The measurement of topography is a key aspect of geomorphology research, and the prevalence of high resolution topographic data predominantly from Light Detection And Ranging (LiDAR) in the past decade has facilitated a revolution in the quantitative study of planetary surface processes. From this increased quality of data, many techniques have been developed to quantify processes occurring at diverse spatial and temporal scales; from the flow of material down a hill-slope to the uplift and subsequent erosion of mountain ranges. Such insights have identified signatures of processes imprinted on landscapes. These include physical processes such as wildfires and landslides, biological processes such as animal burrowing and tree throw, in addition to tectonic uplift and large scale sediment transport. These signatures are observed in both the morphology of hill-slopes and their connection to the channel network, thereby allowing measures of topography to provide quantitative measures of the rates of processes shaping the Earth’s surface. This thesis is concerned with the development and application of reproducible topographic analysis techniques, to yield new insights into hill-slope sediment transport and to provide accurate metrics for quantifying hill-slope properties, including hill-slope length (LH) and relief (R). The measurement of hill-slope length can be performed through the inversion of drainage density, or the analysis of slope-area plots. However, in Chapter 3 I present a method which quantifies the length of hill-slopes through the generation of hill-slope flow paths. The flow path method is shown to be the most reliable of these methods, and is able to provide measurements of the properties of individual hill-slopes, rather than the basin or landscape averaged techniques commonly employed. The topographic predictions of the LH-R relationship of the nonlinear sediment flux law, stating that the rate of sediment transport is nonlinearly dependent on hill-slope gradient, are also tested and contrasted with the predictions of a linear sediment flux law. This provides the first purely topography based test of a sediment flux law. Through the fitting of a prediction of the nonlinear flux derived model to these measurements of hill-slope length and relief, the critical gradient of each landscape, a key parameter in the nonlinear sediment flux law, is also constrained. A nondimensional framework for erosion rate and relief, which allows the comparison of hill-slopes with differing properties in order to identify landscape transience is presented in Chapter 4. This analysis technique builds upon the work performed in Chapter 3, utilizing similar measurements of hill-slope properties, including hill-slope length and relief. The software produced alongside this chapter is shown to reproduce the results of previous studies which have employed this technique. The method is employed on a new landscape in Coweeta, North Carolina where subtle evidence of topographic decay is presented, consistent with models of Miocene topographic rejuvenation in this location. A detailed sensitivity analysis of the technique is performed, highlighting the need for careful parameterization of any analysis, to ensure meaningful results. This method is also employed to estimate an average critical gradient for each landscape, presenting more evidence building upon the evidence presented in Chapter 3 that a broad range of critical gradients exist for any given landscape. The work presented in Chapter 5 attempts to constrain the limits of the geomorphic analyses presented in the previous chapters, when they are applied to low resolution topographic data. A series of topographic datasets are generated at resolutions ranging from 1 to 30 meters upon which topographic analyses are performed. I test two common channel extraction algorithms and find that a simple geometric method, which identifies tangential curvature thresholds in the landscape, provides a more accurate representation of the channel network in low resolution topographic data than a process based method which identifies the topographic signature of channel initiation. The measurement of curvature is also evaluated, and alongside the estimation of diffusivity, is shown to be sensitive to data resolution, however landscape properties also exhibit a strong control on these measurements, where the larger scale curvature signal of Gabilan Mesa, California is more robust than the sharp ridgelines of Santa Cruz Island, California. Finally, the techniques developed in Chapter 3 to measure hill-slope length and relief are tested and are shown to be robust at grid sizes up to 30 meters, with the caveat that an accurate channel network can be constrained.

