Context-Preserving Visual Analytics of Multi-Scale Spatial Aggregation.

Spatial datasets (i.e., location-based social media, crime incident reports, and demographic data) often exhibit varied distribution patterns at multiple spatial scales. Examining these patterns across different scales enhances the understanding from global to local perspectives and offers new insights into the nature of various spatial phenomena. Conventional navigation techniques in such multi-scale data-rich spaces are often inefficient, require users to choose between an overview or detailed information, and do not support identifying spatial patterns at varying scales. In this work, we present a context-preserving visual analytics technique that aggregates spatial datasets into hierarchical clusters and visualizes the multi-scale aggregates in a single visual space. We design a boundary distortion algorithm to minimize the visual clutter caused by overlapping aggregates and explore visual encoding strategies including color, transparency, shading, and shapes, in order to illustrate the hierarchical and statistical patterns of the multi-scale aggregates. We also propose a transparency-based technique that maintains a smooth visual transition as the users navigate across adjacent scales. To further support effective semantic exploration in the multi-scale space, we design a set of text-based encoding and layout methods that draw textual labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each scale, but also indicates the spatial coverage of the aggregates and their hierarchical relationships. We demonstrate the effectiveness of the proposed approaches through real-world application examples and user studies

Development and validation of spatial distribution models of marine habitats, in support of the ecological valuation of the seabed

The marine environment is subjected to increasing anthropogenic pressure. Although there is a willingness of the different activities to minimize their impacts, there is a strong need for the assessment of the ecological value of the seabed, comprising both the abiotic substrate and the living organisms related to it (together called a ‘habitat’). Therefore, ‘habitat mapping’ is crucial, not only for the assessment of the ecological value at a certain moment, but also to follow its evolution over time. Because of the world-wide application of marine habitat mapping, there is currently a great variety in approaches, methodologies to use, as also in the ways habitats are classified. Therefore, it is of utmost importance that attempts are being made to propose more ‘common approaches’ in marine habitat mapping. The general aim of this study is to apply and develop straightforward and statistically sound methodologies for highly reliable sedimentological and habitat modelling, in support of a more sustainable management of our seas. To achieve these aims, this thesis is subdivided into 2 themes: 1) Best coverage data for habitat mapping; and 2) Integration of datasets in the view of habitat mapping

New insights into the suitability of the third dimension for visualizing multivariate/multidimensional data: a study based on loss of quality quantification

Most visualization techniques have traditionally used two-dimensional, instead of three-dimensional representations to visualize multidimensional and multivariate data. In this article, a way to demonstrate the underlying superiority of three-dimensional, with respect to two-dimensional, representation is proposed. Specifically, it is based on the inevitable quality degradation produced when reducing the data dimensionality. The problem is tackled from two different approaches: a visual and an analytical approach. First, a set of statistical tests (point classification, distance perception, and outlier identification) using the two-dimensional and three-dimensional visualization are carried out on a group of 40 users. The results indicate that there is an improvement in the accuracy introduced by the inclusion of a third dimension; however, these results do not allow to obtain definitive conclusions on the superiority of three-dimensional representation. Therefore, in order to draw further conclusions, a deeper study based on an analytical approach is proposed. The aim is to quantify the real loss of quality produced when the data are visualized in two-dimensional and three-dimensional spaces, in relation to the original data dimensionality, to analyze the difference between them. To achieve this, a recently proposed methodology is used. The results obtained by the analytical approach reported that the loss of quality reaches significantly high values only when switching from three-dimensional to two-dimensional representation. The considerable quality degradation suffered in the two-dimensional visualization strongly suggests the suitability of the third dimension to visualize data

The interpretation and characterisation of lineaments identified from Landsat TM imagery of SW England

