indication of which mapping method is the most efficient or suitable for a particular area.