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.

There is an increasing need for three-dimensional description for various applications such as the development of catchment areas, forest fire control and restoration. Three-dimensional information plays an indispensable role; therefore acquisition of the digital elevation models (DEMs) is the first step in these applications. LiDAR is a recent development in remote sensing with great potential for providing high resolution and accurate three-dimensional point clouds for describing terrain surface. The acquired LiDAR data represents the surface where the laser pulse is reflected from the height of the terrain and object above ground. These objects should be removed to derive the DEMs. Many LiDAR data-filtering studies are based on surface, block, and slope algorithms. These methods have been developed to filter out most features above the terrain; however, in certain situations they have proved unsatisfactory. The different algorithm based on different point of view to describe the terrain surface. The appropriate adoption of the advantages from these algorithms will develop a more complete way to derive DEMs. Knowledge-based system is developed to solve some specific problems according to the given appropriate domain knowledge. Huang (2007) proposed a Knowledge-based classification system in urban feature classification using LiDAR data and high resolution aerial imagery with 93% classification accuracy. This research proposed a knowledge-based LiDAR filtering (KBLF) as a follow-up study of Huang¡¦s study. KBLF integrates various knowledge rules derived from experts in the area of ground feature extraction using LiDAR data to increase the capability of describing terrain and ground feature classification. The filtering capability of KBLF is enhanced as expected to get better quality of referenced ground points to recover terrain height and DEMs using Inverse Distance Weighting (IDW) and Nearest Neighbor (NN) methods.

In this study, DEMs and orthoimages were generated from ASTER imagery and their accuracies were assessed. The study site covers an area of approximately 60 x 60 km and encloses the city of Ankara. First, DEMs were generated from stereo ASTER images. In order to find the best GCP combination, different number of GCPs (8, 16, 24, and 32) was used. The accuracies of the generated DEMs were then assessed based on the check points (CP), slopes and land cover types. It was found that 16 GCPs were good compromise to produce the most accurate DEM. The post processing and blunder removal increased the overall accuracy up to 38%. It was also found that there is a strong linear relationship between the accuracies of DEMs and the slopes of the terrain. The accuracies computed for water, urban, forest, mountainous, and other areas were found to be 5.01 m, 8.03 m, 12.69 m, 17.14 m, and 10.21 m, respectively. The overall accuracy was computed as 10.92 m. The orthorectification of the ASTER image was carried out using 12 different mathematical models. Based on the results, the models First Order 2D Polynomial, Direct Linear Transformation and First Order Polynomial with Relief have produced the worst results. On the other hand, the model Second Order Rational Function appears to be the best model to orthorectify the ASTER images. However, the developed model Second Order Polynomial with Relief provides simplicity, consistency and requires less number of GCPs when compared to the model Second Order Rational Function.

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.

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.

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

This study demonstrates the value of historical aerial photographs as a source for monitoring long-term landslide evolution, which can be unlocked by using appropriate photogrammetric methods. The understanding of landslide mechanisms requires extensive data records; a literature review identified quantitative data on surface movements as a key element for their analysis. It is generally acknowledged that, owing to the flexibility and high degree of automation of modern digital photogrammetric techniques, it is possible to derive detailed quantitative data from aerial photographs. In spite of the relative ease of such techniques, there is only scarce research available on data quality that can be achieved using commonly available material, hence the motivation of this study. In two landslide case-studies (the Mam Tor and East Pentwyn landslides) the different types of products were explored, that can be derived from historical aerial photographs. These products comprised geomorphological maps, automatically derived elevation models (DEMs) and displacement vectors. They proved to be useful and sufficiently accurate for monitoring landslide evolution. Comparison with independent survey data showed good consistency, hence validating the techniques used. A wide range of imagery was used in terms of quality, media and format. Analysis of the combined datasets resulted in improvements to the stochastic model and establishment of a relationship between image ground resolution and data accuracy. Undetected systematic effects provided a limiting constraint to the accuracy of the derived data, but the datasets proved insufficient to quantify each factor individually. An important advancement in digital photogrammetry is image matching, which allows automation of various stages of the working chain. However, it appeared that the radiometric quality of historical images may not always assure good results, both for extracting DEMs and vectors using automatic methods. It can be concluded that the photographic archive can provide invaluable data for landslide studies, when modern photogrammetric techniques are being used. As ever, independent and appropriate checks should always be included in any photogrammetric design.

