Visual Analytics Methods for Exploring Geographically Networked Phenomena

abstract: The connections between different entities define different kinds of networks, and many such networked phenomena are influenced by their underlying geographical relationships. By integrating network and geospatial analysis, the goal is to extract information about interaction topologies and the relationships to related geographical constructs. In the recent decades, much work has been done analyzing the dynamics of spatial networks; however, many challenges still remain in this field. First, the development of social media and transportation technologies has greatly reshaped the typologies of communications between different geographical regions. Second, the distance metrics used in spatial analysis should also be enriched with the underlying network information to develop accurate models. Visual analytics provides methods for data exploration, pattern recognition, and knowledge discovery. However, despite the long history of geovisualizations and network visual analytics, little work has been done to develop visual analytics tools that focus specifically on geographically networked phenomena. This thesis develops a variety of visualization methods to present data values and geospatial network relationships, which enables users to interactively explore the data. Users can investigate the connections in both virtual networks and geospatial networks and the underlying geographical context can be used to improve knowledge discovery. The focus of this thesis is on social media analysis and geographical hotspots optimization. A framework is proposed for social network analysis to unveil the links between social media interactions and their underlying networked geospatial phenomena. This will be combined with a novel hotspot approach to improve hotspot identification and boundary detection with the networks extracted from urban infrastructure. Several real world problems have been analyzed using the proposed visual analytics frameworks. The primary studies and experiments show that visual analytics methods can help analysts explore such data from multiple perspectives and help the knowledge discovery process.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Analysis of ecosystem services provision in the Colombian Amazon using participatory research and mapping techniques

Over the last two decades indigenous peoples in the lower Caquetá River basin in Colombia have experienced detrimental changes in the provision of important ecosystem services in ways that have significant implications for the maintenance of their traditional livelihoods. To assess these changes we conducted eight participatory mapping activities and convened 22 focus group discussions. We focused the analysis on two types of change: (1) changes in the location of ecosystem services provisioning areas and (2) changes in the stock of ecosystem services. The focal ecosystem services include services such as provision of food, raw materials and medicinal resources. Results from the study show that in the past two decades the demand for food and raw materials has intensified and, as a result, locations of provisioning areas and the stocks of ecosystem services have changed. We found anecdotal evidence that these changes correlate well with socio-economic factors such as greater need for income generation, change in livelihood practices and consumption patterns. We discuss the use of participatory mapping techniques in the context of marginalized and data-poor regions. We also show how this kind of information can strengthen existing ecosystem-based management strategies used by indigenous peoples in the Colombian Amazon

Spatial genetic structure in the saddled sea bream (Oblada melanura [Linnaeus, 1758]) suggests multi-scaled patterns of connectivity between protected and unprotected areas in the Western Mediterranean Sea

Marine protected areas (MPAs) and networks of MPAs are advocated worldwide for the achievement of marine conservation objectives. Although the knowledge about population connectivity is considered fundamental for the optimal design of MPAs and networks, the amount of information available for the Mediterranean Sea is currently scarce. We investigated the genetic structure of the saddled sea bream ( Oblada melanura) and the level of genetic connectivity between protected and unprotected locations, using a set of 11 microsatellite loci. Spatial patterns of population differentiation were assessed locally (50-100 km) and regionally (500-1000 km), considering three MPAs of the Western Mediterranean Sea. All values of genetic differentiation between locations (Fst and Jost's D) were non-significant after Bonferroni correction, indicating that, at a relatively small spatial scale, protected locations were in general well connected with non-protected ones. On the other hand, at the regional scale, discriminant analysis of principal components revealed the presence of a subtle pattern of genetic heterogeneity that reflects the geography and the main oceanographic features (currents and barriers) of the study area. This genetic pattern could be a consequence of different processes acting at different spatial and temporal scales among which the presence of admixed populations, large population sizes and species dispersal capacity, could play a major role. These outcomes can have important implications for the conservation biology and fishery management of the saddled sea bream and provide useful information for genetic population studies of other coastal fishes in the Western Mediterranean Sea

Structuring functional groups of aquatic insects along the resistance/resilience axis when facing water flow changes

