Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

Development of human visual system analysis for the implementation of a new instrument for flicker measurement

Flicker is a power quality phenomenon that applies to cycle instability of light intensity resulting from supply voltage fluctuation, which, in turn can be caused by disturbances introduced during power generation, transmission or distribution. The standard EN 61000-4-15 which has been recently adopted also by the IEEE as IEEE Standard 1453 relies on the analysis of the supply voltage which is processed according to a suitable model of the lamp – human eye – brain chain. As for the lamp, an incandescent 60 W, 230 V, 50 Hz source is assumed. As far as the human eye – brain model is concerned, it is represented by the so-called flicker curve. Such a curve was determined several years ago by statistically analyzing the results of tests where people were subjected to flicker with different combinations of magnitude and frequency. The limitations of this standard approach to flicker evaluation are essentially two. First, the provided index of annoyance Pst can be related to an actual tiredness of the human visual system only if such an incandescent lamp is used. Moreover, the implemented response to flicker is “subjective” given that it relies on the people answers about their feelings. In the last 15 years, many scientific contributions have tackled these issues by investigating the possibility to develop a novel model of the eye-brain response to flicker and overcome the strict dependence of the standard on the kind of the light source. In this light of fact, this thesis is aimed at presenting an important contribution for a new Flickermeter. An improved visual system model using a physiological parameter that is the mean value of the pupil diameter, has been presented, thus allowing to get a more “objective” representation of the response to flicker. The system used to both generate flicker and measure the pupil diameter has been illustrated along with all the results of several experiments performed on the volunteers. The intent has been to demonstrate that the measurement of that geometrical parameter can give reliable information about the feeling of the human visual system to light flicker.

Time-series Luminance Distribution Maps: implementation of annual daylight simulation methods for occupant visual comfort analysis

Thesis (Master's)--University of Washington, 2016-06

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Particulate texture image analysis with applications

Texture analysis and textural cues have been applied for image classification, segmentation and pattern recognition. Dominant texture descriptors include directionality, coarseness, line-likeness etc. In this dissertation a class of textures known as particulate textures are defined, which are predominantly coarse or blob-like. The set of features that characterise particulate textures are different from those that characterise classical textures. These features are micro-texture, macro-texture, size, shape and compaction. Classical texture analysis techniques do not adequately capture particulate texture features. This gap is identified and new methods for analysing particulate textures are proposed. The levels of complexity in particulate textures are also presented ranging from the simplest images where blob-like particles are easily isolated from their back- ground to the more complex images where the particles and the background are not easily separable or the particles are occluded. Simple particulate images can be analysed for particle shapes and sizes. Complex particulate texture images, on the other hand, often permit only the estimation of particle dimensions. Real life applications of particulate textures are reviewed, including applications to sedimentology, granulometry and road surface texture analysis. A new framework for computation of particulate shape is proposed. A granulometric approach for particle size estimation based on edge detection is developed which can be adapted to the gray level of the images by varying its parameters. This study binds visual texture analysis and road surface macrotexture in a theoretical framework, thus making it possible to apply monocular imaging techniques to road surface texture analysis. Results from the application of the developed algorithm to road surface macro-texture, are compared with results based on Fourier spectra, the auto- correlation function and wavelet decomposition, indicating the superior performance of the proposed technique. The influence of image acquisition conditions such as illumination and camera angle on the results was systematically analysed. Experimental data was collected from over 5km of road in Brisbane and the estimated coarseness along the road was compared with laser profilometer measurements. Coefficient of determination R2 exceeding 0.9 was obtained when correlating the proposed imaging technique with the state of the art Sensor Measured Texture Depth (SMTD) obtained using laser profilometers.

Mutational Analysis of the Rhodopsin Gene in Sector Retinitis Pigmentosa

Background: To determine the role of rhodopsin (RHO) gene mutations in patients with sector retinitis pigmentosa (RP) from Northern Ireland.

Design: A case series of sector RP in a tertiary ocular genetics clinic.

Participants: Four patients with sector RP were recruited from the Royal Victoria Hospital (Belfast, Northern Ireland) and Altnagelvin Hospital (Londonderry, Northern Ireland) following informed consent.