El objetivo general del trabajo es evaluar el comportamiento del modelo de elevaciones SRTM 90m DEM (Modelo Digital de Elevaciones de la Misión Topográfica de Radar del Transbordador) sobre una zona extendida y de topografía muy variada de la República Argentina e incorporar información local al mismo. La técnica de interferometría de radar se ha analizado y utilizado para explicar el comportamiento del modelo en algunos puntos singulares de la zona de aplicación de esta tesis. La zona de trabajo incluyó parte de las provincias de Buenos Aires, La Pampa, Mendoza, Río Negro y Neuquén. Como información de referencia terrestre, se utilizaron puntos pertenecientes a la Red altimétrica del IGN y a la Red POSGAR07. En particular la Red GEOBA98 y su densificación, con puntos altimétricos GPS sobre todo el territorio de la provincia de Buenos Aires, representó la información de referencia que permitió: generar el DEM mejorado, mediante la integración de sus puntos, y la evaluación de su precisión externa. El DEM mejorado (HSRTM DEMMEJ) obtenido en este trabajo, para la zona de estudio, representa un avance con respecto al modelo original SRTM 90m DEM v4.1 CGIAR-CSI. El modelo gravitacional terrestre EGM96 asociado al SRTM 90 m fue analizado y utilizado como indicador del comportamiento de las alturas elipsoidales del geoide en la zona de estudio. Este análisis permitió expresar el nuevo DEM mejorado en coordenadas elipsoidales para facilitar su aplicación en relación a las determinaciones GNSS e independizarlo del modelo geopotencial utilizado. Los nuevos modelos geopotenciales, como el EGM2008, han significado una sensible mejora en la representación del geoide en gran parte de nuestro país. Por ello, finalmente se obtiene un modelo de elevaciones cuyas alturas se encuentran referidas al modelo gravitacional terrestre EGM2008 (HSRTM Nuevo). Las mejoras obtenidas son estimadas poniendo en consideración las características topográficas de las regiones estudiadas. Este nuevo modelo proporciona precisiones de una decena de centímetros

Light Detection and Ranging (LIDAR) är en teknik för att samla in data om terräng. Genom att använda dessa data kan man skapa olika terrängmodeller. Denna studie syftar till att undersöka hur olika procentuella reduceringar av ursprungsdata påverkar kvalitén hos genererade höjdmodeller i form av Triangular Irregular Network (TIN). Detta görs genom att med hjälp av statistiska metoder göra jämförelser mellan punkter i den genererade TIN modellen och motsvarande punkter i det ursprungliga LIDAR punktmolnet. Studien visar att, beroende på noggrannhetskrav och topografi, en så liten andel som 5 % av punkterna kan vara tillräckligt, samt att noggrannhetsförbättring vid användning av mer än 50 % av ursprungsdata inte kan motivera den ökade arbetsbelastningen för datahantering.

