Disaggregating Ethno-Nationalist Civil Wars: A Dyadic Test of Exclusion Theory

Contemporary conflict research usually measures the influence of ethnicity on conflict by capturing ethnic constellations as country-based indices, such as ethnic fractionalization or polarization. However, such aggregated measures are likely to conceal the actual operation of actor-specific mechanisms. In this article, therefore, we introduce a disaggregated model that measures ethnic groups' access to power. We do so by disaggregating both ethnicity and conflict to the level of explicitly geo-coded center-periphery dyads. This procedure allows us to measure the power balance between politically excluded ethnic groups and dominant actors in terms of group sizes, distances between the center and the periphery, and the roughness of the latter's terrain. We rely on geographic information systems (GIS) to compute demographic and ethno-geographic variables. The dyadic analysis enables us to show that exclusion of powerful ethnic minorities increases the likelihood of conflict considerably. In addition, we show that the risk of conflict is positively associated with the extent of rough terrain in the peripheral group's home region and its distance from the political cente

An attraction-based cellular automaton model for generating spatiotemporal population maps in urban areas

We develop a cellular automaton (CA) model to produce spatiotemporal population maps that estimate population distributions in an urban area during a random working day. The resulting population maps are at 50 m and 5 minutes spatiotemporal resolution, showing clearly how the distribution of population varies throughout a 24-hour period. The maps indicate that some areas of the city, which are sparsely populated during the night, can be densely populated during the day. The developed CA model assumes that the population transition trends follow dynamics and propagation patterns similar to a contagious disease. Thus, our model designed to change the states of each grid cell (stable or dynamic) in a way that is similar to changes in the condition of individuals who are exposed to an infectious disease (susceptible or infected). In addition, the modeling space is informed by several geographic features, such as the transport routes, land-use categories, and population attraction points. The model is geosimulated for the city of Trondheim in Norway, where the synthetic day population could be validated using an estimated day-population map based on the registered workplace addresses and employee statistics. The generated maps can be used to estimate a value for the population-at-risk in the wake of a major disaster that occurs in an urban area at any time of a day. In addition to assessing exposure to hazards, the resulting maps also reveal movement patterns, transition trends, peak hours, and activity levels. Possible applications range from public safety, disaster management, transport modeling, and urban growth studies to strategic energy distribution planning.acceptedVersio

Map functions to facilitate situational awareness during emergency events

Emergency events such as floods and wildfires are handled by various responders and at various levels: strategic, tactical, and operational. To facilitate situational awareness, emergency responders require customized map-based decision support systems that are tailored to specific needs depending on the responders’ organizational affiliation, role, objectives, and occupationally specific knowledge. As a result, the systems are equipped with manifold map functions. However, the diversity of map-based emergency tools in use impedes gaining common user skills among their target audiences and thus, requires a systematic overview. Through a multistep research process, this study was to: investigate the requirements for support from map-based tools expressed by various emergency responders in Norway, identify desired map functions, and categorize those functions to facilitate an overview. Six stages constituted our workflow: meetings with Norwegian emergency responders, survey on selected map-based tools, interviews with designers and users of tools, a table-top exercise, theoretical considerations, and validation with stakeholders. This study contributes to the state of the art by systematizing and structuring knowledge about map functions that facilitate situational awareness. In turn, it helps developing and optimizing functionality of map-based tools depending on needs of specific emergency responders.publishedVersionPaid open acces

Using prospective methods to identify fieldwork locations favourable to understand divergences in health care accessibility

