Eventos de inundação são fenômenos geralmente associados a eventos de chuvas intensas. Nesses eventos a cobertura de nuvens, normalmente, prejudica o mapeamento com uso de imagens ópticas. Assim, este trabalho tem como objetivo avaliar os resultados de mapeamento de áreas de inundação utilizando imagens SAR e SRTM. Para aplicação dos métodos foram analisadas as áreas de inundação nas cidades de Santa Fe e Parana, na Argentina. Embora a maior inundação registrada tenha sido no ano de 2003, registros de inundação são frequentemente observados nas províncias de Santa Fé e Entre Ríos. Foi utilizado imagens do satélite Sentinel-1, equipado com sensor C-SAR com dupla polarização (VV/VH). As imagens obtidas são do tipo Interferométrico (IW) Ground Range Detected (GRDH) com resolução espacial de 10 m. Foram utilizadas imagens em períodos com e sem eventos de inundação entre 2016 e 2017, calibradas e coregistradas. Sobre as imagens foram aplicadas técnicas de limiarização e de análise temporal para mapear a mancha de inundação. Também foi elaborado mapa a partir do Modelo Digital de Elevação (MDE) utilizando como referência estações de medição de nível da água dos rios. A validação de todos os métodos foi totalmente remota, baseando-se em um mapeamento da inundação de abril de 2003 na cidade de Santa Fe. Além disso, imagens publicadas de eventos de inundação complementaram a validação e foi possível comparar os resultados com uma imagem óptica Landsat – 8 com resolução de 15 m do dia 22 de fevereiro de 2016, quando o nível do rio Paraná estava acima do nível de alerta Os resultados dos três mapeamentos foram somados para formar uma única imagem com a mancha de inundação em comum. Entre as melhores acurácias, o método de análise do MDE atingiu o melhor resultado, 82% da área de inundação, no entanto, considerando os três métodos, a acurácia atinge mais de 91% de precisão. A técnica de limiarização foi mais eficiente em áreas sem alvos verticais, como áreas urbanas por exemplo. O MDE foi eficiente para simular a inundação em todos os alvos, no entanto em modelos de elevação com melhor resolução, o resultado final do mapeamento será mais preciso. A análise temporal mostrou ser uma técnica promissora para mapeamentos de inundação, no entanto um mapa detalhado de uso de solo é fundamental para aprimorar o resultado desta análise. Todos os processos foram feitos remotamente, possibilitando o desenvolvimento no futuro de um sistema automático para detecção de evento de inundação que pode ser aplicado em áreas com características similares. / Flood events usually go hand in hand with intensive rainfall during which clouds compromise any mapping attempts with optical imagery. Thus, this thesis aims at evaluate the results of mapping flood areas using SAR and SRTM images. For this purpose, flood areas in the cities Santa Fe and Parana in Argentina were analyzed. While the worst flood was registered in 2003, flood events frequently occur in both provinces Santa Fé and Entre Ríos. The employed Sentinel-1 satellite carrying a C-SAR sensor with dual polarization (VV/VH) provided interferometric (IW) Ground Range Detected (GRDH) imagery with a spatial resolution of 10 meters. Images from periods with and without flood events between 2016 and 2017 were calibrated and co-registered. Subsequently on the images were applied threshold and time analysis techniques, as well as a Digital Elevation Model (DEM) analysis with data from stations which measure the rivers’ water levels. The validation of all methods was totally remote, based on a flood mapping of April 2003 in the city of Santa Fe. In addition, published images of flood events complemented the validation and it was possible to compare the results with an optical image Landsat - 8 with 15 m resolution of February 22, 2016, when the level of the Paraná River was above the alert level The three maps were summed to form a single image with the flood spot in common. Among the best accuracy, the MDE analysis method achieved the best result, 82% of the flood area, however, considering all three methods, the accuracy reaches more than 91% accuracy. The thresholding technique was more efficient in areas with no vertical targets, such as urban areas. The DEM was efficient to simulate flooding on all targets, however using elevation models with better resolution, the final result of the mapping will be more accurate. The temporal analysis showed to be a promising technique for flood mapping, however a detailed map of land use is fundamental to improve the results of this analysis. All processes were done remotely, allowing the future development of an automatic flood event detection system that can be applied in areas with similar characteristics.

