The Darwin-Hatherton glacial system is an outlet glacial system in the Transantarctic Mountains, Antarctica, which drains ice from the East Antarctic Ice Sheet into the Ross Ice Shelf. This research provides remotely sensed data that can be used in modeling research for the Darwin-Hatherton glacial system, which in turn can be used in mass balance research for the West Antarctic Ice Sheet. Two improved digital elevation models (DEM) are produced to cover the lower Darwin Glacier and to cover the upper Darwin and Hatherton Glaciers. The new improved DEMs are generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data, with a resolution of 45 m. To produce the two final DEMs, multiple DEMs are firstly adjusted to remove systematic errors and are then stacked and averaged to increase the accuracy and produce the final two DEMs. For the lower Darwin Glacier, 5 DEMs were averaged and in the upper Darwin and Hatherton Glaciers, 6 DEMs were averaged. The accuracy is quantified by a remaining error of + 9 m for the lower Darwin Glacier DEM and + 37 m for the upper Darwin and Hatherton Glaciers DEM. This is a significant improvement from the existing 200 m resolution Radarsat Antarctic mapping project (RAMPv2) DEM which has a remaining error of + 138 m over the lower Darwin Glacier and + 152 m over the upper Darwin and Hatherton Glaciers. The accuracy is assessed by comparing the ASTER and RAMPv2 DEMs to highly accurate ice, cloud and land elevation satellite (ICESat) laser altimetry data. A 15 m resolution, true colour, orthorectified image is provided for the entire Darwin-Hatherton glacial system from ASTER satellite imagery. The DEMs used to orthorectify the ASTER satellite imagery are the two new 45 m resolution ASTER DEMs. Lastly feature tracking was explored as a method for measuring surface ice velocity. This research shows that feature tracking is unsuitable for the Darwin-Hatherton glacial system if using 15 m resolution satellite imagery over a 1 to 4 year time period.

Mountain glaciers are expected to be the greatest contributor to sea level rise over the next century. Glaciers provide a good indicator of global climate and how to monitor their change is an increasingly important issue for climate science and for sea level rise forecasts. However, there has been little direct measurement of glacier volume change in New Zealand. This study explores the use of remotely sensed data for measuring glacier volume change from 1965 to 2006. Digital photogrammetric methods were used to extract topographic data of the Tasman Glacier from aerial photography and ASTER imagery for the years 1965, 1986, 2002 and 2006. SRTM C band data from 2000 were also analysed. Data were compared to an existing digital elvation model produced from the New Zealand Digital Topographic Database to test for their reliability. Using regression analysis, the data were filtered and points representing rock were used to correct points on the glacier ice for vertical bias. The quality of the data extracted from the aerial photography was good on rock and debris covered ice, but poor on snow. The data extracted from ASTER was much more reliable on snow in the upper glacier than the aerial photography, but was very poor in the lower debris covered region of the glacier. While the quality of the SRTM data is very high, there is a second order distortion present in the data that is evident over elevation differences. However, the overall mean difference of the SRTM rock from TOPODATA is close to zero. An overall trend could be seen in the data between dates. However, the 2006 ASTER data proved unreliable on the debris covered section of the glacier. Total volume change is therefore calculated for the period between 1965 and 2002. The data show a loss of 3:4km³ or 0:092km³ per year, an estimated 6% of the total ice in New Zealand. This is compared to estimates using the annual end of summer snowline survey between 1977 and 2005 of 1:78 km³, or 0:064km³ per year. The spatial resolution of ASTER makes high temporal resolution monitoring of volume change unlikely for the New Zealand glaciers. The infrequency of aerial photography, the high cost and vast time involved in extracting good quality elevation data from aerial photography makes it impractical for monitoring glacier volume change remotely. However, SRTM and other radar sensors may provide a better solution, as the data do not rely heavily on user processing.

As part of a collaborative project at a stream segment reach on Proctor Creek in Atlanta, GA, UAV-based SfM photogrammetry was tested as a method for collecting fluvial topographic data relative to traditional USGS total station surveying methods. According to the USGS method, 11 transects were surveyed, and imagery was collected via a UAV to create a SfM DEM. The resulting DEM was incomplete but showed promise for the SfM method. Two additional stream segments were chosen in the Atlanta area, the first along SFPC in DHCL and the second along NFPC near Buford Hwy. For each site 11 transects were surveyed along with submerged GCPs so that the SfM DEMs could be compared to the surveyed data. The BW and BD values were collected from the TS transects and the DEM transects and compared according to the percent difference between the two. For SFPC, the average percent difference values for BW and BD were, respectively, 15.9 and 26.0 with standard deviations of 15.7 and 18.0. For NFPC, the BW and BD average percent difference values were 6.8 and 7.5 with standard deviations of 3.9 and 5.9. The GCPs were also compared for each site using linear regressions. There was no strong correlation for SFPC (R2 = 0.31 and p-value > 0.05), but there was a strong relationship indicated for NFPC (R2 = 0.78 and p-value < 0.05). While the results of this study are variable, the results do indicate promise for future work on this emerging method.

