When comparing numerous educational advantages of Geographic Information Systems (GIS) with the slow integration of GIS practice within education globally, results are confounding. This paradoxical development is also found within South Africa. In fact, GIS has been included in the Further Education and Training (FET) phase by the Department of Basic Education (DoBE) since 2006. However, following the same global trend, curriculum development in South Africa has outpaced educational GIS software research. In addition, the e-learning White paper of SA also urges software development. Barriers hindering GIS practice include the lack of suitable curriculum-aligned GIS software within the South African digital divide context. A need therefore exists for further research regarding educational GIS practice applications within South Africa. Bearing this in mind, a case study was done investigating the viability of an educationally orientated Interactive-GIS-Tutor (I-GIS-T) application within FET phase in Geography. The study was conducted with the grade 11 Geography learners of a secondary school in a rural area of KwaZulu-Natal, as well as with their Geography teacher and two other Geography teachers of the same school. These three teachers have different ICT/GIS abilities and years of teaching experience. Furthermore, the study aimed to identify the main GIS educational barriers, globally and locally, as well as to investigate the viability of the I-GIS-T in relation to these identified barriers. The strategy followed was a case study evaluation, with a qualitative approach to data collection and analysis, supported by quantitative data, since this was most suited to the research questions and context. Pragmatism was therefore the underpinning philosophy within this case study. One-on-one semi-structured teacher interviews were conducted to identify the main barriers of GIS education within the FET phases. Data collection by means of questionnaires, individual interviews, focus group interviews, video recordings and field notes provided a thick description regarding the viability of the I-GIS-T within the natural class setting. ATLAS.tiTM and SPSS software were utilised with analysis of qualitative and supportive quantitative data. Attitudinal tests provided supportive quantitative data. Findings indicated that main GIS practice barriers, globally as well as in the school of study, were the lack of preparation time, a full curriculum, lack of GIS support, complex educational GIS software and the teacher‟s lack of ICT skills. The grade 11 Geography teacher and most of the learners evaluated the I-GIS-T as workable. The I-GIS-T also surmounted the main GIS practice barriers. Furthermore, GIS attitudinal tests revealed an overall positive shift on all the attitudinal questions. The combination of lack of basic computer skills and language (where English is not the mother tongue) were the main reasons why some learners suggested that they struggled with the software. Future I-GIS-T development recommended incorporation of a multi-language choice component, as well as exploratory activities. Within this case study, learners who have mastered basic computer skills found the I-GIS-T effective and workable and therefore a viable GIS software application option within the FET phase Geography. In order to be able to generalise statistically, further quantitative research is suggested. In fact, future quantitative research, employing SEM (Structural Equation Modeling) within the Technology Acceptance Model (TAM) might prove the I-GIS-T to be a viable option within FET schools throughout SA, as well as in other developing countries. / Thesis (MEd (Curriculum Development))--North-West University, Potchefstroom Campus, 2013

<p>Accurate 3D landscape models of cities or mountains have wide applications in mission</p> <p>planning, navigation, geological studies, etc. Lidar scanning using drones can provide high</p> <p>accuracy 3D landscape models, but the data is more expensive to collect as the area of</p> <p>each scan is limited. Thanks to recent maturation of Very-High-Resolution (VHR) optical</p> <p>imaging on satellites, people nowadays have access to stereo images that are collected on a</p> <p>much larger area than Lidar scanning. My research addresses unique challenges in satellite</p> <p>stereo, including stereo rectification with pushbroom sensors, dense stereo matching using</p> <p>image pairs with varied appearance, e.g. sun angles and surface plantation, and rasterized</p> <p>digital surface model (DSM) generation. The key contributions include the Continuous 3D-</p> <p>Label Semi-Global Matching (CoSGM) and a large scale dataset for satellite stereo processing</p> <p>and DSM evaluation.</p>