Submitted by Rafaela Soares Niemann (rafaelaniemann@gmail.com) on 2018-01-30T19:22:21Z No. of bitstreams: 1 dissertacao_rafaela_soares_niemann.pdf: 20839099 bytes, checksum: 3e520cbdddb994f623e86eb596a2eeae (MD5) / Approved for entry into archive by Ana Paula Santulo Custódio de Medeiros null (asantulo@rc.unesp.br) on 2018-01-31T11:10:28Z (GMT) No. of bitstreams: 1 niemann_rs_me_rcla.pdf: 19917697 bytes, checksum: f24581bad9ffd4cf3c683c92a81563b2 (MD5) / Made available in DSpace on 2018-01-31T11:10:28Z (GMT). No. of bitstreams: 1 niemann_rs_me_rcla.pdf: 19917697 bytes, checksum: f24581bad9ffd4cf3c683c92a81563b2 (MD5) Previous issue date: 2017-12-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Os modelos digitais de elevação são importantes para a geração de informações sobre variáveis ambientais correlacionadas à topografia, principalmente como subsídio à análises geomorfométricas. O sensoriamento remoto pode contribuir com a geração de modelos digitais de elevação, principalmente através do uso de sensores de alta resolução espacial e tecnologias avançadas. Os VANTs – Veículos Aéreos Não Tripulados – tem sido cada vez mais explorados no âmbito da cartografia e topografia, com atuação cada vez mais importante dentro da ciência, devido à capacidade de transportarem diferentes sensores e ao seu baixo custo de operação. Câmeras fotográficas simples acopladas aos VANTs podem ser combinadas com tecnologias de visão computacional, trazendo novas oportunidades para explorar a geração de modelos digitais de elevação. Algoritmos de visão computacional, como o Structure-from-Motion (SfM), permitem a extração de pontos tridimensionais a partir de imagens sobrepostas obtidas por VANTs. Esses pontos compõem nuvens de pontos capazes de subsidiar a geração de modelos digitais de superfície (MDS), quando combinadas com algoritmos de interpolação de dados. Contudo, os modelos gerados desta maneira nos retornam informações relacionadas à superfície dos objetos presentes sobre o terreno, incluindo por exemplo construções e dosséis vegetais. A filtragem e classificação das nuvens de pontos se faz assim necessária para geração de modelos digitais que descrevam mais fielmente a superfície do terreno, sem estes elementos. Nesta dissertação, avaliamos dois métodos para a filtragem e interpolação de modelos digitais de terreno (MDT) a partir de nuvens de pontos geradas por imageamento ótico baseado em VANTs. A área de estudo escolhida foi a região da Serra do Cipó-MG, caracterizada por relevo acidentado e cobertura vegetal variada. O primeiro método consistiu na filtragem (classificação) direta da nuvem de pontos, e o segundo na filtragem do modelo digital de superfície em formato raster, ambos seguidos de interpolação. Os métodos avaliados se mostraram adequados, com coeficientes de determinação da ordem de R² = 0,98 em relação a dados de referência tomados por DGPS. A filtragem foi bastante eficiente para áreas íngremes e com vegetação baixa, e menos eficiente em áreas de vegetação arbórea densa. Os métodos avaliados no presente trabalho contribuirão para a melhoria da geração de MDTs com base na tecnologia emergente oferecida pelos VANTs, que poderão ser utilizados como subsídios a estudos ambientais diversos. / Digital elevation models are important for producing information on different environmental variables correlated to topography, especially for geomorphometric analyses. Remote sensing can contribute to the generation of digital elevation models, mainly through high spatial resolution sensors and advanced technologies. UAVs - Unmanned Aerial Vehicles - have been increasingly employed in the fields of cartography and topography, and have had an increasingly prominent role in science, as they can carry different sensors and have low-cost operation. Simple cameras attached to UAVs can be combined with computer vision technologies, bringing new opportunities to explore the production of digital elevation models. Computer vision algorithms such as Structure-from-Motion (SfM) allow the extraction of threedimensional points from superimposed images obtained by UAVs. These points make up points clouds capable of supporting the production of digital surface models (DSM) when combined with interpolation algorithms. However, models generated this way give us information related to the surface of objects present on the ground, including buildings and plant canopies. Point cloud filtering and classification is thus necessary for producing digital