O presente trabalho avaliou a utilização de imagens ASTER GDEM e SRTM em substituição a cartas planialtmétricas em escala 1:10000 e 1:50000 como fonte de dados altimétricos para predição de perda de solo em microbacia hidrográfica. Para tanto as imagens com os dados de topografia e demais informações foram incorporadas ao banco de dados do SPRING. Como requisito para estimar perda de solo pela Equação Universal da Perda de Solo, estabeleceu-se o uso atual da terra na microbacia hidrográfica do Ceveiro, situada no município de Piracicaba, SP. Foi constatado que a microbacia é utilizada em sua maior parte pela lavoura de canade- açúcar e verificou-se ainda que as áreas de preservação permanente não estão em conformidade com a lei vigente. Atualmente ocupam uma área de 196,38 hectares e se fossem restituídas passariam a ocupar 255,16 hectares a mais, perfazendo um total de 451,54 hectares.O modelo ASTER GDEM foi o que apresentou melhor concordância nas estimativas de perda de solo com os modelos de referência 1:10000 e 1:50000, segundo o valor do índice Kappa que foi de 0,32 e 0,28 respectivamente, entretanto os modelos de elevação obtidos por sensoriamento remoto, quando analisados pela exatidão do produtor e exatidão do usuário encontraram resultados discrepantes de perda de solo para a microbacia hidrográfica quando comparados aos modelos de referência / The present study assessed the use of the terrain elevation models ASTER GDEM and SRTM in replacement of the topographic charts on 1:10000 and 1:150000 scales, as data for predicting soil loss on small watershed basin. All the altimetry data and further information were incorporated to the GIS/SPRING. For estimating the soil erosion it was necessary to establish the actual land use for the Ceveiro Watershed basin, situated at Piracicaba, São Paulo State, Brazil and it was noted that most of the land use is for the sugar cane crop and also was observed that most of the preservation area establish by law is not present at the area. If those preservation areas were recomposed it should use 451,54 hectares against the 196,38 present nowadays. The terrain elevation model ASTER GDEM was the one that most agreed with the reference data for predicting soil loss, respectively Kappa index of 0,32 and 0,28 for the reference data 1:10000 and 1:50000. Nevertheless the users accuracy and producers accuracy showed that the results are discrepant when they are compared with the reference data.

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.

There is overwhelming scientific evidence that shows the temperature of the Earth's atmosphere is rising at an unprecedented rate. This is attributed to increased levels of greenhouse gas emissions, a large proportion of which originates from anthropogenic combustion of carbon-based fossil fuels for energy. There is therefore a strong argument for the increased role of less environmentally damaging, low carbon energy sources including renewable energy technologies. Run-of-river hydropower is one such renewable energy option, considered more environmentally benign than traditional hydropower which requires the construction of large dams to create a reservoir. The aim of this study was to develop a model to search for, and map, economically viable run-of-river hydropower resource that can function on any global catchment of any size. Development and testing of the model was conducted on China's 2 million km2 Yangtze River drainage basin, the third longest river in the world and a rich landscape for hydropower. A gridded, distributed hydrological model was developed integrating high-resolution meteorological datasets and a digital elevation model (DEM). Using the model, the surface hydrology of the Yangtze catchment was simulated at a timestep of 6 minutes to obtain the mean daily surface runoff for every day from the beginning of 1979 to the end of 2007. Observed river flow data from sub-catchments of the Yangtze were used to calibrate the model by differential optimisation, an evolutionary computation technique. Validation was carried out on a 1.6 million km2 sub-catchment resulting in a mean objective function of 0.95 (where a perfect fit would be 1.0) across 8 objective functions commonly used in hydrology. Catchment wide mean daily runoff data was used to develop flow duration curves across the catchment river network. Virtual power stations were constructed at each river cell, iteratively testing differing scheme configurations, and costed using the RETScreen methodology. A best performing hydropower network was determined by a conflict algorithm, designed to prioritise high profit schemes and to remove lower performing and conflicting schemes. This resulted in a potential run-of-river installed capacity across the Yangtze catchment of 103GW (at 10% discount rate), generating 394TWh per annum. This model would be a valuable tool in finding optimal locations for future hydropower resource.