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 2008

Submitted by William Justo Figueiro (williamjf) on 2015-07-01T23:37:49Z No. of bitstreams: 1 10.pdf: 1839460 bytes, checksum: 72eb68f5839e6788cf3f08b69ca3d26c (MD5) / Made available in DSpace on 2015-07-01T23:37:49Z (GMT). No. of bitstreams: 1 10.pdf: 1839460 bytes, checksum: 72eb68f5839e6788cf3f08b69ca3d26c (MD5) Previous issue date: 2011 / FAPERGS - Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul / O sistema LIDAR obtém nuvens de pontos georreferenciadas que podem ser convertidas em Modelos Digitais de Afloramentos (MDAs). Os pulsos de laser são gerados e emitidos por um Laser Scanner Terrestre, que atinge a superfície do afloramento em diferentes pontos. Estes objetos refletem o pulso incidente, que volta para o equipamento. Com isso, a distância entre o sensor e o objeto é determinada com base no intervalo de tempo entre a emissão e o retorno do pulso. Para fins de Modelagem Digital de Afloramentos (MDA) o uso dessa técnica é recente e necessita do desenvolvimento de pesquisas. Diante disso, o objetivo desse trabalho foi estabelecer uma sequencia de métodos envolvendo a aquisição e processamento de nuvem de pontos e a visualização e interpretação de superfícies e volumes de um Modelo Digital de Afloramentos (MDA). A Rocha da Pedra Pintada, localizado no Rio Grande do Sul na Cidade de Caçapava do Sul, foi imageado a partir de 7 estações e a nuvem totalizou 17 milhões de pontos, que foi convertida, após processamento, em um MDA. Para a interpretação geológica, utilizou-se a técnica de ortorretificação para sobrepor a nuvem de pontos a fotografias de alta resolução do afloramento, o que agregou qualidade na visualização e interpretação do MDA. Dificuldades nas etapas de tratamento dos dados ocorreram em razão do grande volume de dados, da ausência de recursos de otimização de processamento e da limitação no gerenciamento de banco de dados. Além disso, faz-se necessário desenvolver um aplicativo eficiente de visualização tridimensional com ferramentas especificas de interpretação geológica. / The LIDAR system provides georeferrenced clouds with thousand-to-million of points which can be converted in digital outcrops models. A laser beam is emitted and captured by a laser scanner after reaching an outcrop in many different positions. Based on the travel time between sensor and outcrop it is possible to determine the position of each point with high accuracy. This technique is still a novelty for applied studies in Geology, especially in Digital Outcrop Models (DOMs), being necessary research and development. Thus, the goal of this work was establish a workflow concerning acquisition and processing of point clouds, and visualization and geological interpretation of DOMs. The Pedra Pintada, located in the state Rio Grande do Sul in the city Caçapava do Sul outcrop was imaged from seven different stations and the cloud has 17 million points, converted in a DOM after processing. The geological interpretation was made possible by the orthorectification technique, in which a high resolution photograph overlies the point cloud and the visual quality is obtained. The huge volume of data, the lack of optimized processing resources and the inadequate dataset management became visualization and interpretation of DOMs a difficult task. Furthermore, it is necessary to develop a software with an efficient tridimensional visualization system with specific tools for geological interpretations.

Submitted by William Justo Figueiro (williamjf) on 2015-07-09T22:32:57Z No. of bitstreams: 1 27b.pdf: 4120563 bytes, checksum: 28666d8a39aa4371e2cad8353a3b6fc2 (MD5) / Made available in DSpace on 2015-07-09T22:32:57Z (GMT). No. of bitstreams: 1 27b.pdf: 4120563 bytes, checksum: 28666d8a39aa4371e2cad8353a3b6fc2 (MD5) Previous issue date: 2012-08-01 / Petrobras - Petróleo Brasileiro S. A. / UNISINOS - Universidade do Vale do Rio dos Sinos / O presente estudo visou o desenvolvimento e aplicação de uma metodologia para a detecção e classificação de diferentes respostas espectrais em nuvens de pontos obtidas a partir de escâner a laser terrestre (Laser Scanner Terrestre) com o intuito de identificar a presença de diferentes rochas em afloramentos e a geração de um Modelo Digital de Afloramento. A ferramenta para a classificação de padrões espectrais, denominada K-Clouds, foi desenvolvida com base em análise de agrupamentos (clusters), que a partir de uma indicação do número de classes fornecido pelo usuário através da análise de um histograma dos dados, realiza a classificação da nuvem de pontos. Os dados classificados podem então ser interpretados por geólogos para uma melhor compreensão e identificação das rochas presentes no afloramento. Além da detecção de diferentes rochas, verificouse que é possível detectar pequenas alterações nas características físico-químicas das mesmas, como aquelas causadas por intemperismo e variação composicional. / The present study aimed to develop and implement a method for detection and classification of spectral signatures in point clouds obtained from Terrestrial Laser Scanner in order to identify the presence of different rocks in outcrops and to generate a Digital Outcrop Model. To achieve this objective, a software based on cluster analysis was created, named K-Clouds. This software was developed through a partnership between UNISINOS and the company V3D. This tool was designed to, beginning with an analysis and interpretation of a histogram from a point cloud of the outcrop and subsequently indication of a number of classes provided by the user, process the intensity return values. This classified information can then be interpreted by geologists, to provide a better understanding and identification from the existing rocks in the outcrop. Beyond the detection of different rocks, this work was able to detect small changes in the physical-chemical characteristics of the rocks, as they were caused by weathering or compositional changes.