models that more accurately describe the bare terrain surface. In this dissertation, we evaluated two methods for filtering and interpolating digital terrain models (DTM) from point clouds generated by UAVbased optical imaging. The chosen study area was the Serra do Cipó region (Minas Gerais, Brazil), characterized by rugged relief and heterogeneous vegetation cover. The first method consisted of direct filtering (classification) of the point cloud, and the second method was based on filtering the digital surface model in raster format, both followed by interpolation. The evaluated methods were adequate, with determination coefficients of the order of R² = 0.98 in relation to reference data taken by DGPS. Filtering was quite efficient for steep areas with low vegetation, and less efficient in areas of dense arboreal vegetation. The methods evaluated in the present work will contribute to the improvement and generation of DTMs based on the emerging technology offered by UAVs, which can be used as subsidies to diverse environmental studies.

Nesse estudo foram mapeadas e mensuradas as variações de área, elevação mínima e orientação das geleiras da Colômbia e da Venezuela (trópicos internos), entre os anos 1985-2015. Para o mapeamento das áreas das geleiras foram utilizadas como base imagens Landsat, sensores TM, ETM+ e OLI. Às imagens selecionadas foi aplicado o Normalized Difference Snow Index (NDSI), no qual são utilizadas duas bandas em que o alvo apresenta comportamento espectral oposto ou com características bem distintas: bandas 2 e 5 dos sensores TM e ETM+ e bandas 3 e 6 do sensor OLI. Os dados de elevação e orientação das massas de gelo foram obtidos a partir do Modelo Digital de Elevação SRTM (Shuttle Radar Topography Mission – v03). Em 1985, a soma das áreas das sete geleiras estudadas correspondia a 92,84 km², enquanto no último ano estudado (2015/2016) esse valor passou para 36,97 km². A redução de área ocorreu em todas as geleiras analisadas, com taxas de retração anual variando entre 2,49% a.a. e 8,46% a.a. Houve retração das áreas de gelo localizadas em todos os pontos cardeais considerados, bem como, elevação da altitude nas frentes de geleiras. Além da perda de área ocorrida nas menores altitudes, onde a taxa de ablação é mais elevada, também se observou retração em alguns topos, evidenciado pela ocorrência de altitudes menores nos anos finais do estudo, em comparação com os anos iniciais. Como parte das geleiras colombianas está localizada sobre vulcões ativos, essas áreas sofrem influência tanto de fatores externos, quanto de fatores internos, podendo ocorrer perdas de massa acentuadas causadas por erupção e/ou terremoto. / In this study, glaciers located in Colombia and Venezuela (inner tropics) were mapped between 1985-2015. The area of these glaciers was measured and the variations that occurred in each glacier were compared to identify whether the glacier was growing or shrinking. The minimum elevation of the glaciers fronts and the aspect of the glaciers were analyzed. The glaciers areas ware obtained by the use of Landsat images, TM, ETM+ and OLI sensors. The Normalized Difference Snow Index (NDSI) was applied to the selected images, in which two bands were used, where the ice mass has opposite (or very different) spectral behavior: bands 2 and 5 from sensors TM and ETM+, and bands 3 and 6 from sensors OLI. The elevation and the aspect data of the glaciers were obtained from SRTM (Shuttle Radar Topography Mission – v03) Digital Elevation Model. In 1985/1986, the sum of the areas of the seven studied glaciers corresponded to 92.84 km², while in the last year analyzed (2015/2016), this value shrank to 36.97 km². The area shrinkage occurred in all the glaciers that were mapped, with annual decline rates ranging from 2.49%/year to 8.46%/year. It is also possible to observe a decrease of the ice covered in all aspects considered, as well as an elevation in all glaciers fronts. In addition to the area loss occurred at lower altitudes, where the ablation rate is higher than in higher altitudes, shrinkage in some mountain tops was also present, which is evidenced by the occurrence of lower maximum elevations in the final years of the study, when compared with the initial years. Considering that part of the Colombian’s glaciers are located on active volcanoes, these areas are influenced by external and internal factors, and the occurrence of volcanic eruption and/or earthquake can cause sharp mass losses.