Two Landsat TM scenes of SW England and a sub-scene of North Cornwall have been analysed visually in order to examine the effect of resolution on lineament interpretation. Images were viewed at several different scales as a result of varying image resolution whilst maintaining a fixed screen pixel size. Lineament analysis at each scale utilised GIS techniques and involved several stages: initial lineament identification and digitisation; removal of lineaments related to anthropogenic features to produce cleansed lineament maps; compilation of lineament attributes using ARC/INFO; cluster analysis for identification of lineament directional families; and line sampling of lineament maps in order to determine spacing. SW England lies within the temperate zone of Europe and the extensive agricultural cover and infrastructure conceal the underlying geology. The consequences of this for lineament analysis were examined using sub-images of North Cornwall. Here anthropogenic features are visible at all resolutions between 30m and 120m pixel sizes but lie outside the observation threshold at 150m. Having confidence that lineaments at this resolution are of non-anthropogenic origin optimises lineament identification since the image may be viewed in greater detail. On this basis, lineament analysis of SW England was performed using image resolutions of 150m. Valuable geological information below the observation threshold in 150m resolution images is likely, however, to be contained in the lineament maps produced from higher resolution images. For images analysed at higher resolutions, therefore, knowledge-based rules were established in order to cleanse the lineament populations. Compiled lineament maps were 'ground truthed' (primarily involving comparison with published geological maps but included phases of field mapping) in order to characterise their geological affinities. The major lineament trends were correlated to lithotectonic boundaries, and cross-cutting fractures sets. Major lineament trends produced distinct frequency/orientation maxima. Multiple minor geological structures, however, produced semi-overlapping groups. A clustering technique was devised to resolve overlapping groups into lineament directional families. The newly defined lineament directional families were further analysed in two ways: (i) Analysis of the spatial density of the length and frequency of lineaments indicates that individual and multiple lineament directional families vary spatially and are compartmentalised into local tectonic domains, often bounded by major lineaments. Hence, such density maps provide useful additional information about the structural framework of SW England. (ii) Lineament spacing and length of the lineament directional families were analysed for the effect of scale and geological causes on their frequency/size distributions. Spacing of fracture lineaments were found to be power-law, whereas lengths showed power-law and non-power-law distributions. Furthermore the type of frequency/size distribution for a lineament directional family can change with increasing resolution

A Methodology to Quantify the Topographic Characteristics of Wetland Landscapes

Topography underpins natural processes ranging from incident solar radiation at a location to overland flow and water pooling. Despite the influence of topography on natural processes and subsequent ecosystem function, especially in wetland ecosystems reliant on surrounding topography for water inputs, topography has not been adequately incorporated into reclamation planning and permit closure requirements. Instead, wetland restoration and reclamation projects are typically guided by simple height-to-length ratios that produce little variation or resemblance to natural wetlands. We present a methodology to quantify the topographic characteristics in wetland landscapes to guide the creation of naturally appearing and self-sustaining reclaimed wetland landscapes. Topographic characteristics in 3,434 1km2 sample landscapes were quantified using terrain roughness and landform element composition and configuration. A large set of metrics were reduced to a parsimonious subset that was applied across three natural regions and a gradient of disturbance. Nonparametric statistical tests were used to compare landscapes across these two dimensions. We found that landscape-scale topographic characteristics can be represented by five roughness metrics and seven landform element pattern metrics. These metrics demonstrate that surface roughness and landform element patterns significantly differ among natural regions and that high disturbance landscapes significantly differ from other disturbance levels. Wetland reclamation plans should replicate the topographic characteristics found in the surrounding natural landscape. To do so, topographic characteristic benchmarks are required for reclamation design and regulatory approval of closure permits. The presented methodology and resulting metric values can be used as a step towards achieving this goal

Handbook of Mathematical Geosciences

This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences

Environmental geochemistry of Potentially Toxic Elements (PTEs) and Persistent Organic Pollutants (POPs) as a tool of exposure evaluation and chemical risk assessment

