Thesis (M.S.)--University of Wisconsin--Madison, 1984. / Two folded maps in pocket. Typescript. Includes tables. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 133-148).

Thesis (doctoral)--University of Tartu, 2006. / This dissertation is based on 3 papers.

Orientador: Gilberto Amaral / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Geociencias / Made available in DSpace on 2018-07-24T01:50:00Z (GMT). No. of bitstreams: 1 Duarte_MariaIriandeMascena_M.pdf: 3738528 bytes, checksum: 3a8905f2052baf8a035d8178927962a7 (MD5) Previous issue date: 1998 / Resumo: O presente trabalho aborda o tratamento e integração de dados aerogeofisicos (gamaespectrometria e magnetometria), geológicos e de imagens do Landsat5- TM. Os mesmos foram analisados individualmente e de forma integrada, utilizando-se técnicas de processamento digital de imagens (PDI) e de sistemas georeferenciados de informações (SIG), com ênfase na geologia do Supergrupo Rio das Velhas (NE do Quadrilátero Ferrífero, MG). procurou-se com isto contribuir para a compreensão do contexto geológico da região e de seu potencial metalogenético para ouro. A análise dos produtos individuais mostrou que os melhores resultados foram obtidos através dos dados aerogeofisicos, onde a gamaespectrometria exibiu uma grande eficácia na correlação com as unidades geológicas mapeadas na área, enquanto a magnetometria mostrou-se eficaz no reconhecimento e correlação com a estruturação geral da área. As imagem do Landsat5- TM não apresentaram bons resultados na discriminação litológica, em virtude da presença da grande quantidade de vegetação e ao espesso manto de intemperismo existente na área. A extração e o tratamento dos alinhamentos estruturais, permitiu separar áreas com diferentes níveis de fTaturamento que podem servir como uma ferramenta na seleção de áreas favoráveis a mineralizações, em especial as auríferas. A partir da integração dos dados gamaespectrométricos com os traços de fTaturas extraídos da imagem do Landsat5- TM, procurou-se selecionar áreas favoráveis ou prioritárias a pesquisa mineral para ocorrências de ouro. Os resultados demonstram a possibilidade da aplicação dos dados gamaespectrométricos integrados aos traços de fraturas à seleção de áreas prioritárias a pesquisa mineral, mesmo em regiões de densa cobertura vegetal / Abstract: The analysis of the geology of the Archean Rio das Velhas Supergroup, in the northeastem portion of the Quadrilátero Ferrífero, and its gold mineralizations, using remote sensing, aerogeophysical and geological data integration was the main objective of this work. Digital image processing and georeferenced information systems (GIS) techniques were applied to Landsat-TM and aerogeophysical data (magnetics and gamma-spectrometry), in order to obtain additional lithological and structural information and its relationship with known gold deposits in the area. For lithology, the best results were obtained with gamma-spectrometric data which presented a good correlation with the known mapped units. Magnetic data were useful for mapping iron formations as well as the main structural trends. Landsat-TM image analysis presented poor results for lithology due to the presence of intense weathering and vegetation cover. However, its infra-red bands were useful for extraction of fracture traces whose digital processing allowed the identification of zones with different brittle behavior, potentially linked to hydrothermal processes. GIS data integration, using gamma-spectrometry, :fracture trace data and location of mineral occurrences, resulted in the definition of areas potentially favourable for mineral exploration, even in areas with thick soil and vegetation covers / Mestrado / Metalogenese / Mestre em Geociências

No description available.

Thesis (Ph. D.)--Oregon State University, 1984. / Typescript (photocopy). Includes bibliographical references (leaves 97-99). Also available on the World Wide Web.

No description available.

Typescript (photocopy) / Thesis (Ph. D.)--University of Hawaii at Manoa, 1980. / Bibliography: leaves [193]-201. / Microfiche. / xii, 201 leaves, bound ill. (some col.), maps 28 cm

Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 68-69).

Being able to accurately map forest carbon is a critical step in the global carbon cycle modeling and management process. This project is aimed at enhancing the current methodologies used for forest carbon mapping, and applying a method to account for any errors produced. By doing so, more accurate decisions can be made based on the knowledge gained from forest carbon maps; such as policy decisions on how to manage forests, or how to mitigate climate change. The use of remotely sensed images, in combination with Forest Inventory and Analysis (FIA) data, is one such way of doing this. This study compared three different methods; including linear regression, cosimulation, and up-scaled cosimulation to interpolate forest carbon based on a defined relationship between sample plots of national FIA data and satellite images. An uncertainty analysis was completed in an effort to quantify, and separate the different sources of error produced within a cosimulation mapping effort. The results indicated that the band ratio of TM4 / TM5 + TM4 / TM7 had the highest correlation coefficient, around 0.56, with the FIA forest carbon values. At a resolution of 90 m ×by 90 m, co-simulation predicted carbon values from about 14 Mg/ha, to 135 Mg/ha. The regression model, at the same resolution, estimated carbon values from about -17 Mg/ha, to 2,400 Mg/ha. Up-scaled cosimulation at a resolution of 990 m x× 990 m, predicted carbon values of ranging from 16 Mg/ha, to 133 Mg/ha. The uncertainty analysis was unable to produce any statistically significant results, with all R2 values below 0.1. These results showed that using a linear regression produced some impossible estimates, while cosimulation led to more realistic values. However, no conclusion can be made when comparing the methods based on the map validation techniques used. Although limited validation of the results was conducted, using both the FIA data and some independent sampling data; further work that focuses on validation is recommended.

Forests are important natural resources of Canada. Their renewal has been recognized to be important for continued wood supply and for other benefits. Consequently, the major emphasis of forest management activities focuses upon restocking clearcut forest lands. Effective planning and successful implementation of reforestation programs require efficient techniques for obtaining timely and accurate information regarding restocking status over cutover forest lands. In this thesis the potential of Landsat thematic mapper (TM) data for monitoring reforesting clearcuts was investigated. Landsat-5 TM data covering clearcut forest lands reforesting with lodgepole pine (Pinus contorta Dougl.) were analyzed. To assess spectral separability of various restocking classes and classifying reforestation areas according to their stocking status multivariate distance measures were employed to select the optimum three band subset from six reflective TM bands. Three commonly used vegetation indices, namely the ratio vegetation index, the normalized difference vegetation index, and the infrared index, were also studied for quantitative assessment of vegetation. The main conclusion of the study is that TM bands 3, 4, and 5 are the best for discriminating various restocking classes. The classification accuracy was estimated to be approximately 90 percent. The infrared index appears to be the most suitable vegetation index for quantitative assessment of reforestation. / Forestry, Faculty of / Graduate