Eventos de inundação são fenômenos geralmente associados a eventos de chuvas intensas. Nesses eventos a cobertura de nuvens, normalmente, prejudica o mapeamento com uso de imagens ópticas. Assim, este trabalho tem como objetivo avaliar os resultados de mapeamento de áreas de inundação utilizando imagens SAR e SRTM. Para aplicação dos métodos foram analisadas as áreas de inundação nas cidades de Santa Fe e Parana, na Argentina. Embora a maior inundação registrada tenha sido no ano de 2003, registros de inundação são frequentemente observados nas províncias de Santa Fé e Entre Ríos. Foi utilizado imagens do satélite Sentinel-1, equipado com sensor C-SAR com dupla polarização (VV/VH). As imagens obtidas são do tipo Interferométrico (IW) Ground Range Detected (GRDH) com resolução espacial de 10 m. Foram utilizadas imagens em períodos com e sem eventos de inundação entre 2016 e 2017, calibradas e coregistradas. Sobre as imagens foram aplicadas técnicas de limiarização e de análise temporal para mapear a mancha de inundação. Também foi elaborado mapa a partir do Modelo Digital de Elevação (MDE) utilizando como referência estações de medição de nível da água dos rios. A validação de todos os métodos foi totalmente remota, baseando-se em um mapeamento da inundação de abril de 2003 na cidade de Santa Fe. Além disso, imagens publicadas de eventos de inundação complementaram a validação e foi possível comparar os resultados com uma imagem óptica Landsat – 8 com resolução de 15 m do dia 22 de fevereiro de 2016, quando o nível do rio Paraná estava acima do nível de alerta Os resultados dos três mapeamentos foram somados para formar uma única imagem com a mancha de inundação em comum. Entre as melhores acurácias, o método de análise do MDE atingiu o melhor resultado, 82% da área de inundação, no entanto, considerando os três métodos, a acurácia atinge mais de 91% de precisão. A técnica de limiarização foi mais eficiente em áreas sem alvos verticais, como áreas urbanas por exemplo. O MDE foi eficiente para simular a inundação em todos os alvos, no entanto em modelos de elevação com melhor resolução, o resultado final do mapeamento será mais preciso. A análise temporal mostrou ser uma técnica promissora para mapeamentos de inundação, no entanto um mapa detalhado de uso de solo é fundamental para aprimorar o resultado desta análise. Todos os processos foram feitos remotamente, possibilitando o desenvolvimento no futuro de um sistema automático para detecção de evento de inundação que pode ser aplicado em áreas com características similares. / Flood events usually go hand in hand with intensive rainfall during which clouds compromise any mapping attempts with optical imagery. Thus, this thesis aims at evaluate the results of mapping flood areas using SAR and SRTM images. For this purpose, flood areas in the cities Santa Fe and Parana in Argentina were analyzed. While the worst flood was registered in 2003, flood events frequently occur in both provinces Santa Fé and Entre Ríos. The employed Sentinel-1 satellite carrying a C-SAR sensor with dual polarization (VV/VH) provided interferometric (IW) Ground Range Detected (GRDH) imagery with a spatial resolution of 10 meters. Images from periods with and without flood events between 2016 and 2017 were calibrated and co-registered. Subsequently on the images were applied threshold and time analysis techniques, as well as a Digital Elevation Model (DEM) analysis with data from stations which measure the rivers’ water levels. The validation of all methods was totally remote, based on a flood mapping of April 2003 in the city of Santa Fe. In addition, published images of flood events complemented the validation and it was possible to compare the results with an optical image Landsat - 8 with 15 m resolution