Spatial Distribution of Soil Geochemistry in Geoforensics

Two common scenarios in Geoforensics (definition in text) are considered: the provenance, or localization of unknown samples and the question of sample variability at scenes of crime/alibi locations. Both have been discussed in forensic and soil science publications, but mostly within a theoretical or non-forensic context. These previous publications provide context for the two case study scenarios (one actual, one based on a range of criminal casework) that consider provenance and variability. A challenging scientific question in geoforensics is the provenance question: ‘where may this sample have come from?’ A question the Tellus data can assist in answering. The question of variation between samples maybe less of a challenge, yet variation between a suspect sample within a scene of crime requires detailed sampling. Variation on a larger (tens to hundreds of kilometres) scale may provide useful intelligence on where a sample came from. To summarise, databases such as Tellus and TellusBorder may be used as effective tools to assist in the search for the origin of displaced soil and sediment

MHD wave modes resolved in fine-scale chromospheric magnetic structures

Within the last decade, due to significant improvements in the spatial and temporal resolution of chromospheric data, magneto hydrodynamic (MHD)wave studies in this fascinating region of the Sun's atmosphere have risen to the forefront of solar physics research. In this review we begin by reviewing the challenges and debates that have manifested in relation to MHD wave mode identification in fine-scale chromosphericmagnetic structures, including spicules, fibrils and mottles. Next we goon to discuss how the process of accurately identifying MHD wave modes also has a crucial role to play in estimating their wave energy flux.This is of cardinal importance for estimating what the possible contribution of MHD waves is to solar atmospheric heating. Finally, we detail how such advances in chromospheric MHD wave studies have also allowed us, for the first time, to implement cutting-edge magneto seismological techniques that provide new insight into the sub-resolution plasma structuring of the lower solar atmosphere.

Temporal and spatial patterns in α- and γ-hexachlorocyclohexane concentrations in industrially contaminated rivers

Fluxes of HCH isomers α- and γ-HCH dynamics were determined in four industrial U.K. rivers feeding the North Sea. Sampling was conducted weekly basis over a 2-year period. This was complemented by discrete studies of events where two hourly sampling periods were used to investigate the fine time scale dynamics of fluxes. Two intensively industrialized rivers had average isomer concentrations of ~20 ng L^-1 for both isomers, while average concentrations in the two less industrialized rivers ranged between 1.5 and 5.0 ng L^-1. α-HCH concentrations showed no strong temporal patterns on any river, which contrasts with γ-HCH levels that increased considerably during late summer/early autumn following sustained periods of low river flow. Sampling during high river flow events on rivers with differing HCH pollution histories both showed the same dynamics in HCH isomer concentrations. γ-HCH concentrations decreased 4-fold during events while α-HCH-concentrations stayed constant. The increases in γ-HCH concentrations under low flow conditions and the rapid dilution of this isomer during events indicate that γ-HCH has current inputs to these river systems. It was calculated that these four rivers export 30.8 kg yr^-1 of γ-HCH and 14.8 kg yr^-1 of α-HCH to the North Sea.

Temporal Spatial-Keyword Top-k publish/subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date tweets such that their locations are close to a user specified location and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “food poisoning vomiting.” We consider the Temporal Spatial-Keyword Top-k Subscription (TaSK) query. Given a TaSK query, we continuously maintain up-to-date top-k most relevant results over a stream of geo-textual objects (e.g., geo-tagged Tweets) for the query. The TaSK query takes into account text relevance, spatial proximity, and recency of geo-textual objects in evaluating its relevance with a geo-textual object. We propose a novel solution to efficiently process a large number of TaSK queries over a stream of geotextual objects. We evaluate the efficiency of our approach on two real-world datasets and the experimental results show that our solution is able to achieve a reduction of the processing time by 70-80% compared with two baselines.

Using geotechnical and LIDAR spatial monitoring to determine key environmental slope instability thresholds of a Jurassic coastal landslide: Straidkilly Point, Northern Ireland, UK.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland to the famous Giant’s Causeway in the North has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). At various locations along the route, fluid interactions between the problematic geology, Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability within the vadose zone. During such instances of instability, debris flows and composite mudflows encroach on the carriageway posing a hazard to road users. This paper examines the site investigative, geotechnical and spatial analysis techniques currently being implemented to monitor slope stability for one site at Straidkilly Point, Glenarm, Northern Ireland. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration dynamic data.
Terrestrial LiDAR (TLS) was applied to the slope for the monitoring of failures, with surveys carried out on a bi-monthly basis. TLS monitoring allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, erosion and deposition. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters are characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDARi datasets were used for the spatio-morphological characterisation of the slope on a macro scale. Results from the geotechnical and environmental monitoring were compared with spatial data obtained through Terrestrial and Airborne LiDAR, providing a multi-faceted approach to slope stability characterization, which facilitates more informed management of geotechnical risk by the Northern Ireland Roads Service.