O presente trabalho avaliou a utilização de imagens ASTER GDEM e SRTM em substituição a cartas planialtmétricas em escala 1:10000 e 1:50000 como fonte de dados altimétricos para predição de perda de solo em microbacia hidrográfica. Para tanto as imagens com os dados de topografia e demais informações foram incorporadas ao banco de dados do SPRING. Como requisito para estimar perda de solo pela Equação Universal da Perda de Solo, estabeleceu-se o uso atual da terra na microbacia hidrográfica do Ceveiro, situada no município de Piracicaba, SP. Foi constatado que a microbacia é utilizada em sua maior parte pela lavoura de canade- açúcar e verificou-se ainda que as áreas de preservação permanente não estão em conformidade com a lei vigente. Atualmente ocupam uma área de 196,38 hectares e se fossem restituídas passariam a ocupar 255,16 hectares a mais, perfazendo um total de 451,54 hectares.O modelo ASTER GDEM foi o que apresentou melhor concordância nas estimativas de perda de solo com os modelos de referência 1:10000 e 1:50000, segundo o valor do índice Kappa que foi de 0,32 e 0,28 respectivamente, entretanto os modelos de elevação obtidos por sensoriamento remoto, quando analisados pela exatidão do produtor e exatidão do usuário encontraram resultados discrepantes de perda de solo para a microbacia hidrográfica quando comparados aos modelos de referência / The present study assessed the use of the terrain elevation models ASTER GDEM and SRTM in replacement of the topographic charts on 1:10000 and 1:150000 scales, as data for predicting soil loss on small watershed basin. All the altimetry data and further information were incorporated to the GIS/SPRING. For estimating the soil erosion it was necessary to establish the actual land use for the Ceveiro Watershed basin, situated at Piracicaba, São Paulo State, Brazil and it was noted that most of the land use is for the sugar cane crop and also was observed that most of the preservation area establish by law is not present at the area. If those preservation areas were recomposed it should use 451,54 hectares against the 196,38 present nowadays. The terrain elevation model ASTER GDEM was the one that most agreed with the reference data for predicting soil loss, respectively Kappa index of 0,32 and 0,28 for the reference data 1:10000 and 1:50000. Nevertheless the users accuracy and producers accuracy showed that the results are discrepant when they are compared with the reference data.

Analysis of digital elevation models (DEMs) by means of geomorphometry provides means of recognising fractures and characterising the morphotectonics of an area in a quantitative way. The objective of the thesis is to develop numerical methods and a consistent GIS methodology for tectonic geomorphology and apply it to test sites. Based on the study of landforms related to faults, geomorphological characteristics are translated into mathematical and numerical algorithms. The methodology is based on general geomorphometry. In this study, the basic geometric attributes (elevation, slope, aspect and curvatures) are complemented with the automatic extraction of ridge and valley lines and surface specific points. Evan’s univariate and bivariate methodology of general geomorphometry is extended with texture (spatial) analysis methods such as trend, autocorrelation, spectral, wavelet and network analysis. Digital terrain modelling is carried out by means of (1) general geomorphometry, (2) digital drainage network analysis, (3) digital image processing, (4) lineament extraction and analysis, (5) spatial and statistical analysis and (6) DEM specific digital methods such as shaded relief models, digital cross-sections and 3D surface modelling. Geological data of various sources and scales are integrated in a GIS database. Interpretation of multi-source information confirmed the findings of digital morphotectonic investigation. A simple shear model with principal displacement zone in the NE-SW direction can explain most of the morphotectonic features associated with structures identified by geological and digital morphotectonic investigations in the Kali Basin. Comparison of the results of the DTA with the known geology from NW Greece indicated that the major faults correspond to clear lineaments. Thus, DTA of an area in the proposed way forms a useful tool to identify major and minor structures covering large areas. In this thesis, numerical methods for drainage network extraction and aspect analysis have been developed and applied to tectonic geomorphology.

The Prairie Pothole Region (PPR) of North American contains millions of wetlands in shallow depressions that provide important hydrological and ecological functions. To assess and model these functions it is important to have accurate methods to quantify wetland water volume storage. Hayashi and van der Kamp (2000) developed equations suitable for calculating water volume in natural, regularly shaped wetlands when two coefficients are known. This thesis tested the robustness of their full and simplified volume (V) area (A) depth (h) methods to accurately estimate volume for the range of wetland shapes occurring across the PPR. Further, a digital elevation model (DEM) derived from light detection and ranging (LiDAR) data was used to extract the necessary data for applying the simplified V-A-h method at a broad spatial scale. Detailed topographic data were collected for 27 wetlands in the Smith Creek Research Basin and St. Denis National Wildlife Area, Saskatchewan that ranged in surface area shape. The full V-A-h method was found to accurately estimate volume (errors <5%) across wetlands of various shapes and is therefore suitable for calculating water storage in the variety of wetland shapes found in the PPR. Analysis of the simplified V-A-h method showed that the depression (p) and size (s) coefficients are sensitive to the timing of area and depth measurements and the accuracy of area measurements. Surface area and depth should be measured concurrently at two points in time to achieve volume errors <10%. For most wetlands this means measuring area and depth in spring when water levels are approximately 70% of hmax, and also in late summer prior to water depths dropping below 0.1 m. The wetted perimeter of the deepest water level must also be measured accurately to have volume errors less than 10%. Applying the simplified V-A-h method to a LiDAR DEM required GIS analysis to extract elevation contours that represent potential water surfaces. From these data the total wetland depth and s coefficient were estimated. Volume estimates through this LiDAR V-A-h method outperformed estimates from two volume-area equations commonly used in the PPR. Furthermore, the process to extract the wetland coefficients from the LiDAR DEM was automated such that storage could be estimated for the entire St. Denis National Wildlife Area. Applying the simplified V-A-h method according to the guidelines and data sources recommended here will allow for more accurate, time-effective water storage estimates at multiple spatial scales, thereby facilitating evaluation and modelling of hydrological and ecological functions.