of February 22, 2016, when the level of the Paraná River was above the alert level The three maps were summed to form a single image with the flood spot in common. Among the best accuracy, the MDE analysis method achieved the best result, 82% of the flood area, however, considering all three methods, the accuracy reaches more than 91% accuracy. The thresholding technique was more efficient in areas with no vertical targets, such as urban areas. The DEM was efficient to simulate flooding on all targets, however using elevation models with better resolution, the final result of the mapping will be more accurate. The temporal analysis showed to be a promising technique for flood mapping, however a detailed map of land use is fundamental to improve the results of this analysis. All processes were done remotely, allowing the future development of an automatic flood event detection system that can be applied in areas with similar characteristics.

M. Ing. / Digital Surface Models (DSM) are widely used in the earth sciences for research, visu- alizations, construction etc. In order to generate a DSM for a speci c area, specialized equipment and personnel are always required which leads to a costly and time consuming exercise. Image processing has become a viable processing technique to generate terrain models since the improvements of hardware provided adequate processing power to complete such a task. Digital Surface Models (DSM) can be generated from stereo imagery, usually obtained from a remote sensing platform. The core component of a DSM generating system is the image matching algorithm. Even though there are a variety of algorithms to date which can generate DSMs, it is a computationally complex calculation and does tend to take some time to complete. In order to achieve faster DSMs, an investigation into an alternative processing platform for the generation of terrain models has been done. The Graphics Processing Unit (GPU) is usually used in the gaming industry to manipulate display data and then render it to a computer screen. The architecture is designed to manipulate large amounts of oating point data. The scientic community has begun using the GPU processing power available for technical computing, hence the term, General Purpose computing on a Graphics Processing Unit (GPGPU). The GPU is investigated as alternative processing platform for the image matching procedure since the processing capability of the GPU is so much higher than the CPU but only for a conditioned set of input data. A matching algorithm, derived from the GC3 algorithm has been implemented on both a CPU platform and a GPU platform in order to investigate the viability of a GPU processing alternative. The algorithm makes use of a Normalized Cross Correlation similarity measurement and the geometry of the image acquisition contained in the sensor model to obtain conjugate point matches in the two source images. The results of the investigation indicated an improvement of up to 70% on the processing time required to generate a DSM. The improvements varied from 70% to some cases where the GPU has taken longer to generate the DSM. The accuracy of the automatic DSM generating system could not be clearly determined since only poor quality reference data was available. It is however shown the DSMs generated using both the CPU and GPU platforms relate to the reference data and correlate to each other. The discrepancies between the CPU and the GPU results are low enough to prove the GPU processing is bene cial with neglible drawbacks in terms of accuracy. The GPU will definitely provide superior processing capabilites for DSM generation above a CPU implementation if a matching algorithm is speci cally designed to cater for the bene ts and limitations of the GPU.