Methods: The diagnosis of sector RP was based on clinical examination, International Society for Clinical Electrophysiology of Vision (ISCEV) standard electrophysiology, and visual field analysis. DNA was extracted from peripheral blood leucocytes and the coding regions and adjacent flanking intronic sequences of the RHO gene were polymerase chain reaction (PCR) amplified and cycle sequenced.

Main Outcome Measure: Rhodopsin mutational status.

Results: A heterozygous missense mutation in RHO (c.173C > T) resulting in a non-conservative substitution of threonine to methionine (p. Thr58Met) was identified in one patient and was absent from 360 control individuals. This non-conservative substitution (p.Thr58Met) replaces a highly evolutionary conserved polar hydrophilic threonine residue with a non-polar hydrophobic methionine residue at position 58 near the cytoplasmic border of helix A of RHO.

Conclusions: The study identified a RHO gene mutation (p.Thr58Met) not previously reported in RP in a patient with sector RP. These findings outline the phenotypic variability associated with RHO mutations. It has been proposed that the regional effects of RHO mutations are likely to result from interplay between mutant alleles and other genetic, epigenetic and environmental factors.

All of My Blood is Red: Contemporary Metis Visual Culture and Identity

This thesis explores notions of contemporary Metis identity through the lens of visual culture, as articulated in the works of three visual artists of Metis ancestry. I discuss the complexities of being Metis with reference to specific art works by Christi Belcourt, David Garneau and Rosalie Favell. In addition to a visual culture analysis of these three Metis artists, I supplement my discussion of Metis identity with a selection of autoethnographic explorations of my identity as a Metis woman through out this thesis. The self-reflexive aspect of this work documents the ways in which my understanding of myself as a Metis woman have been deepened and reworked in the process of conducting this research, while also offering an expanded conception of contemporary Metis culture. I present this work as an important point of departure for giving a greater presence to contemporary Metis visual culture across Canada:

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.

Use of comet assay to assess DNA damage in patients infected by Helicobacter pylori - Comparisons between visual and image analyses

Studies of DNA damage in gastric epithelial cells of Helicobacter pylori (H. pylori)-infected patients are conflicting, possibly due to different methods used for scoring DNA damage by Comet assay. Therefore, we compared the sensitivity of visual microscopic analysis (arbitrary units-scores and comets%) and image analysis system (tail moment), in the gastric epithelial cells from the antrum and corpus of 122 H. pylori-infected and 32 non-infected patients. The feasibility of cryopreserved peripheral blood lymphocytes and whole-blood cells for DNA damage biomonitoring was also investigated. In the antrum, the levels of DNA damage were significantly higher in H. pylori-infected patients with gastritis than in non-infected patients with normal mucosa, when evaluated by image analysis system, arbitrary units and comets%. In the corpus, the comets% was not sufficiently sensitive to detect the difference between H. pylori-infected patients with gastritis and non-infected patients with normal mucosa. The image analysis system was sensitive enough to detect differences between non-infected patients and H. pylori-infected patients with mild gastritis and between infected patients with moderate and severe gastritis, in both antrum, and corpus, while arbitrary units and comets% were unable to detect these differences. In cryopreserved peripheral blood lymphocytes, the levels of DNA damage (tail moment) were significantly higher in H. pylori-infected patients with moderate and severe gastritis than in non-infected patients. Overall, our results indicate that the image analysis system is more sensitive and adequate to measure the levels of DNA damage in gastric epithelial cells than the other methods assayed. (c) 2005 Elsevier B.V. All rights reserved.

Social Rankings: análisis visual de sentimientos en redes sociales

Social Rankings es una aplicación web que realiza un seguimiento en tiempo real de entidades en las redes sociales. Detecta y analiza las opiniones sobre estas entidades utilizando técnicas de análisis de sentimientos para generar un informe visual de su valoración y su evolución en el tiempo.

