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Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-11-03T20:42:55Z No. of bitstreams: 1 JoseEdsonDeAlmeidaJunior_DISSERT.pdf: 6070806 bytes, checksum: b15852e13e5be71af8ab041cf03063b8 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-11-17T00:14:16Z (GMT) No. of bitstreams: 1 JoseEdsonDeAlmeidaJunior_DISSERT.pdf: 6070806 bytes, checksum: b15852e13e5be71af8ab041cf03063b8 (MD5) / Made available in DSpace on 2017-11-17T00:14:16Z (GMT). No. of bitstreams: 1 JoseEdsonDeAlmeidaJunior_DISSERT.pdf: 6070806 bytes, checksum: b15852e13e5be71af8ab041cf03063b8 (MD5) Previous issue date: 2017-08-18 / O presente trabalho tem como objetivo a avalia??o multitemporal de curto prazo da retra??o numa fal?sia da Forma??o Barreiras, na ?rea do Centro de Lan?amento Barreira do Inferno (CLBI), localizada no litoral oriental do Estado do Rio Grande do Norte (RN). Os estudos foram conduzidos entre agosto de 2016 e fevereiro de 2017, com a utiliza??o do Laser Esc?ner Terrestre (LT), aparelho que utiliza o pulso laser para fazer o mapeamento da fal?sia. A primeira etapa do estudo usou os dados da nuvem de pontos levantada em 21 de agosto de 2016, para a constru??o de 10 Modelos Digitais do Terreno (MDT) em quatro diferentes softwares, para a sele??o do m?todo interpolador que melhor representa a superf?cie estudada. A segunda etapa consistiu na caracteriza??o da fal?sia quanto ao seu principal indutor erosivo, atrav?s da utiliza??o de 30 perfis transversais a face da fal?sia obtidos a partir dos MDTs, gerados na etapa anterior, resultando numa subdivis?o da fal?sia em 5 setores de acordo com esta caracteriza??o. As avalia??es e quantifica??o da eros?o total e da taxa de retra??o foram conduzidas a partir da compara??o entre os MDTs e perfis transversais gerados em cada um dos levantamentos. Os resultados mostraram que a fal?sia apresentou uma retra??o de aproximadamente 6 cm com uma eros?o total de 333 m? no per?odo de estudo. O resultado tamb?m mostrou a import?ncia de se avaliar a confiabilidade da nuvem de pontos com rela??o a presen?a de vazios, ocasionados por sombreamentos durante os levantamentos, que podem ser fontes de erros significativos. O estudo desta fal?sia se faz importante por ser o primeiro a utilizar o LT neste tipo de forma??o, como tamb?m por representar uma nova ferramenta para o entendimento da din?mica costeira. / This research aims a short-term multi-temporal evaluation of the seacliff retreat of the Barreiras Formation, in the Barreira do Inferno Launch Center (CLBI, in Portuguese) located in the eastern coast of Rio Grande do Norte (RN), Brazil. The studies were conducted between August 2016 and February 2017 through a Terrestrial Laser Scanning (TLS), which is equipment that utilizes a pulsed laser to map seacliffs face. The first phase of the study used the point cloud generated on August 21, 2016, for the construction of 10 Digital Elevation Model (DEM) via four different softwares for selecting the interpolation method that best represents the studied surface. The second phase was the description of the seacliff according to its main erosive cause through 30 transversal seacliff face profiles obtained through the DEM generated in the previous phase. It led to a subdivision of the seacliff in 5 segments according to its description. The evaluation and quantification of the net erosion and the retreat rate were conducted through comparing the DEMs with the transversal profiles generated. The results expressed that the seacliff had a retreat of approximately 6 centimeters with a net erosion of 333 m? during the study period. It was also observed the importance of evaluating the reliability of the point cloud because of the presence of blanks due to the shading during the data collection, which may cause significant errors. The evaluation of this seacliff was relevant not only because it was the first to be done through TLS in this type of formation, but also because it represents a new way for understanding the coast dynamic.

Context. Triangulated irregular network (TIN) can produce terrain meshes with a reduced triangle count compared to a regular grid. At the same time, TIN meshes are more challenging to optimize in real-time in comparison to other approaches. Objectives. This thesis explores efficient generation of view-dependent, adaptive TIN meshes for terrain during runtime with no or minimal preprocessing. Methods. Since the workings of the proposed technique is a novel approach, an empirical strategy was employed to present the findings instead of partial comparisons to related techniques. Results. To determine the result of the technique, run-time performance is measured and presented to provide incentives for implementation and improvements on the proposed algorithm. Several problem sizes are tested with varying terrain features to determine the effectiveness as a result of the features in the mesh.  Conclusions. We conclude that reducing the problem of mesh simplification to that of 2D Delaunay triangulation on sampled points spanning terrains is valid approach for triangulating on-the-fly. Moreover, this approach opens up for further improvements which may soon allow real-time triangulation of TINs.

The thesis deals with the issues of digital terrain model creation. It aims to explain the solution of an international contract, starting from gathering the data and finishing with the creation and visualization of the digital terrain model of the given location. The software AutoCAD Civil 3D 2013 is used for modeling. Main outcomes of the thesis are volume calculation of flood line, contoured map of the dam area, the digital model and its visualization.

As more data sources containing 3-D information are becoming available, an increased interest in 3-D imaging has emerged. Among these is the 3-D reconstruction of buildings and other man-made structures. A necessary preprocessing step is the detection and isolation of individual buildings that subsequently can be reconstructed in 3-D using various methodologies. Applications for both building detection and reconstruction have commercial use for urban planning, network planning for mobile communication (cell phone tower placement), spatial analysis of air pollution and noise nuisances, microclimate investigations, geographical information systems, security services and change detection from areas affected by natural disasters. Building detection and reconstruction are also used in the military for automatic target recognition and in entertainment for virtual tourism. Previously proposed building detection and reconstruction algorithms solely utilized aerial imagery. With the advent of Light Detection and Ranging (LiDAR) systems providing elevation data, current algorithms explore using captured LiDAR data as an additional feasible source of information. Additional sources of information can lead to automating techniques (alleviating their need for manual user intervention) as well as increasing their capabilities and accuracy. Several building detection approaches surveyed in the open literature have fundamental weaknesses that hinder their use; such as requiring multiple data sets from different sensors, mandating certain operations to be carried out manually, and limited functionality to only being able to detect certain types of buildings. In this work, a building detection system is proposed and implemented which strives to overcome the limitations seen in existing techniques. The developed framework is flexible in that it can perform building detection from just LiDAR data (first or last return), or just nadir, color aerial imagery. If data from both LiDAR and aerial imagery are available, then the algorithm will use them both for improved accuracy. Additionally, the proposed approach does not employ severely limiting assumptions thus enabling the end user to apply the approach to a wider variety of different building types. The proposed approach is extensively tested using real data sets and it is also compared with other existing techniques. Experimental results are presented.

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