M.Sc. / Light Detection and Ranging (LiDAR) provide decidedly accurate datasets with high data densities, in a very short time-span. However, the high volumes of data associated with LiDAR often require some form of data reduction to increase the data handling efficiency of these datasets, of which the latter could affect the feasibility of Digital Elevation Models (DEMs). Critically, when DEM processing times are reduced, the resultant DEM should still represent the terrain adequately. This study investigated three different data reduction techniques, (1) random point reduction, (2) grid resolution reduction, and (3) combined data reduction, in order to assess their effects on the accuracy, as well as the data handling efficiency of derived DEMs. A series of point densities of 1 %, 10 %, 25 %, 50 % and 75 % were interpolated along a range of horizontal grid resolutions (1-, 2-, 3-, 4-, 5-, 10- and 30- m). Results show that, irrespective of terrain complexity, data points can be randomly reduced up to 25 % of the data points in the original dataset, with minimal effects on the remaining dataset. However, when these datasets are interpolated, data points can only be reduced to 50 % of the original data points, before showing large deviations from the original DEM. A reduction of the grid resolution of DEMs showed that the grid resolution could be lowered to 4 metres before showing significant deviations. When combining point density reduction with grid resolution reduction, results indicate that DEMs can be derived from 75 % of the data points, at a grid resolution of 3 metres, without sacrificing more than 15 percent of the accuracy of the original DEM. Ultimately, data reduction should result in accurate DEMs that reduce the processing time. When considering the effect on the accuracy, as well as the processing times of the data reduction techniques, results indicate that resolution reduction is the most effective data reduction technique. When reducing the grid resolution to 4 metres, data handling efficiencies improved by 94 %, while only sacrificing 10 % of the data accuracy. Furthermore, this study investigated data reduction on a variety of terrain complexities and found that the reduction thresholds established by this study were applicable to both complex and non-complex terrain.

Conducting single frame orthorectification on satellite images to create an ortho-image requires four basic components, namely an image, a geometric sensor model, elevation data (for example a digital elevation model (DEM)) and ground control points (GCPs). For this study, orthorectification was executed numerous times (in three stages) and each time components were altered to test the geometric accuracy of the resulting ortho-image. Most notably, the distribution and number of ground control points, the quality of the elevation source and the geometric sensor model or lack thereof were altered. Results were analysed through triangulating and comparing the geolocation accuracy of the ortho-images. The application of these different methods to perform orthorectification encompass the aim of this paper, which was to investigate and compare the positional accuracies of ortho-images under various orthorectification scenarios and provide improved geometric accuracies of VHR satellite imagery when diverse ground control and elevation data sources are available. By investigating the influence that the distribution and number of GCPs and the quality of DEMs have on the positional accuracy of an ortho-image, it became clear that a reasonable increase in the number of uniformly distributed GCPs combined with progressively accurate DEMs will ultimately improve the quality of the orthorectified product. The results also showed that when more GCPs were applied, the smaller the difference in accuracy was between the different DEMs utilised. It was interesting to note that when it is suitable to manually collect well-distributed GCPs using a GPS handheld device over the study area then a very accurate result can be expected. Nonetheless, it is also important to note that if it is not possible/practical to achieve the latter, satellite based GCP collection do provide a very good alternative. It was also determined that utilising GCPs which were extracted from vector road layers to only cover specific areas in the image scene produced less favourable results. Several contributions towards improved orthorectification procedures were made in this study. These include the development of an automatic GCP extraction script (A-GCP-ES), written in the Python scripting language with the purpose to ease the process of manually placing GCPs on an input image when repeatedly performing orthorectification. / Thesis (PhD)--University of Pretoria, 2016. / Geography, Geoinformatics and Meteorology / PhD / Unrestricted

No description available.