<p dir="ltr">Canopy height is a fundamental metric for extracting valuable information about forested areas. Over the past decade, Lidar technology has provided a straightforward approach to measuring canopy height using various platforms such as terrestrial, unmanned aerial vehicle (UAV), airborne, and satellite sensors. However, satellite Lidar data, even with its global coverage, has a sparse sampling pattern that doesn’t provide continuous coverage over the globe. In contrast, satellites like LANDSAT offer seamless and widespread coverage of the Earth's surface through spectral data. Can we exploit the abundant spectral information from satellites like LANDSAT and ECOSTRESS to infer structural information obtained from Lidar satellites like Global Ecosystem Dynamic Investigation (GEDI)? This study aims to develop a deep learning model that can infer canopy height derived from sparsely observed Lidar waveforms using multi-sensor spectral data from spaceborne platforms. Specifically designed for localized site, the model focuses on county-level canopy height estimation, taking advantage of the relationship between canopy height and spectral reflectance that can be established in a local setting – something which might not exist universally. The study hopes to achieve a framework that can be easily replicable as height is a dynamic metric which changes with time and thus requires repeated computation for different time periods.</p><p dir="ltr">The thesis presents a series of experiments designed to comprehensively understand the influence of different spectral datasets on the model’s performance and its effectiveness in different types of test sites. Experiment 1 and 2 utilize Landsat spectral band values to extrapolate canopy height, while Experiment 3 and 4 incorporate ECOSTRESS land surface temperature and emissivity band values in addition to Landsat data. Tippecanoe County, predominantly composed of cropland, serves as the test site for Experiment 1 and 3, while Monroe County, primarily covered by forests, serves as the test site for Experiment 2 and 4. When compared to the Airborne Lidar dataset from the United States Geological Survey (USGS) – 3D Elevation Program (3DEP), the model achieves a Root Mean Square Error (RMSE) of 4.604m for Tippecanoe County using Landsat features while 5.479m for Monroe County. After integrating Landsat and ECOSTRESS features, the RMSE improves to 4.582m for Tippecanoe County but deteriorates to 5.860m for Monroe County. Overall, the study demonstrates comparable results to previous research without requiring feature engineering or extensive pre-processing. Furthermore, it successfully introduces a novel methodology for integrating multiple sources of satellite data to address this problem.</p>

<p dir="ltr">We explore the efficacy of sparsity and ensemble model in the classification of hyperspectral images, a pivotal task in remote sensing applications. While Convolutional Neural Networks (CNNs) and Transformer models have shown promise in this domain, each exhibits distinct limitations; CNNs excel in capturing the spatial/local features but falter to capture spectral features, whereas Transformers captures the spectral features at the expense of spatial features. Furthermore, the computational cost associated with training several independent CNN and Transformer networks becomes expensive. To address these limitations, we propose a novel ensemble framework comprising pruned CNNs and Transformers, optimizing both spatial and spectral feature utilization while curbing computational costs. By integrating sparsity through model pruning, our approach effectively reduces redundancy and computational complexity without compromising accuracy. Through extensive experimentation, we find that our method achieves comparable accuracy to its non-sparse counterparts while decreasing the computational cost. Our contribution enhances remote sensing analytics by demonstrating the potential of sparse and ensemble models in improving the precision and computational efficiency of hyperspectral image classification.</p>

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / Dunas costeiras exercem um importante papel na manutenÃÃo do fluxo de sedimentos da zona costeira. O Parque Nacional de Jericoacoara, localizado no estado do CearÃ, regiÃo Nordeste do Brasil, possui uma morfologia pouco frequente, trata-se de um promontÃrio associado com um campo de dunas mÃveis denominadas barcanas, dunas individuais, de grande porte com formato de ferraduras que se deslocam em direÃÃo L â O. Elas realizam o by-pass, o transporte de sedimentos, essencial para a manutenÃÃo da linha de costa. Neste trabalho, foi priorizada a definiÃÃo da evoluÃÃo morfodinÃmica de dunas mÃveis isoladas (dunas Papai Noel, PÃr-do-Sol e Arraia), tendo como referencial teÃrico a anÃlise das paisagens e como procdimento tÃcnico principal a anÃlise espaÃo-temporal do recobrimento de imagens multitemporais dos satÃlites Landsat e Quickbird entre os anos de 1973 a 2014. AtravÃs da comparaÃÃo da distribuiÃÃo espaÃo temporal das morfologias dunares, nesse perÃodo de 41 anos, evidenciaram-se mudanÃas significativas na Ãrea, perÃmetro e deslocamento das dunas. Foi possÃvel constatar a aÃÃo dos fluxos de matÃria e energia vinculados com migraÃÃo continuada direcionada para a faixa de praia (setor de bypassing de sedimentos). A dinÃmica de migraÃÃo das dunas, quando analisadas apÃs as imagens de 2000, evidenciou possibilidades de alteraÃÃes dos aspectos morfolÃgicos influenciados pelo incremento do fluxo turÃstico, quando instituÃdo o PARNA de Jericoacoara. As mudanÃas foram mais significativas, sobretudo, entre os anos de 2001 a 2005, o que pode estar relacionado a uma maior intervenÃÃo humana (fluxo de turistas). A utilizaÃÃo das tÃcnicas de geoprocessamento para o mapeamento da evoluÃÃo morfodinÃmica do campo de dunas do Parque Nacional de Jericoacoara constituiu- se uma ferramenta essencial para a produÃÃo de informaÃÃes que certamente subsidiarÃo a continuidade do planejamento ambiental da referida, que se constitui como uma Unidade de ConservaÃÃo de ProteÃÃo Integral. / Coastal dunes play an important role in the sediment flow of the coastal zone. The unique morphology of the Jericoacoara National Park in the northeastern Brazilian state of Cearà consists of a promontory covered by a mobile dune field consisting of large, horseshoe-shaped dunes known locally as barcanas that migrate from east to west. These dunes are responsible for the by-pass, the transport of sediments essential for the maintenance of the coastline. The present study focused on the morphodynamic evolution of these isolated mobile dunes through the recovery of multitemporal Landsat and Quickbird satellite images from the years between 1975 and 2014. The comparison of the spatio-temporal distribution of the morphology of these dunes over this 41-year period revealed significant shifts in their area, perimeter, and movement. It was possible to confirm that the flow of material and energy were linked to a process of continuous migration in the direction of the beach (sediment bypassing sector). The dynamics of the dune migration in the years following 2000, when the national park was established, indicate possible impacts of the increase in tourism within the area on the morphology of the dunes. The changes were most significant between 2001 and 2005, possibly reflecting a greater influx of tourists and thus more intense anthropogenic impacts. The different geoprocessing techniques applied to the mapping of the morphodynamic evolution of the dune field of the Jericoacoara National Park proved to be an essential tool for the production of information that will guarantee the long-term environmental planning of this integral conservation unit.