A penny for your thoughts! Patterns of fMRI activity reveal the content and the spatial topography of visual mental images

Visual mental imagery is a complex process that may be influenced by the content of mental images. Neuropsychological evidence from patients with hemineglect suggests that in the imagery domain environments and objects may be represented separately and may be selectively affected by brain lesions. In the present study, we used functional magnetic resonance imaging (fMRI) to assess the possibility of neural segregation among mental images depicting parts of an object, of an environment (imagined from a first-person perspective), and of a geographical map, using both a mass univariate and a multivariate approach. Data show that different brain areas are involved in different types of mental images. Imagining an environment relies mainly on regions known to be involved in navigational skills, such as the retrosplenial complex and parahippocampal gyrus, whereas imagining a geographical map mainly requires activation of the left angular gyrus, known to be involved in the representation of categorical relations. Imagining a familiar object mainly requires activation of parietal areas involved in visual space analysis in both the imagery and the perceptual domain. We also found that the pattern of activity in most of these areas specifically codes for the spatial arrangement of the parts of the mental image. Our results clearly demonstrate a functional neural segregation for different contents of mental images and suggest that visuospatial information is coded by different patterns of activity in brain areas involved in visual mental imagery. Hum Brain Mapp 36:945-958, 2015.

Regional variability in visual field sensitivity during hypercapnia

PURPOSE: Previous investigations have demonstrated a relative vascular autoregulatory inefficiency of the inferior compared to the superior retina in healthy subjects breathing increased CO2. The purpose of this study was to determine whether the superior and inferior visual field sensitivities of healthy eyes are similarly affected during mild hypercapnia. DESIGN: Experimental study. METHODS: Visual field analysis (Humphrey Field Analyser; SITA standard 24-2 program) was carried out on one randomly selected eye of 22 subjects (mean age, 27.7 ± 5 years) during normal room air breathing and isoxic hypercapnia. The Student paired t-tests were used to compare the visual field indices mean deviation (MD) and pattern standard deviation (PSD) for each breathing condition. A secondary, sectoral analysis of mean pointwise sensitivity was performed for each condition. In each case a P value of <.01 was considered statistically significant (Bonferroni corrected). RESULTS: Visual field MD was -0.23 ± 0.95dB during room air breathing and -0.49 ± 1.04dB during hypercapnia (P = .034). Sectoral pointwise mean sensitivity deteriorated by 0.46dB (P = .006) in the upper visual hemifield during hypercapnia, whereas no significant difference was observed for the lower hemifield (P = .331). CONCLUSIONS: The upper visual hemifield exhibited a significantly greater degree of deterioration in pointwise visual field mean sensitivity compared to the lower hemifield during hypercapnic conditions. This suggests that the upper visual hemifield and hence inferior retina is more susceptible to insult during hypercapnia than the superior retina in healthy individuals. A regional susceptibility of inferior retinal function to altered vascular or metabolic effects may account for the earlier and more frequent inferior nerve fibre damage associated with glaucomatous optic neuropathy. © 2003 by Elsevier Science Inc. All rights reserved.

Landslide Susceptible Locations in Western Ghats: Prediction through openModeller

Many shallow landslides are triggered by heavy rainfall on hill slopes resulting in enormous casualties and huge economic losses in mountainous regions. Hill slope failure usually occurs as soil resistance deteriorates in the presence of the acting stress developed due to a number of reasons such as increased soil moisture content, change in land use causing slope instability, etc. Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration and information related to land surface susceptibility. Terrain analysis applications using spatial data such as aspect, slope, flow direction, compound topographic index, etc. along with information derived from remotely sensed data such as land cover / land use maps permit us to quantify and characterise the physical processes governing the landslide occurrence phenomenon. In this work, the probable landslide prone areas are predicted using two different algorithms – GARP (Genetic Algorithm for Rule-set Prediction) and Support Vector Machine (SVM) in a free and open source software package - openModeller. Several environmental layers such as aspect, digital elevation data, flow accumulation, flow direction, slope, land cover, compound topographic index, and precipitation data were used in modelling. A comparison of the simulated outputs, validated by overlaying the actual landslide occurrence points showed 92% accuracy with GARP and 96% accuracy with SVM in predicting landslide prone areas considering precipitation in the wettest month whereas 91% and 94% accuracy were obtained from GARP and SVM considering precipitation in the wettest quarter of the year.