Made available in DSpace on 2015-03-13T17:08:24Z (GMT). No. of bitstreams: 1 RenataCLA.pdf: 1406363 bytes, checksum: c23d0993b7ed86a192397c6e7f6d9580 (MD5) Previous issue date: 2004-10-14 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamar?, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamar? for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamar?. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier / Objetiva o estabelecimento de uma metodologia para monitoramento de derramamento de ?leo no mar, na ?rea de Explora??o Submersa do P?lo de Guamar?, no Estado do Rio Grande do Norte, utilizando imagens orbitais de radares de abertura sint?tica (SAR) integradas aos produtos meteoceanogr?ficos. A aplica??o do modelo metodol?gico foi composto pelas seguintes etapas: (1) a cria??o de um mapa base da ?rea de Explora??o; (2) o processamento de imagens NOAA/AVHRR e ERS-2 para gera??o de produtos meteoceanogr?ficos; (3) o processamento de imagens RADARSAT-1 para monitoramento das manchas de ?leo; (4) a integra??o da imagem RADARSAT-1 com os produtos de imagens NOAA/AVHRR e ERS-2; e (5) a estrutura??o de um banco de dados. A Integra??o da imagem RADARSAT-1 da Bacia Potiguar do dia 21.05.99 com o mapa base da ?rea de Explora??o do P?lo de Guamar? para a identifica??o das prov?veis fontes das manchas de ?leo, foi utilizada com sucesso na detec??o da prov?vel mancha de ?leo detectada pr?xima ? sa?da do emiss?rio submarino na ?rea de Explora??o do P?lo de Guamar?. Para subsidiar a integra??o da imagem RADARSAT-1 com os produtos de imagens NOAA/AVHRR e ERS-2, desenvolveu-se uma metodologia para a classifica??o das manchas de ?leo identificadas em imagens RADARSAT-1. Nesta metodologia, testou-se os seguintes algor?tmos de classifica??o n?o-supervisionada: K-means, Fuzzy k-means e Isodata, que s?o parte integrante do software PCI Geomatics, o qual foi utilizado para a filtragem das imagens RADARSAT-1. Para a avalia??o dos resultados, as manchas de ?leo submetidas ? classifica??o n?o-supervisionada foram comparadas aos resultados do Classificador Textural por Semivariograma (STC), o qual foi desenvolvido especificamente para esta finalidade e requer a utiliza??o do software PCI Geomatics para efetuar parte do processamento das imagens RADARSAT-1. Por fim, os resultados das classifica??es foram analisados atrav?s de An?lise Visual; C?lculo de Proporcionalidade de Grandezas e An?lise Estat?stica. Dentre os tr?s algoritmos de classifica??o testados n?o houve significantes altera??es em rela??o as manchas classificadas pelo STC, em nenhuma das an?lises efetuadas. Os procedimentos adotados demonstraram que a metodologia descrita aqui poder? ser aplicada com sucesso, utilizando os classificadores n?o supervisionados testados, o que acarretaria em diminui??o de tempo no processo de identifica??o e classifica??o de manchas de ?leo, em compara??o ? utiliza??o do classificador STC

Canada has become increasingly economically dependent on the exportation of bitumen to trans-oceanic international markets. As the export of Alberta bitumen from ports located in British Columbia increases, oil spill response and readiness measures become increasingly important. Although the frequency of ship-source oil spills has dramatically declined over the past several decades, they remain environmentally devastating when they occur. In the event of a marine spill, great lengths of shoreline are at risk of being contaminated. Once ashore, oil can persist for decades if shoreline hydraulic conditions are correct and remediation does not occur. Most commonly transported oils (e.g., fuel oils, Bunker C, crude oil, etc.) have been thoroughly studied, and their fate and behaviour in the event of a marine spill is well understood. In contrast, because diluted bitumen has been historically traded in relatively low quantities and has almost no spill history, there is a sizable knowledge gap regarding its effects and behaviour in both the marine environment and on coastal shorelines. The intent of this thesis was to develop a classification scheme to identify marine shorelines of high and low diluted bitumen (dilbit) retention for southeastern Vancouver Island, British Columbia. This study builds upon the outcome of former laboratory bench top dilbit and sediment research known as Bitumen Experiments (Bit_Ex). Bit_Ex investigated dilbit penetration and retention in six engineered sediment classifications ranging from coarse sand to very large pebble in accordance with the Wentworth Classification scheme. This research used Bit_Ex findings to predict dilbit retention in poorly sorted in-situ beach sediments found on shorelines representative of the southern coast of Vancouver Island, British Columbia, Canada. Field and laboratory measurements were conducted to document the occurrence of in-situ shoreline sediments and hydraulic conditions and were used to predict dilbit retention by comparing such characteristics between Bit_Ex and unconsolidated in-situ beach sediments. Saturated hydraulic conductivity (Ks) was measured using a double-ring constant-head infiltrometer. Measured Ks values were then compared to predicted Ks values generated by five semi-empirical Ks equations. A modified version of the Hazen Approximation was selected as the most appropriate. Using measured and calculated metrics, sediments were grouped as having either low or high dilbit retention. When sediments were analysed as homogenous samples, the experimental results suggested two of ten shorelines were composed of a combination of low and high retention sections, while the remaining eight sites were of low retention. Upon the isolation of coarse surface strata, results indicated two shorelines were entirely veneered with high retention sediments, and four shorelines were a combination of high and low retention. The residual four shorelines were found to be entirely composed of low retention sediments. The results illuminate the importance of shoreline stratification when predicting shoreline oil retention. This characteristic is a factor that current shoreline oil retention mapping techniques do not adequately consider. Additionally, the findings suggest that while sediments indicative of retaining weathered dilbit are relatively uncommon within Juan de Fuca and Harro Straits, high retention unweathered dilbit sediments are more common. / Graduate / 2018-06-26