<p> The hydrological cycle is affected by land use variability. Land use spatial and temporal variability has the power to alter watershed runoff, water resource quantity and quality, ecosystems, and environmental sustainability. In recent decades, agriculture lands, pastures, plantations, and urban areas have increased, resulting in significant increases in energy, water, and fertilizer usage, as well as significant biodiversity losses. </p>

<p dir="ltr">As a new spaceborne laser remote sensing system, the Global Ecosystem Dynamics Investigation, or GEDI, is being widely used for monitoring forest ecosystems. However, its measurements are subject to uncertainties that will affect the calculation of ground elevation and vegetation height. This research intends to investigate the quality of the GEDI elevation data and its relevance to topography and land cover.</p><p dir="ltr">In this study, the elevation of the GEDI data is compared to 3DEP DEM, which has a higher resolution and accuracy. All the experiments in this study are conducted for two locations with vastly different terrain and land cover conditions, namely Tippecanoe County in Indiana and Mendocino County in California. Through this investigation we expect to gain a comprehensive understanding of GEDI’s elevation quality in various terrain and land cover conditions.</p><p dir="ltr">The results show that GEDI data in Tippecanoe County has better elevation accuracy than the GEDI data in Mendocino County. GEDI in Tippecanoe County is almost four times more accurate than in Mendocino County. Regarding land cover, GEDI have better accuracy in low vegetation areas than in forest areas. The ratio can be around three times better in Tippecanoe County and around one and half times better in Mendocino County. In terms of slope, GEDI data shows a clear positive correlation between RMSE and slope. The trend indicates as slope increases, the RMSE increases concurrently. In other words, slope and GEDI elevation accuracy are inversely related. In the experiment involving slope and land cover, the results show that slope is the most influential factor to GEDI elevation accuracy.</p><p dir="ltr">This study informs GEDI users of the factors they must consider for forest biomass calculation and topographic mapping applications. When high terrain slope and/or high vegetation is present, the GEDI data should be checked with other data sources like 3DEP DEM or any ground truth measurements to assure its quality. We expect these findings can help worldwide users understand that the quality of GEDI data is variable and dependent on terrain relief and land cover.</p>