Environmental pollution is one of the most challenging environmental issues to tackle due to its impact to human health and the ecosystem. One of the main objectives of environmental geochemistry is to investigate, characterise, and reveal the patterns of organic compounds and inorganic elements and further unveil their possible sources. Geogenic features and anthropogenic activities are the main sources of environmental contamination which are likely to release these contaminants into atmospheric, soil and water media. Moreover, anthropogenic activities let out chemicals produced from industrial activities, domestic, livestock and municipal wastes (including wastewater), agrochemicals, and petroleum-derived products. Organic pollutants cover a large group of synthetized pollutants and Persistent Organic Pollutants (POPs) have received a specific attention due to their physico-chemical properties, high toxicity, and subject to long-range atmospheric transfer. Polychlorinated biphenyls (PCBs), Polycyclic Aromatic Hydrocarbons (PAHs) and Organochlorines Pesticides (OCPs) are the main POPs that are subject to different regulation schemes to their irreversible adverse effects to both human and wildlife health. Stockholm Convention, Rotterdam and Basel, World Health organisation (WHO) and United Nations Economic Commission for Europe POPs Protocol have so far addressed, threated and introduced legislation which ban or fix threshold’s values of these POPs into environment. Potentially Toxic Elements (PTEs) are widespread metals/metalloids related to geogenic and/or anthropogenic activities. PTEs are one of the major concerns in the environment because their concentrations are increasing due to accelerated population growth rate, higher level of urbanisation and industrialisation providing a great variety of anthropogenic contamination/pollution sources. They have often been given special emphasis because their accumulation in different matrices can cause soil and land degradation and they can be transferred into the human body as a consequence of dermal contact, inhalation and ingestion through food chain and drinking water. PTEs are generally non-biodegradable having long biological half-lives and tend to accumulate in soils being absorbed to clay minerals and organic matter. However, their bioavailability is influenced by different physicochemical processes (e.g. pH, Eh) and physiological adaptation. PTEs and POPs can be observed in different environmental media but soil is considered an important reservoir due to its physico-chemical properties which confer high retention capacity of these pollutants. Soil contamination has been increasing worldwide and has become the focus of attention in recent years. Several soil parent materials are natural sources of certain organic contaminants, elements, and these can pose a risk to the environment and human health at elevated concentrations. For that, various geostatistical computations have been used to identify source patterns of different pollutants related to underlying geological features and/or anthropogenic activities, and to further distinguish mineralisation from contamination. Several single and complex contamination/mineralisation indices such as Enrichment Factor, Geo-accumulation Index or Single Pollution Index have been elaborated to quantify the contamination or mineralisation status of different PTEs. They are generally based on intervention limits (thresholds) or background/baseline values of a single element based on National Legislation, as a reference. Indices based on intervention limits (thresholds) are easily interpretable and comparable, but they disregard the compositional nature of geochemical data; hence they can be biased and/or spurious. This PhD research project reveals novel geostatistical computations that will lay out sources patterns of Potentially Toxic Elements (PTEs) and Persistent Organic Pollutants (POPs), and assess the soils contamination levels in the central-southern Italy. Series of follow up studies have provided an invaluable baseline for these contaminants distribution in Italy to push towards an institutional response for more adequate regulation of these pollutants worldwide. A further ongoing research project is currently investigating the content and bioavailability of mercury and Potentially Toxic Elements (PTEs) in artisanal and small-scale gold mining (ASGM) districts of Kedougou (Senegal). This study in particular will represent a fundamental stepping stone to build a baseline review of PTEs in ASGM of Kedougou (Senegal) and evaluate human health risks from exposure of PTEs. It is envisaged that the results of this study should trigger more detailed surveys in contaminated areas as well as ad-hoc risk-based studies, which in the long-term will constitute a strong argument to cause an adequate institutional response by the Senegalese regulating authorities for a full application the Minamata convention

A landscape approach to reserving farm ponds for wintering bird refuges in Taoyuan, Taiwan

Man-made farm ponds are unique geographic features of the Taoyuan Tableland. Besides irrigation, they provide refuges for wintering birds. The issue at hand is that these features are disappearing and bring with it the loss of this refuge function. It is ecologically significant because one fifth of all the bird species in Taiwan find a home on these ponds. This study aims at characterizing the diversity of bird species associated with these ponds whose likelihood of survival was assessed along the gradient of land development intensities. Such characterization helps establish decision criteria needed for designating certain ponds for habitat preservation and developing their protection strategies. A holistic model was developed by incorporating logistic regression with error back-propagation into the paradigm of artificial neural networks (ANN). The model considers pond shape, size, neighboring farmlands, and developed areas in calculating parameters pertaining to their respective and interactive influences on avian diversity, among them the Shannon-Wiener diversity index (HÂ). Results indicate that ponds with regular shape or the ones with larger size possess a strong positive correlation with HÂ. Farm ponds adjacent to farmland benefited waterside bird diversity. On the other hand, urban development was shown to cause the reduction of farmland and pond numbers, which in turn reduced waterside bird diversity. By running the ANN model with four neurons, the resulting HÂ index shows a good-fit prediction of bird diversity against pond size, shape, neighboring farmlands, and neighboring developed areas with a correlation coefficient (r) of 0.72, in contrast to the results from a linear regression model (r < 0.28). Analysis of historical pond occurrence to the present showed that ponds with larger size and a long perimeter were less likely to disappear. Smaller (< 0.1 ha) and more curvilinear ponds had a more drastic rate of disappearance. Based on this finding, a logistic regression was constructed to predict pond-loss likelihood in the future and to help identify ponds that should be protected. Overlaying results from ANN and form logistic regression enabled the creation of pond-diversity maps for these simulated scenarios of development intensities with respective to pond-loss trends and the corresponding dynamics of bird diversity