Understanding how differences in intensity and frequency of hydrological disturbances affect the resistance and resilience of aquatic organisms is key to manage aquatic systems in a fast-changing world. Some aquatic insects have strategies that improve the permanence (resistance), while others use strategies that favor recolonization (resilience). Therefore, we carried out a manipulative experiment to understand the influence of functional characteristics of aquatic insects in their permanence and recolonization against hydrological disturbances in streams in the biodiversity hotspot of the Cerrado of Brazil. We placed 200 artificial substrates in five streams and submitted them to changing water flow regimes that differed both in frequency and intensity, and we observed the response of the aquatic community for 39 days. We used a hierarchical Bayesian approach to estimate the probabilities of permanence and recolonization of each life strategy group (nine groups). We observed that the most intense changes in the water flow tended to affect the permanence of almost all groups, but the intensity of this effect reduced over time. On the other hand, less frequent disturbances, regardless of intensity, tended to reduce the permanence of most groups of aquatic insects over time. The different effects of disturbance intensity may have been related to a greater recolonization capacity of some groups. The results we present are worrisome in a scenario of reduced riparian vegetation around streams and with the expectation of precipitation becoming more concentrated in shorter periods of time due to climate change in the Cerrado hotspot, reducing the occurrence of many groups of aquatic insects in their habitat, particularly those with traits associated with resistance against hydrological disturbance

A data-driven approach to road accidents in the municipality of Lisbon

Traffic accidents in urban areas lead to reduced quality of life and social inequality in cities, specially in third world countries. The growth of the urban mesh and the population density is seldom accompanied by the development or sizing of the road infrastructure. It is a fact that the number and severity of road accidents in Portugal have been decreasing over the last thirty years, bringing us closer to the European average. However, despite these facts, the situation remains worrying. Despite the adoption of programs such as the European Commission Road Safety Program and the recent EU Road Safety Policy Framework 2021-2030 or, on a national basis, the PENSE 2020 - National Strategic Plan for Road Safety the number of road accidents with victims in the district of Lisbon is still higher than the European average. Thus, and for this dissertation, we conducted an exploratory data analysis (EDA) on the combined data of traffic incidents recorded in the occurrence management system of the Lisbon Fire Brigade Regiment (RSB) and the road accidents reported to ANSR by the security forces (GNR and PSP) through the Statistical Bulletin of Traffic Accidents (BEAV). Furthermore, with data from occurrences in the Municipality of Lisbon between 2010 and 2020, to identify the existence of Black Spots in Lisbon's roads and which are the most significant and contributing factors to explain their existence. The data on road accidents were also georeferenced to capitalize their spatial existence and, consequently, better understand the existing spatial patterns and risk factors. Subsequently, through the use of the ArcGIS Pro we apply the algorithms of the Kernel Density and Hot Spot Analysis (Getis-Ord Gi*) tools, identifying the existence of the black spots, and that human, environmental and circumstantial factors have an influence on the severity of accidents, being the content validity guaranteed through an expert committee. This way, our research goal is to contribute to identify accident concentration areas in the city of Lisbon (hotspots), considering their influencing conditions.Os acidentes de trânsito em áreas urbanas conduzem à redução da qualidade de vida e à desigualdade social nas cidades, especialmente nos países em desenvolvimento. O crescimento da malha urbana, assim como, a densidade populacional raramente é acompanhada pelo desenvolvimento ou dimensionamento da infraestrutura rodoviária. É um facto que o número e a gravidade dos acidentes rodoviários em Portugal têm vindo a diminuir ao longo dos últimos trinta anos, o que permitiu aproximarmos da média Europeia, apesar destes factos a situação continua a ser preocupante. Apesar da adoção de programas como o Programa de Segurança Rodoviária da Comissão Europeia ou, numa base nacional, o PENSE 2020 - Plano Estratégico Nacional para a Segurança Rodoviária os números de acidentes de viação com vítimas no distrito de Lisboa continuam a ser mais elevados do que a média europeia. Desta forma e para efeitos deste trabalho realizamos uma análise de dados exploratória (AED) aos dados dos incidentes de transito registados no sistema de gestão de ocorrências do Regimento de Sapadores Bombeiros de Lisboa e a os dados de acidentes rodoviários reportados à ANSR pelas forças de segurança (GNR e PSP) através do Boletim Estatístico de Acidentes de Viação (BEAV) e ocorridos no concelho de Lisboa entre 2010 e 2020 por forma a identificar a existência de Pontos Negros nas vias de Lisboa e quais os fatores mais significantes e contribuintes que permitam explicar a sua existência. Os dados relativos aos acidentes rodoviários foram também georreferenciados para capitalizar a sua existência espacial e, consequentemente, compreender melhor os padrões espaciais existentes e os fatores de risco. Posteriormente através do recurso ArcGIS Pro aplicaram-se os algoritmos das ferramentas Densidade de Kernel e Hot Spot Analysis (Getis-Ord Gi*), identificando a existência dos pontos negros, e que fatores humanos, ambientais e circunstanciais têm influência na gravidade dos acidentes e que algumas variáveis de exposição foram consideradas importantes na explicação da ocorrência dos mesmos, sendo a validade do conteúdo garantida através de uma comissão de especialistas. Pretende-se, assim, contribuir para a identificação das zonas de concentração de acidentes da cidade de Lisboa (hotspots), tendo em conta as suas condições influenciadoras. Potenciando a segurança rodoviária no município

