Visibility analysis is an important GIS tool that is used in a diverse array of disciplines ranging from earth sciences to telecommunications. Multi-visibility, as a cumulative type of visibility, combines many point-to-point results into a multi-value array. Points, lines, or areas can be used as sources or targets / and the combined values can be calculated in both ways. Through multi-visibility, a special 2.5D visibility value surface can be constructed over a digital elevation model. The effectiveness of multi-visibility can be increased with weighted target zones. Other types of weighting criteria can be defined, such as distance and angle. Open source GIS tools offer a limited amount of support for that type of multivisibility analysis. In this study, a weighted multi-visibility methodology has been developed which accepts a path as the source. The path can have a specific direction to account for moving subjects that have a specific view angle based on their direction. A software tool has been developed to apply the methodology in a practical and automated way. The tool was written in Python programming language and can be run as a plugin to the open source Quantum GIS software. The proposed weighted multi-analysis methodology and its software tool can be used to assess the quality of visibility through the generation of value surfaces and calculation of a combined quantitative visibility value for the full path.

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.

The most widely used classification method for statistical mapping is Jenks’s natural breaks. However, it has been found that natural breaks is not good at classifying data which have scaling property. Scaling property is ubiquitous in many societal and natural phenomena. It can be explained as there are far more smaller things than larger ones. For example, there are far more shorter streets than longer ones, far more smaller street blocks than bigger ones, and far more smaller cities than larger ones. Head/tail breaks is a new classification scheme that is designed for values that exhibit scaling property. In Digital Elevation Models (DEMs), there are far more lower elevation points than higher elevation points. This study performs both head/tail breaks and natural breaks for values from five resolutions of DEMs. The aim of this study is to examine advantages and disadvantages of head/tail breaks classification scheme compared with natural breaks. One of the five resolutions of DEMs is given as an example to illustrate the principle behind the head/tail breaks in the case study.The results of head/tail breaks for five resolutions are slightly different from each other in number of classes or level of details. The similar results of comparisons support the previous finding that head/tail breaks is advantaged over natural breaks in reflecting the hierarchy of data. But the number of classes could be reduced for better statistical mapping. Otherwise the top values, which are very little, would be nearly invisible in the map.A main conclusion to be drawn from this study is that head/tail breaks classification scheme is advantaged over natural breaks in presenting hierarchy or scaling of elevation data, with the top classes gathered into one. Another conclusion is when the resolution gets higher; the scaling property gets more striking.

Closed depressions, low elevation features in a landscape with no outlet point, play an important role in both surface and subsurface hydrology. These depressions, which are common in hummocky morainal landscapes, pool incoming surface flow, promoting infiltration and facilitating leaching of surface pollutants into vital groundwater resources. Due to the cost of ground based identification in large areas and difficulties with the identification of irregular depressions, remote identification using digital elevation models (DEMs) stands as a practical and effective tool for the mapping of these closed depressions. A modified stochastic depression identification algorithm was used in this study to characterize depressions in the Waterloo and Paris-Galt-Guelph moraines of Southwestern Ontario. The simulation output was a map of depressions in the study area. Depressions were corroborated using GRCA Wetlands data, Google Street View imagery, SWOOP 2006 orthophotos and field validation. Depression corroboration showed that the algorithm was able to accurately identify the location of closed depressions containing wetlands and closed depressions that are dry (largely due to wetland draining) in the hummocky topography of the study site. This research has implications for depression mapping in the field of digital terrain analysis as it enables the identification of real depressions in large study areas with a moderate resolution DEM. Providing a means of efficiently mapping closed depressions is important because of the role closed depressions play in the recharge of important groundwater stores. / Natural Resources Canada

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.

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.

Digital Elevation Models (DEM) are typically created through a variety of multi-step processes that are generally labour intensive. This thesis explores the trade-offs involved in automating these processes in order to produce a DEM at various resolutions, while minimizing artifacts and highlighting areas where artifacts or uncertainty may have been introduced. The iDEM system is a prototype design to automate the creation of customized DEM complete with a detailed audit-trail of metadata history. Originally conceived as a solution to creating DEM for tsunami modelling, iDEM is applicable to modelling any spherical surface. The proposed framework is highly generalizable in that it leverages existing applications in a plug-and-play manner, essentially integrating them into a new system. The creation of DEM in our prototype design utilizes an amalgamation of three existing fusion methods that allow tessellation without edge distortion and propagates data uncertainty for every DEM generated. The challenge of integrating data in different formats is tackled by automatically generating customized DEM based on the selection of any module providing data fusion techniques applied to the best measurements available. / Graduate

This thesis evaluates the potential for using line of sight returns and return signals from underneath a forest canopy using X-band, airborne synthetic aperture radar (SAR) tomography. Approximately 30% of the Earth’s land surface is covered by vegetation, therefore global digital elevation models (DEMs) contain a signal from the forest canopy and not the ground. By uncovering new techniques to find the ground signals, using data collected from airborne platforms as verification, such procedures could be applied to currently operational and future X-band, spaceborne systems with the aim of resolving much of the vegetation bias on an international scale. Data from three sources is presented; data collected from Selex ES’s SAR systems, the GOTCHA dataset and simulated data. Before carrying out tomography it is shown that SAR interferometry (InSAR) can successfully be applied to X-band, helicopter data. A scatterer defined as a candidate persistent scatterer (CPS) is introduced, where the pixels are stable and coherent over a matter of days. An algorithm for selecting CPSs is developed by exploiting sparsity and a novel choice of hard thresholding operator. Using simulated forestry and SAR information the effects of changing input parameters on the outcome of the tomographic profile is analysed. What is found in this study is that model simulations demonstrate that ground points can be detected if the platform motion is relatively stable and that temporal decorrelation over the forest volume is kept to a minimal. An understory can confuse the tomographic profile since less line of sight observations can be made. By combining line of sight observations alongside new tomography techniques on high resolution SAR data this thesis shows it is possible to detect ground scatterers, even at X-band.

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.