Environmental concerns are becoming increasingly relevant during a period of hemorrhaging ecosystem goods and services. Restoring these would result in positive outcomes for public health and economic benefit. This thesis seeks to address two environmental concerns: (1) accurate soil mapping and (2) treatment of nitrogen to affect water quality change.The current method of soil mapping, SSURGO (USDA‐NRCS Soil survey), is often erroneous and misleading. Two studies in this dissertation are conducted to evaluate the potential that different resolution digital elevation models (DEMs) have to distribute soil characteristics successfully. These studies are conducted in southwest Virginia and western Vermont. The aforementioned studies evaluated 36 and 59 soil samples, respectively. Spatial characteristics, including slope, catchment area, and topographic wetness, are derived from several DEMs. In chapter 2, these characteristics are spatially compared, and we found that small resolution rasters result in narrow flow paths relative to coarser rasters. In chapter 3, we isolate the analysis to focus on resolution size, instead of a mix of both resolution size and generation method. This is done by recursively coarsening small rasters, deriving spatial attributes from said rasters and evaluating their potential to fit the soil characteristics of interest. Here we found that slopes generated from resolutions smaller than 11m were poor predictors of soil characteristics. Both chapters are finished by proposing and evaluating a soil map. Proposed regressions beat SSURGO in all investigated properties. Furthermore, proposed maps consistently beat out uninformed smallest resolution derived maps.Chesapeake bay water quality managers are struggling to achieve targets for nitrogen loading. This is in part due to the widespread presence of legacy nitrogen. Legacy nitrogen is an emerging issue, and springs exporting high levels of nitrogen are not uncommon in northern Virginia. This thesis explores, in part, a novel concept of treating large loads of nitrogen exported from a spring with a bioreactor. Bioreactors are a young science that most typically pair carbon heavy subterranean receptacles to agricultural drainage. This provides a location for nitrogen fixing bacteria to consume nitrate/nitrite, turning these into inert nitrogen gas. A spring fed bioreactor is studied for 10 months, and bioreactor conditions including influent and effluent nitrogen concentrations, bioreactor flow, and temperature are collected. A model driven by first order reaction equations is found to be most accurate with inputs of temperature and bioreactor age. The resulting marginal effects of these inputs were consistent with previously reported studies. / Doctor of Philosophy / Centuries of industrialization have resulted in widespread human progress but have, at times, adversely impacted the environment. Constituents rely heavily on environmental services, such as clean air and water, to subsist. Environmental degradation has resulted in detrimental effects to public health, and remediation is currently economically viable. As such, there are strong incentives for researchers to understand environmental processes at a fundamental level. One such process is soil characteristic distribution. The distribution of soil characteristics, such as soil texture or organic matter, is especially important for agriculturalists, hydrologists and geotechnicians. Soil texture and organic matter distribution can affect crop yield, nitrogen export to surface waters, and structural stability of soils. Thus, accurate characterization of measured soil properties is paramount to multiple fields. The most typically used soil map is USDA‐NRCS Soil survey (commonly referred to as SSURGO). Currently, the SSURGO database is a poor predictor of soil characteristics. There is an opportunity to improve soil characteristic distribution using digital elevation models (DEMs). As DEMs become cheaper to develop, they are typically available in multiple resolutions and generation methods. In this research, several DEMs are used to better soil maps for watersheds in Southwest Virginia and Western Vermont. Both studies showed that DEMs can better distribute soils when compared to the current SSURGO maps. Additionally, we showed that the finest resolution dataset was not always best, and mixed resolution topographic wetness indices to be most advantageous for distributing soils.Another such process is remediation of surface waters from high loads of nitrogen and phosphorus. The Haber-Bosch method of producing nitrogen fertilizer is one of the most important human innovations in recent history. This method is likely responsible for the aversion of widespread famine in the early 1900s. However, residents of multiple river systems, including the Chesapeake Bay and the Mississippi River, are suffering from the adverse effects of widespread hypoxic/anoxic (with little/no oxygen, respectively) zones within water. These have partially been responsible for the decline of commercial ventures such as fisheries and tourism. These zones are caused by eutrophication, a process of unsustainable plant growth in the presence of nitrogen and phosphorus. Water quality managers typically target agricultural runoff and point source polluters when trying to eliminate anthropogenic nitrogen. However, legacy nitrogen (nitrogen stored in groundwater in excess of a year) has become an emerging concern for water quality. It is not uncommon for springs in karst areas to be contaminated with high concentrations of nitrogen. These springs present a point source that can be treated by an emerging technology: bioreactors. Bioreactors are subterranean, woodchip filled basins that provide a location for microbes to exchange water soluble nitrogen for inert nitrogen gas. The consistency in nitrogen loading and constant flow provide stability relative to more traditional bioreactor installations. Most typically, bioreactors are installed downstream of agricultural drainage systems, and influent flow and nitrogen load depend wholly on precipitation/irrigation and nitrogen application. In this thesis, a novel spring fed bioreactor is studied. Removal rates of nitrogen are quantified using a regression driven by reaction kinetics. The analysis showed bioreactor efficiency was intimately related to hydraulic residence time, nitrogen loading, bioreactor bed temperature, and bioreactor age. The spring fed bioreactor is found to be advantageous because of its consistency, and disadvantages because springs are colder and thus less efficient than typical irrigated runoff.