<div>With increasing focus on large scale planning and allocation of resources for protection against future flood risk, it is necessary to analyze and improve the deficiencies in the conventional flood modeling approach through a better understanding of the interactions between river hydrodynamics and subsurface processes. Recent studies have shown that it is possible to improve the flood inundation modeling and mapping using physically-based integrated models that incorporate observable data through assimilation and simulate hydrologic fluxes using the fundamental laws of conservation of mass at multiple spatiotemporal scales. However, despite the significance of integrated modeling in hydrology, it has received relatively less attention within the context of flood hazard. The overall aim of this dissertation is to study the heterogeneity in complex physical processes that govern the watershed response during flooding and incorporate these effects in integrated models across large scales for improved flood risk estimation. Specifically, this dissertation addresses the following questions: (1) Can physical process incorporation using integrated models improve the characterization of antecedent conditions and increase the accuracy of the watershed response to flood events? (2) What factors need to be considered for characterizing scale-dependent physical processes in integrated models across large watersheds? (3) How can the computational efficiency and process representation be improved for modeling flood events at large scales? (4) Can the applicability of integrated models be improved for capturing the hydrodynamics of unprecedented flood events in complex urban systems?</div><div><br></div><div>To understand the combined effect of surface-subsurface hydrology and hydrodynamics on streamflow generation and subsequent inundation during floods, the first objective incorporates an integrated surface water-groundwater (SW-GW) modeling approach for simulating flood conditions. The results suggest that an integrated model provides a more realistic simulation of flood hydrodynamics for different antecedent soil conditions. Overall, the findings suggest that the current practice of simulating floods which assumes an impervious surface may not be providing realistic estimates of flood inundation, and that an integrated approach incorporating all the hydrologic and hydraulic processes in the river system must be adopted.</div><div><br></div><div>The second objective focuses on providing solutions to better characterize scale-dependent processes in integrated models by comparing two model structures across two spatial scales and analyzing the changes in flood responses. The results indicate that since the characteristic length scales of GW processes are larger than SW processes, the intrinsic scale (or resolution) of GW in integrated models should be coarser when compared to SW. The results also highlight the degradation of streamflow prediction using a single channel roughness when the stream length scales are increased. A distributed channel roughness variable along the stream length improves the modeled basin response. Further, the results highlight the ability of a dimensionless parameter 𝜂1, representing the ratio of the reach length in the study region to maximum length of the single stream draining at that point, for identifying which streams may require a distributed channel roughness.</div><div><br></div><div>The third objective presents a hybrid flood modeling approach that incorporates the advantages of both loosely-coupled (‘downward’) and integrated (‘upward’) modeling approaches by coupling empirically-based and physically-based approaches within a watershed. The computational efficiency and accuracy of the proposed hybrid modeling approach is tested across three watersheds in Indiana using multiple flood events and comparing the results with fully- integrated models. Overall, the hybrid modeling approach results in a performance comparable to a fully-integrated approach but at a much higher computational efficiency, while at the same time, providing objective-oriented flexibility to the modeler.</div><div><br></div><div>The fourth objective presents a physically-based but computationally-efficient approach for modeling unprecedented flood events at large scales in complex urban systems. The application of the proposed approach results in accurate simulation of large scale flood hydrodynamics which is shown using Hurricane Harvey as the test case. The results also suggest that the ability to control the mesh development using the proposed flexible model structure for incorporating important physical and hydraulic features is as important as integration of distributed hydrology and hydrodynamics.</div>

<p>This study examines the extent to which transit may be able to assist with the upward mobility of low-income groups, specifically those making less than a living wage. Previous studies relating to job accessibility have examined the feasibility of reaching jobs using various modes of transportation, and some have factored educational requirements into the attainability of those jobs. However, no studies thus far have attempted to determine transit accessibility to jobs that can facilitate and enable upward mobility for low-income households. Employment data relevant to the labor force of Marion County, Indiana, is used to determine the earnings (mainly wages or salaries) associated with occupations, and which occupations require no more than a high school education. Those occupations are then paired with the various industries they are found in, and the earnings belonging to the industry’s highest-earning occupation is associated with that industry. The median household incomes of low-income Census block groups (CBGs) are then compared to the earnings of each transit-accessible industry to evaluate whether those earnings are large enough to induce upward mobility for those living in the CBGs. Bus routes and bus stops for the local transit system (IndyGo) along with workplace locations are mapped in ArcGIS to assess the low-income population’s accessibility to workplaces belonging to a select group of industries. </p><p> </p><p> </p><p>Bus routes that serve both downtown Indianapolis and low-income CBGs were found to provide people living in those CBGs with access to some of the most lucrative jobs, particularly those found in the <i>Finance and Insurance</i> industries. Over half of Indianapolis’ transit-accessible industries have earnings amounts large enough to induce upward mobility for those living in all the low-income CBGs; this corresponds to 6,748 unique workplaces. Findings from this study suggest that low-income people would benefit from having access to transit routes that serve downtowns and other areas with high concentrations of white-collar jobs. Low-income Indianapolis residents informed of this study’s results may be motivated to explore the possibilities for better-paying jobs accessible to them by transit. Furthermore, methods used in this study can help in ranking different transit routes for accessibility to workplaces conducive to upward mobility. The rankings can be updated periodically to assist in addressing equity goals for transit planning.</p>