Footprints in the sand: a persistent spatial impression of fishing in a mobile groundfish assemblage

Fishing is well known to curtail the size distribution of fish populations. This paper reports the discovery of small-scale spatial patterns in length appearing in several exploited species of Celtic Sea demersal 'groundfish'. These patterns match well with spatial distributions of fishing activity, estimated from vessel monitoring records taken over a period of 6 years, suggesting that this 'mobile' fish community retains a persistent impression of local-scale fishing pressure. An individual random-walk model of fish movement best matched these exploitation 'footprints' with individual movement rates set to <35 km per year. We propose that Celtic Sea groundfish may have surprisingly low movement rates for much of the year, such that fishing impact is spatially heterogeneous and related to local fishing intensity.

Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F(CT) = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F(CT) range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.

SOPS: A System for Efficient Processing of Spatial-Keyword Publish/Subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users’ need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “dengue fever headache.” In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.

Spatial variation in adult sex ratio across multiple scales in the invasive golden apple snail, Pomacea canaliculata

Adult sex ratio (ASR) has critical effects on behavior and life history and has implications for population demography, including the invasiveness of introduced species. ASR exhibits immense variation in nature, yet the scale dependence of this variation is rarely analyzed. In this study, using the generalized multilevel models, we investigated the variation in ASR across multiple nested spatial scales and analyzed the underlying causes for an invasive species, the golden apple snail Pomacea canaliculata. We partitioned the variance in ASR to describe the variations at different scales and then included the explanatory variables at the individual and group levels to analyze the potential causes driving the variation in ASR. We firstly determined there is a significant female-biased ASR for this species when accounting for the spatial and temporal autocorrelations of sampling. We found that, counter to nearly equal distributed variation at plot, habitat and region levels, ASR showed little variation at the town level. Temperature and precipitation at the region level were significantly positively associated with ASR, whereas the individual weight, the density characteristic, and sampling time were not significant factors influencing ASR. Our study suggests that offspring sex ratio of this species may shape the general pattern of ASR in the population level while the environmental variables at the region level translate the unbiased offspring sex ratio to the female-biased ASR. Future research should consider the implications of climate warming on the female-biased ASR of this invasive species and thus on invasion pattern.

Multi-scale dynamics on the Eastern Brazilian margin

Este trabalho combina esforços de simulação numérica e de análise de dados para investigar a dinâmica em diversos compartimentos (oceano aberto, plataforma continental e zona costeira-estuarina) e, em multiplas escalas, na Margem Continental Leste Brasileira (MCLB). A circulação de largo e mesoescala espacial e a propagação da maré barotrópica são investigadas através de uma configuração aninhada do modelo numérico ROMS. O estudo da dinâmica regional da Baía de Camamu (CMB) baseia-se na análise de dados locais. A MCLB, localizada a SW do Atlântico Sul entre 8±S e 20±S, possui plataforma estreita, batimetria complexa, e baixa produtividade primária. A sua dinâmica é influenciada pela divergência da Corrente Sul Equatorial (CSE). As simulações refletem as conexões sazonais e espaciais entre a Corrente do Brasil e a Contra Corrente Norte do Brasil , em conexão com a dinâmica da CSE. As simulações revelam atividades vorticais nas proximidades da costa e interações com a dinâmica costeira, cujos padrões são descritos. A validação do modelo em mesoescala é baseada em cálculos de energia cinética turbulenta e em dados históricos de transporte. A CMB, localizada a 13±400S, abriga uma comunidade piscatória tradicional e extenso de manguezal. Situa-se porém sobre uma bacia sedimentar com grande reservas de óleo e gás, estando em tensão permanente de impacto ambiental. Neste trabalho sumarizamos as condições físicas regionais e investigamos sua dinâmica interna, focando sua variabilidade em amostragens realizadas sob condições de seca (Setembro de 2004) e de chuva (Julho de 2005). Finalmente, o modelo numérico ROMS é forçado com o sinal de maré, empregando-se uma configuração simples (com coeficientes de atrito de fundo constantes e condições hidrográficas homogéneas), com o intuito de avaliar sua resposta e investigar a natureza da propagação da maré barotrópica na MCLB, convergindo na CMB. A análise da resposta do modelo à maré basea-se em séries históricas do nível do mar para a MCLB e dados recentes da CMB.

Multi-scale keypoints in V1 and face detection

End-stopped cells in cortical area V1, which combine out- puts of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representa- tion, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Al- though a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.

Face normalization using multi-scale cortical keypoints

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extractions. Simple, complex and end-stopped cells tuned to different spatial frequencies (scales) and/or orientations provide input for line, edge and keypoint detection. This yields a rich, multi-scale object representation that can be stored in memory in order to identify objects. The multi-scale, keypoint-based saliency maps for Focus-of-Attention can be explored to obtain face detection and normalization, after which face recognition can be achieved using the line/edge representation. In this paper, we focus only on face normalization, showing that multi-scale keypoints can be used to construct canonical representations of faces in memory.

Landslide susceptibility evaluation and validation at a regional scale

Tese de doutoramento, Geografia (Geografia Física), Universidade de Lisboa, Instituto de Geografia e Ordenamento do Território, 2014

Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.