Central to this article is the issue of choosing sites for where a fieldwork could provide a better understanding of divergences in health care accessibility. Access to health care is critical to good health, but inhabitants may experience barriers to health care limiting their ability to obtain the care they need. Most inhabitants of low-income countries need to walk long distances along meandering paths to get to health care services. Individuals in Malawi responded to a survey with a battery of questions on perceived difficulties in accessing health care services. Using both vertical and horizontal impedance, we modelled walking time between household locations for the individuals in our sample and the health care centres they were using. The digital elevation model and Tobler’s hiking function were used to represent vertical impedance, while OpenStreetMap integrated with land cover map were used to represent horizontal impedance. Combining measures of walking time and perceived accessibility in Malawi, we used spatial statistics and found spatial clusters with substantial discrepancies in health care accessibility, which represented fieldwork locations favourable for providing a better understanding of barriers to health access.publishedVersio

Using locational data in a novel mixed-methods sequence design: Identifying critical health care barriers for people with disabilities in Malawi

The primary aim of this study was to determine which health care barriers were most important for people with disabilities in Malawi. To accomplish this, we devised a sequential mixed-methods research design that integrated locational survey data and qualitative data from field studies. Our secondary aim was to evaluate this research design not only as a design-solution to our particular research objective, but as a tool with more general applicability within social sciences. Malawi has one of the most underserved health service populations in the world with chronic resource shortages and long travel distances where people with disabilities are at a particular disadvantage. Nevertheless, our results show that even in a resource scarce society such as Malawi it is the interpersonal relationships between patients and health service providers that has the largest impact on the perception of access among patients. Our results also suggest that the sequential mixed-methods design is effective in guiding researchers towards models with strong specifications.publishedVersio

Map-based interfaces for common operational picture

Common operationalpicture (COP) map-based interfacesdisplay operational information to support integrationofemergency responders. Such interfacesintegrate different subsystems and present the resulting information into an overview for enabling situation awareness. Literature shows that they are often developed from non-user-centric perspectives and are defined in technological terms that arenot adequately capturing the users’ needs. Therefore,theaim of this particular work in progressis to get insight into the features and the role of COP map-based interfaces currently being used in Norway to (1) examine theircontent, functionality, and design;and(2) to understand how such displays are incorporated into the servicecontext.This studystructuresthe knowledge on map displays that constitute part of the COP services.Using workshopand interviews with the developers and usersof existing COP map services, we identify requirements for a common operational symbology and common operational functionality to improvesuch map services andmake them interoperable.publishedVersio

Evaluating Flood Exposure for Properties in Urban Areas Using a Multivariate Modelling Technique

Urban flooding caused by heavy rainfall is expected to increase in the future. The main purpose of this study was to investigate the variables characterizing the placement of a house, which seem to have an impact when it comes to the exposure to floods. From the same region in Norway, data from 347 addresses were derived. All addresses were either associated with insurance claims caused by flooding or were randomly selected. A multivariate statistical model, Partial Least Square Regression (PLS), was used. Among others, the analysis has shown that the upstream, sealed area is the most significant variable for characterizing properties’ exposure to urban flooding. The model confirms that flooding tends to occur near old combined sewer mains and in concave curvature, and houses located in steep slopes seem to be less exposed. Using this method, it is possible to rank and quantify significant exposure variables contributing to urban floods within a region. Results from the PLS-analysis might provide important input to professionals, when planning and prioritizing measures. It can also predict flood-prone areas and make residents aware of the risks, which may induce them to implement preventive measures.publishedVersio

Sharing Incident and Threat Information for Common Situational Understanding

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VisAdapt: A visualization tool to support climate change adaptation

In this article we present the design and implementation of the web-based visualization tool VisAdapt, developed to support homeowners in the Nordic countries to assess anticipated climate change and climate related risks which are expected to negatively impact their living conditions. The tool guides the user through a three-step visual exploration process to facilitate the exploration of risks and adaptation measures, specifically adapted to the user. VisAdapt has been developed over the course of two years in close collaboration with domain experts and end users to ensure the validity of the included data and the efficiency of the visual interface. Although VisAdapt is designed for Nordic homeowners, the insights gained from the development process and the lessons learned from the project could be valuable to researchers in a wide area of application domains.acceptedVersionnivå

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large-scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS-telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat-use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat-use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat-use studiespublishedVersio