<p>Digital elevation models (DEM) can be used for a multitude of applications. Under ideal circumstances, calibration of a remotely acquired estimate of topographic elevation is calibrated through use of ground control points (GCP) which would be ubiquitous, seamlessly joining remotely sensed data and high accuracy check points. In reality there are many areas on the earth’s surface which are difficult, expensive, or dangerous to access. Under these circumstances, the acquisition of GCPs may not be realistic and relative DEMs must be used. Innovative methods must then be used to determine the relative error associated with a DEM in a given study area. The method presented in this paper compares three DEMs (ASTER, CDED, SRTM) derived from independent acquisition systems to determine their relative errors.</p> <p>The ASTER DEM data was chosen for a lineament analysis study in north central Ontario, Canada. This study used a quantitative digital approach to determine the density of lineaments mimicking the geometry of the northern Sudbury Igneous Complex contact (SIC). The study revealed a lineament density at ~25km north of the northern SIC contact, suggesting a ring structure from an ancient multi-ring impact basin. This argument is supported by findings of the pattern of plagioclase clouding intensities in Matachewan dykes in the vicinity of the ring structure. The orientation of the dykes may have some connection to the faulting and block rotation caused by crater wall collapse.</p> <p>Paleomagnetic data from the norite in the SIC and Foy Offset dyke combined with an unconstrained magnetic inversion of the Foy Offset dyke suggest that the Sudbury Structure has not been folded, but instead has been deformed by brittle deformation.</p> / Master of Science (MSc)

The braided rivers and floodplains in the Upper Waitaki Basin (UWB) of the South Island of New Zealand are critical habitats for endangered and threatened fauna such as the black stilt. However, this habitat has degraded due to introduced predators, hydropower operations, and invasive weeds including Russell lupins. While conservation efforts have been made to restore these habitats, flood events may provide a natural mechanism for removal of invasive vegetation and re-creation of natural floodplain habitats. However, little is understood about the hydraulic effects of floods on vegetation and potential mortality in these dynamic systems. Therefore, this thesis analyzed the flood-induced processes that cause lupin mortality in a reach of the Ahuriri River in the UWB, and simulated various sized flood events to assess how and where these processes occurred. To determine the processes that cause lupin mortality, post-flood observations were utilized to develop the hypothesis that flood-induced drag, erosion, sediment deposition, inundation, and trauma were responsible. Field and laboratory experiments were conducted to evaluate and quantify these individual processes, and results showed that drag, erosion, sediment deposition and inundation could cause lupin mortality. Utilizing these mortality processes, mortality thresholds of velocity, water depth, inundation duration, and morphologic changes were estimated through data analysis and evaluation of various empirical relationships. Delft3D was the numerical model used to simulate 2-dimensional flood hydraulics in the study-reach and was calibrated in three stages for hydraulics, vegetation, and morphology. Hydraulic calibration was achieved using the study-reach topography captured by Structure-from-Motion (SfM) and various hydraulic data (depth, velocity, and water extent from aerial photographs). Vegetation inclusion in Delft3D was possible utilizing a function called ‘trachytopes’, which represented vegetation roughness and flow resistance and was calibrated utilizing data from a lupin-altered flow conveyance experiment. Morphologic calibration was achieved by simulating an observed near-mean annual flood event (209 m3 s-1) and adjusting the model parameters until the simulated morphologic changes best represented the observed morphologic changes captured by pre- and post-flood SfM digital elevation models. Calibration results showed that hydraulics were well represented, vegetation inclusion often improved the simulated water inundation extent accuracy at high flows, but that local erosion and sediment deposition were difficult to replicate. Simulation of morphological change was expected to be limited due to simplistic bank erosion prediction methods. Nevertheless, the model was considered adequate since simulated total bank erosion was comparable to that observed and realistic river characteristics (riffles, pools, and channel width) were produced. Flood events ranging from the 2- to 500-year flood were simulated with the calibrated model, and lupin mortality was estimated using simulation results with the lupin mortality thresholds. Results showed that various degrees of lupin mortality occurred for the different flood events, but that the dominant mortality processes fluctuated between erosion, drag, and inundation. Sediment deposition-induced mortality was minimal, but was likely under-represented in the modeling due to poor model sediment deposition replication and possibly over-restrictive deposition mortality thresholds. The research presented in this thesis provided greater understanding of how natural flood events restore and preserve the floodplain habitats of the UWB and can be used to aid current and future braided river conservation and restoration efforts.