Thesis (M.S.)--Middle East Technical University, 2003. / Keywords: Remote sensing, alteration mapping, spectral library, Cappadocian Volcanic Province.

Hydrovolcanic basaltic tephras from tuff rings and tuff cones were studied in order to better understand their origin and alteration processes. The visual and near infrared reflectance of tephras collected from Basin and Range tuff rings and tuff cones was measured in the laboratory. Further mineralogic and chemical information was gained through petrographic microscopy, X-ray diffraction, electron microprobe analysis and iron Mossbauer spectrometry. In addition, remotely sensed data from several airborne sensors was obtained for the Lunar Crater Volcanic Field in Nye County, Nevada and the Pavant Butte tuff cone in Millard County, Utah. Fresh tuff rings, resulting from dry pyroclastic surges, are composed of a variable mix of country rock fragments and unaltered sideromelane which has a dark reflectance spectrum dominated by Fe²⁺ crystal field bands near 1 and 2 μm. If water condenses on the sideromelane, a process of nearly syn-depositional hydration can occur. With increasing hydration, water and OH vibrational absorptions develop at 1.4 and 1.9 μm. Smectite clay minerals were recognized within thinly bedded tuff rings by the presence of a 2.2 μm absorption and by XRD results. These minerals have developed without extensive palgonitization. Tuff ring tephras can also become oxidized to the extent that a well developed Fe³⁺-O²⁻ charge transfer edge develops with weak Fe³⁺ crystal field features shortwards of 0.8 μm. The poorly inflated pyroclastic “flow”, that characterizes tuff cone formation, produces hot, wet, cohesive ash deposits that can alter relatively rapidly to palagonite. The reflectance of these highly palagonitized tephras is twice as high as that of tuff ring deposits, H₂O and OH vibrational absorption bands are also stronger and a 2.3 μm Mg-OH band is generally present. Increasing oxidation causes spectral features resulting from Fe³⁺ to become more pronounced. These include a shortwards shift in position and shallowing of the “1-μm” crystal field band and steepening of the Fe³⁺-O²⁻ charge transfer edge. Differences in spectral reflectance are ascribed primarily to differences in the degree of alteration which in turn is influenced by the water/magma ratio extant at the time of eruption. Remotely sensed data of hydrovolcanic vents acquired by several different air- and spaceborne sensors was also examined. These data sets were analyzed using a linear spectral mixture model. It was found that palagonite tuff constitutes an easily mapped spectral endmember, while the hydrated tuff typical of tuff rings is difficult to distinguish from other dark materials. The best mapping was performed with the systems with high spatial resolution such as the NSOO1 Thematic Mapper Simulator and the Geoscan Mk II advanced multispectral scanner. Airborne Visible/lnfrared Imaging Spectrometer (AVIRIS) data, calibrated to reflectance through reference endmember modelling, revealed previously undetected 2.2 μm absorption features in the palagonite tuff at Pavant Butte. The 1-μm feature in Pavant Butte palagonite tuff was mapped from the AVIRIS data using a band depth mapping routine although the resulting discrimination of palagonite tuffs was not as good as was obtained with the spectral mixture model.

<p> The Truckee Meadows (Reno, NV) sits in a tectonically complex area of western Nevada, where Walker Lane-style transtension is dominant throughout the region. A new Light Detection and Ranging (LiDAR) study focuses on the Truckee Meadows region of western Nevada, including the Reno/Sparks metropolitan area in Washoe County. We use the airborne LiDAR imagery (1485 sq. km) to create high quality, bare-earth topographic maps that were previously unattainable in vegetated, populated or alpine terrain. This approach gives us an opportunity to improve fault maps that may be outdated or incomplete in the area. Here we provide LiDAR imagery of a large section of Washoe County and an updated fault map of the greater Truckee Meadows region. </p><p> We also use this new LiDAR survey of the Truckee Meadows and nearby basins to constrain geometry, length, distribution, and slip rates along faults imaged by this new dataset. Estimated slip rates are compared to those derived from a geodetic block model constrained by Global Positioning Station (GPS) data to test for consistency. GPS station data and geologic mapping show that both east-west oriented extension and northwest-oriented right-lateral strike slip accommodate transtension as a backdrop for tectonics studies of region, with some northeast-oriented left-lateral strike slip. This study aims to better understand how this transtension is partitioned along remapped faults and newly identified structures in this urban setting, as the framework for strain accommodation in this area remains poorly understood. </p><p> Faults with normal offset were measured along strike using bare-earth LiDAR returns to determine the amount of vertical separation across geomorphic surfaces, and then converted to extension assuming a fault dip of 60 (+/-10) degrees. Since the primary geomorphic surfaces in this region are the result of Sierra Nevadan glacial outwash episodes, we use previously published geologic maps to link each surface to an associated date. When integrated across several basin perpendicular transects within the Mt. Rose pediment, we calculate a total extension rate of 0.87 (+0.40/-0.48) mm/yr for the southern Truckee Meadows basin. Integrated slip rates from fault scarp offsets are within the bounds of 1.23 (+/-0.70) mm/yr suggested by geodetic modeling. Block modeling highlights that north-striking faults primarily accommodate east-west extension, and so northwest-striking faults and/or block rotations must accommodate the northwest-directed shear seen in GPS velocities. This trend is bolstered by the discovery of a new northwest-oriented fault on Peavine Mountain 6 km east of the Mogul (2008) seismicity trend. Our study provides further evidence that the Truckee Meadows sits at a critical transition from north-striking normal faults in the southern part of the basin to northwest-oriented strike-slip faults to the north, an observation that mimics regional tectonics and geomorphology of the adjacent Lake Tahoe/Truckee system to the west.</p>