Social preferences for ecosystem services in a biodiversity hotspot in South America

Identifying which ecosystem services are relevant to different stakeholders and understanding stakeholders’ perceptions of such services is useful for making informed decisions, especially in regions of the world where the achievement of biodiversity conservation goals is threatened by economically productive activities. In this article, we assess social preferences for ecosystem services in a biodiversity hotspot in central Chile. We use a consultative case study to ask local stakeholders (n = 70) from the Campana Peñuelas Biosphere Reserve to identify the most important ecosystem services the area provides for them and inquire about the perceived vulnerability of the services to changes in the future. We also explore the association between the perceived importance of ecosystem services and the sociodemographic and cultural characteristics of the respondents, which allows us to identify contrasting stakeholder perceptions of different ecosystem services. The most important services for local actors were the drinking water, fresh air and climate change control, genetic pool of plant communities in central Chile, and educational value. From the perspective of local actors, the services that could be threatened by negative changes in the future in terms of their provision included the possibilities of developing conservation activities focused on iconic threatened animal and plant species, water regulation, food from agriculture, and drinking water. Contrasting perceptions about the importance of ecosystem services emerged among stakeholders. While small farmers and members of local organizations attributed higher importance values to provisioning services, scientists and rangers and administrators of protected areas as well as teachers, NGO members and local government employees attributed more importance to the regulating and cultural services associated with threatened species. Our results can serve as a source of information for the planning and decision-making processes related to the search for socially and ecologically sustainable solutions for land use managemen

A Competitive gaussian model and linear regression technique for modeling MST neuron receptive field responses for primate perception of self-motion

This thesis presents a linear regression technique applied to non-linear features extracted from a scaled Gaussian mixture model (SGMM) to describe the receptive field (RF) behavior of neurons in the Medial Superior Temporal region of the brain of Rhesus monkeys which viewed visual stimuli on a projector screen. The stimuli consist of simple and complex combinations of planar, circular, and radial motion and neuron responses were recorded in spikes/second. It is our goal to understand the neuronal responses of the primates to these stimuli and to create a model capable of predicting how the RFs in the primates\u27 neurons respond to novel stimuli simulating the effects of self- motion. The SGMM is trained in stages using a competitive algorithm where a speciated genetic algorithm competes against a custom greedy algorithm. The regions of each subject\u27s visual field which produce the most active neuron responses are identified as hotspot regions for that neuron. We strongly believe that the non-linear interaction between RFs can be explained by the relationship between hotspot and non-hotspot region behavior based on the direction of stimulus motion within each region. Our results show that the SGMM is capable of reasonably modeling and predicting firing rate response values for simple visual stimuli for a moderate number of data points, and that the linear model is capable of very accurately modeling and predicting firing rate response values for more complex stimuli for a small number of data points

Influencing operational policing strategy by predictive service analytics

Everyday there are growing pressures to ensure that services are delivered efficiently, with high levels of quality and with acceptability of regulatory standards. For the Police Force, their service requirement is to the public, with the police officer presence being the most visible product of this criminal justice provision. Using historical data from over 10 years of operation, this research demonstrates the benefits of using data mining methods for knowledge discovery in regards to the crime and incident related elements which impact on the Police Force service provision. In the UK, a Force operates over a designated region (macro-level), which is further subdivided into Beats (micro-level). This research also demonstrates differences between the outputs of micro-level and macro-level analytics, where the lower level analysis enables adaptation of the operational Policing strategy. The evidence base provided through the analysis supports decisions regarding further investigations into the capability of flexible neighbourhood policing practices; alongside wider operations i.e. optimal officer training times