published_or_final_version / Geography and Geology / Master / Master of Philosophy

CDOM (chromophoric dissolved organic matter) plays an important role in determining underwater light field and aquatic photochemical and biological processes. Knowing CDOM properties, origin, sink, content, and distribution is able to provide us not only a useful approach to evaluate, but also a new perspective to understand water quality, carbon cycle, as well as the climate change. Remote sensing inversion of CDOM bears the potential capability to assess CDOM at large scale, but it has not been fully investigated yet. Particularly, the previous approaches cannot meet the accuracy and spatial resolution requirement for analyzing complex waters in estuarine and coastal regions. Therefore, a new scheme, which combines a newly developed inversion algorithm and hyperspectral remote sensing, is proposed to solve problems encountered in CDOM evaluation. This research covers three study sites, in the estuarine and coastal regions of the Mississippi River, Hudson River, and Neponset River. Very high resolution in situ data were collected in these sites and EO-1 Hyperion satellite images were also acquired accordingly. Based on a quasi-analytical algorithm (QAA), a QAA-CDOM algorithm was developed, by which CDOM absorption coefficient ag(440) is separated from adg(440)(total absorption coefficient of CDOM and non-algal particles). Some QAA's parameters and functions were also optimized, using available datasets (in situ, IOCCG, and NOMAD). Result validation in the Atchafalaya plume has proved that QAA-CDOM is capable of estimating ag(440) in excellent accuracy (RMSE=0.11 m−1 and R2=0.73 in the Atchafalaya River plume region). More importantly, applying QAA-CDOM to other locations, including the Mississippi River, Amazon River, and Moreton Bay, also derived very reasonable and accurate ag(440), covering a wide range from 0.01 to 15 m −1. This confirms that our method is applicable to a wide range of estuarine regions. The uncertainties involved in CDOM inversion were also analyzed, aiming to know the origin, magnitude, and propagation of uncertainty in different inversion phases. This work strongly indicates that the proposed scheme, QAA-CDOM hyperspectral remote sensing inversion, is robust and reliable to quantify CDOM's concentration, distribution and dynamic for diverse waters, and hence can be applied to other regions.

Orientador: Carlos Roberto de Souza Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Geociências / Made available in DSpace on 2018-08-27T02:30:54Z (GMT). No. of bitstreams: 1 Locatelli_PauloEduardo_M.pdf: 8425905 bytes, checksum: a57947ba3b089a77dc310bac5fc58f26 (MD5) Previous issue date: 2014 / Resumo: A extração automática de feições lineares a partir de técnicas de processamento digital de imagens atualmente é uma ampla possibilidade em Geociências, permitindo a interpretação de lineamentos e reconhecimento de padrões em fotos aéreas e imagens de satélite. Entretanto, o que ainda predomina é a extração dessas feições de forma manual, o que geralmente se traduz como um trabalho demorado, sujeito à experiência do usuário e critérios subjetivos. A extração e interpretação de feições lineares auxiliada por algoritmos e métodos computacionais permite acelerar o processo e reduzir a subjetividade inerente ao método manual. Nesse sentido, diferentes algoritmos têm sido propostos com a finalidade de otimizar o processo de detecção destas feições. Em Geociências, feições lineares geralmente estão associadas a elementos da estrutura geológica, como zonas de falha, famílias de fraturas, enxames de diques e cinturões de cisalhamento. A identificação dessas estruturas é essencial na exploração mineral e de hidrocarbonetos, entre outras áreas. No entanto, a identificação de lineamentos em superfície não garante a existência de correlação com estruturas geológicas em profundidade. Neste contexto, este trabalho utiliza a região de Serra Leste, Carajás (PA), como área teste para verificar a recorrência de um lineamento, em diferentes fontes de dados, no sentido de ponderar a sua relevância geológica em níveis crustais diversos. Os dados empregados no trabalho incluem: (i) modelos digitais de elevação (MDEs) extraídos de dados óticos (ASTER) e de micro-ondas na banda-C (SRTM), (ii) imagens multiespectrais orbitais, e (iii) produtos gerados a partir de dados aerogeofísicos (magnetometria). Aos MDEs foram aplicados algoritmos de extração automática de lineamentos e técnica de realce das feições morfoestruturais. Aos dados aeromagnéticos foram aplicados (i) métodos de realce das anomalias magnéticas; (ii) deconvolução de Euler e (iii) métodos de inversão para se obter o modelo de susceptibilidade magnética. Os resultados obtidos indicam que mapas de declividade, gerados a partir dos MDEs, são produtos singulares para extração otimizada de lineamentos com base em programas semiautomáticos. Os produtos aeromagnéticos indicam uma grande coerência entre anomalias magnéticas realçadas, independente de uso de métodos direto ou inverso de processamento. Entretanto, a comparação entre as anomalias magnéticas em profundidade e lineamentos superficiais marcados por feições do relevo mostra significativa decorrelação. Essa constatação tem impacto importante sobre o uso de mapas estruturais foto-interpretados ou gerados automaticamente na exploração mineral e petrolífera / Abstract: The automatic extraction of linear features by digital image processing techniques has been showing a wide range of possibility in Geosciences allowing the interpretation of lineaments and pattern recognition in aerial photos and satellite images. However, there is still a predominance of manual extraction of these features, which usually is a time consuming job and subject to expertise and subjective criteria. The extraction and interpretation of linear features when aided by computational methods and algorithms can speed up the process and reduce the subjectivity inherent to the manual process. In this sense, several algorithms have been proposed in order to optimize the detection process of these features. In geosciences, linear features are commonly related with geological structure elements, such as fault or shear zones, fractures families and dyke swarms. The identification of these structures is essential to mineral and hydrocarbons exploration, among other areas. However, the identification of surface lineaments does not ensure correlation with in-depth geological structures. In this context, this work uses Serra Leste region, in Carajás Province, Pará State, Brazil, as a testing area to check the recurrence of lineaments in different data sources in order to assess its geological significance in several crustal levels. The data used in this study include: (i) digital elevation models (DEMs) extracted from the optical data (ASTER) and in the microwave C-band (SRTM), (ii) orbital multispectral images, and (iii) products generated from airborne geophysics (magnetometry). Algorithms for automatic extraction of lineaments and technical enhancement of morphostructural features were applied to the DEMs. With regard to the magnetic data, the flowing techniques: (i) methods for enhancement of magnetic anomalies, (ii) Euler deconvolution and (iii) inversion methods to recover susceptibility model. The results indicate that slope maps, generated from the DEMs, are unique products for an optimized lineament extraction using semi-automated methods. The magnetic products display a wide coherence between enhanced magnetic anomalies, independent of the use of direct or inverse processing methods. Nonetheless, the comparison between the magnetic anomalies at depth and surface lineament, marked by relief features, shows no significant correlation. This finding has important impact on the use of photo-interpreted structural maps or automatically generated in mineral and oil exploration / Mestrado / Geologia e Recursos Naturais / Mestre em Geociências

Thesis (M.Sc. (Geography)) --University of Limpopo, 2018 / Soil erosion, which is a critical component of land degradation, is one of the serious global environmental problems often threatening food security, water resources, and biodiversity. A comprehensive assessment and analysis of remote sensing applications in the spatial soil erosion mapping and monitoring over time and space is therefore, important for providing effective management and rehabilitation approaches at local, national and regional scales. The overall aim of the study was to assess the use of multispectral remote sensing sensors in mapping and monitoring the spatio-temporal variations in levels of soil erosion in the former homelands of Sekhukhune district, South Africa. Firstly, the effectiveness of the new and freely available moderate-resolution multispectral remote sensing data (Landsat 8 Operation Land Imager: OLI and Sentinel-2 Multi-Spectral Instrument: MSI) derived spectral bands, vegetation indices, and a combination of spectral bands and vegetation indices in mapping the spatio-temporal variation of soil erosion in the former homelands of Sekhukhune District, South Africa is compared. The study further determines the most optimal individual sensor variables that can accurately map soil erosion. The results showed that the integration of spectral bands and spectral vegetation indices yielded high soil erosion overall classification accuracies for both sensors. Sentinel-2 data produced an OA of 83, 81% whereas Landsat 8 has an OA of 82.86%. The study further established that Sentinel-2 MSI bands located in the NIR (0.785-0.900 μm), red edge (0.698-0.785μm) and SWIR (1.565-2.280 μm) regions were the most optimal for discriminating degraded soils from other land cover types. For Landsat 8 OLI, only the SWIR (1.560-2.300 μm), NIR (0.845-0.885 μm) region were selected as the best regions. Of the eighteen spectral vegetation indices computed, Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) and Global Environmental Monitoring Index (GEMI) were selected as the most suitable for detecting and mapping soil erosion. Secondly, the study assessed soil erosion in the former homelands of Sekhukhune, South Africa by applying a time-series analysis (2002 and 2017), to track changes of areas affected by varying degrees of erosion. Specifically, the study assessed and mapped changes of eroded areas (wet and dry season), using multi-date Landsat products 8 OLI and 7 Enhanced Thematic Mapper (ETM+)). Additionally, the study used extracted eroded areas and overlay analysis was performed together with geology, slope and the Topographic Wetness Index (TWI) of the area under study to assess whether and to what extent the observed erosional trends can be explained. ii Time series analysis indicated that the dry season of 2002, experienced 16.61 % (224733 ha) of erosion whereas in 2017 19.71% was observed. A similar trend was also observed in the wet season. This work also indicates that the dominant geology type Lebowa granite: and Rustenburg layered its lithology strata experienced more erosional disturbances than other geological types. Slopes between 2-5% (Nearly level) experienced more erosion and vice-versa. On the hand, the relationship between TWI and eroded areas showed that much erosion occurred between 3 and 6 TWI values in all the seasons for the two different years, however, the dry season of 2002 had a slightly higher relationship and vice-versa. We, therefore, recommend use and integration of freely and readily available new and free generation broadband sensors, such as Landsat data and environmental variables if soil erosion has to be well documented for purposes of effective soil rehabilitation and conservation. Keywords: Food security Global changes, Land degradation, Land-based ecosystems, Land management practices, Satellite data, Soil conservation, Sustainable Development; Topographic Wetness Index; Time series analysis.

The objective of this thesis was to identify the mechanisms associated with the recurrence of rock-slope instability along the R518 and R523 roads in Limpopo. Advanced geotechnical methods and ASTER imagery were used for the purpose while a predictive rockfall hazard rating matrix chart and rock slope stability charts for unsaturated sensitive clay soil and rock slopes were to be developed. The influence of extreme rainfall on the slope stability of the sensitive clay soil was also evaluated. To achieve the above, field observations, geological mapping, kinematic analysis, and limit equilibrium were performed. The latter involved toppling, transitional and rotational analyses. Numerical simulation was finally resorted to. The following software packages were employed: SWEDGE, SLIDE, RocData, RocFall, DIPS, RocPlane, and Phase 2. The simulation outputs were analyzed in conjunction with ASTER images. The advanced remote sensing data paved the way for landslide susceptibility analysis. From all the above, rockfall hazard prediction charts and slope stability prediction charts were developed. Several factors were also shown by numerical simulation to influence slope instability in the area of study, i.e. sites along the R518 and R523 roads in the Thulamela Municipality. The most important factors are extreme rainfall, steep slopes, geological features and water streams in the region, and improper road construction. Owing to the complexity of the failure mechanisms in the study area, it was concluded that both slope stability prediction charts and rock hazard matrix charts are very useful. They indeed enable one to characterize slope instability in sensitive clay soils as well as rockfall hazards in the study area. It is however recommended that future work is undertaken to explore the use of sophisticated and scientific methods. This is instrumental in the development of predictive tools for rock deformation and displacement in landslide events. / Electrical and Mining Engineering / D. Phil. (Mining Engineering)