The use of GIS in Brownfield redevelopment

In recent years, the issue of Brownfield site development - the re-use of previously used urban land - has gained a significant place in the planning agenda. However, not all Brownfield sites are derelict or contaminated land, some are significant as environmental amenities - be it part of wider ecosystem or a green area for the local population. The growing concern to include environmental aspects into the public debate have lead the Environment Agency, the Jackson Environment Institute and the Centre for Advanced Spatial Analysis to commission a short term pilot study to evaluate the contribution of a GIS for decision support and for "discussion support".In this paper, we describe how the state-of-the-art in geographic information (GI) and GI Science (GISc) can be used in a short term and limited project to achieve a practical and usable system. We are drawing on developments in information availability, as made accessible through the World Wide Web and research themes in GISc ranging from Multimedia GIS to Public Participation GIS

Can urban metabolism models advance green infrastructure planning? Insights from ecosystem services research

Urban metabolism studies have gained momentum in recent years as a means to assess the environmental performance of cities and to point to more resource-efficient strategies for urban development. Recent literature reviews report a growing number of applications of the industrial ecology model for Material Flow Analysis (MFA) in the design of the built environment. However, MFA applications in green infrastructure development are scarce. In this article, we argue that: i) the use of MFA in green infrastructure practice can inform decision-making towards more resource-efficient urban planning; ii) the ecosystem service concept is critical to operationalize MFA for green infrastructure planning and design, and, through this, can enhance the impact of urban metabolism research on policy making and planning practice. The article draws from a systematic review of literature on urban ecosystem services and benefits provided by green infrastructure in urban regions. The review focuses on ecosystem services that can contribute to a more energy-efficient and less carbon-intensive urban metabolism. Using the Common International Classification of Ecosystem Services as a baseline, we then discuss opportunities for integrating energy provision and climate regulation ecosystem services in MFA. Our discussion demonstrates that the accounting of ecosystem services in MFA enables expressing impacts of green infrastructure on the urban energy mix (renewable energy provision), the magnitude of energy use (mitigation of building energy demand), and the dynamics of biogeochemical processes in cities (carbon sequestration). We finally propose an expanded model for MFA that illustrates a way forward to integrate the ecosystem service concept in urban metabolism models and to enable their application in green infrastructure planning and design

Modeling emergency management data by UML as an extension of geographic data sharing model: AST approach

Applying GIS functionality provides a powerful decision support in various application areas and the basis to integrate policies directed to citizens, business, and governments. The focus is changing toward integrating these functions to find optimal solutions to complex problems. As an integral part of this approach, geographic data sharing model for Turkey were developed as a new approach that enables using the data corporately and effectively. General features of this model are object-oriented model, based on ISO/TC211 standards and INSPIRE Data Specifications, describing nationwide unique object identifiers, and defining a mechanism to manage object changes through time. The model is fully described with Unified Modeling Language (UML) class diagram. This can be a starting point for geographic data providers in Turkey to create sector models like Emergency Management that has importance because of the increasing number of natural and man-made disasters. In emergency management, this sector model can provide the most appropriate data to many "Actors" that behave as emergency response organizations such as fire and medical departments. Actors work in "Sectors" such as fire department and urban security. Each sector is responsible for "Activities" such as traffic control, fighting dire, emission, and so on. "Tasks" such as registering incident, fire response, and evacuating area are performed by actors and part of activity. These tasks produce information for emergency response and require information based on the base data model. By this way, geographic data models of emergency response are designed and discussed with "Actor-Sector-Activity-Task" classes as an extension of the base model with some cases from Turkey

Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages

Model-driven design of context-aware applications

In many cases, in order to be effective, software applications need to allow sensitivity to context changes. This implies however additional complexity associated with the need for applications’ adaptability (being capable of capturing context, interpreting it and reacting on it). Hence, we envision 3 ‘musts’ that, in combination, are especially relevant to the design of context-aware applications. Firstly, at the business modeling level, it is considered crucial that the different possible context states can be properly captured and modeled, states that correspond to certain desirable behaviors. Secondly, it must be known what are the dependencies between the two, namely between states and behaviors. And finally, what is valid for application design in general, business needs are to be aligned to application solutions. In this work, we address the mentioned challenges, by approaching the notion of context and extending from this perspective a previously proposed business-software alignment approach. We illustrate our achieved results by means of a small example. It is expected that this research contribution will be useful as an additional result concerning the alignment between business modeling and software design

Future capacity growth of energy technologies: are scenarios consistent with historical evidence?

Future scenarios of the energy system under greenhouse gas emission constraints depict dramatic growth in a range of energy technologies. Technological growth dynamics observed historically provide a useful comparator for these future trajectories. We find that historical time series data reveal a consistent relationship between how much a technology’s cumulative installed capacity grows, and how long this growth takes. This relationship between extent (how much) and duration (for how long) is consistent across both energy supply and end-use technologies, and both established and emerging technologies. We then develop and test an approach for using this historical relationship to assess technological trajectories in future scenarios. Our approach for “learning from the past” contributes to the assessment and verification of integrated assessment and energy-economic models used to generate quantitative scenarios. Using data on power generation technologies from two such models, we also find a consistent extent - duration relationship across both technologies and scenarios. This relationship describes future low carbon technological growth in the power sector which appears to be conservative relative to what has been evidenced historically. Specifically, future extents of capacity growth are comparatively low given the lengthy time duration of that growth. We treat this finding with caution due to the low number of data points. Yet it remains counter-intuitive given the extremely rapid growth rates of certain low carbon technologies under stringent emission constraints. We explore possible reasons for the apparent scenario conservatism, and find parametric or structural conservatism in the underlying models to be one possible explanation

An Empirical Bayes Approach for Distributed Estimation of Spatial Fields

In this paper we consider a network of spatially distributed sensors which collect measurement samples of a spatial field, and aim at estimating in a distributed way (without any central coordinator) the entire field by suitably fusing all network data. We propose a general probabilistic model that can handle both partial knowledge of the physics generating the spatial field as well as a purely data-driven inference. Specifically, we adopt an Empirical Bayes approach in which the spatial field is modeled as a Gaussian Process, whose mean function is described by means of parametrized equations. We characterize the Empirical Bayes estimator when nodes are heterogeneous, i.e., perform a different number of measurements. Moreover, by exploiting the sparsity of both the covariance and the (parametrized) mean function of the Gaussian Process, we are able to design a distributed spatial field estimator. We corroborate the theoretical results with two numerical simulations: a stationary temperature field estimation in which the field is described by a partial differential (heat) equation, and a data driven inference in which the mean is parametrized by a cubic spline

Cohesion, team mental models, and collective efficacy: Towards an integrated framework of team dynamics in sport

A nomological network on team dynamics in sports consisting of a multi-framework perspective is introduced and tested. The aim was to explore the interrelationship among cohesion, team mental models (TMM), collective-efficacy (CE), and perceived performance potential (PPP). Three hundred and forty college-aged soccer players representing 17 different teams (8 female and 9 male) participated in the study. They responded to surveys on team cohesion, TMM, CE and PPP. Results are congruent with the theoretical conceptualization of a parsimonious view of team dynamics in sports. Specifically, cohesion was found to be an exogenous variable predicting both TMM and CE beliefs. TMM and CE were correlated and predicted PPP, which in turn accounted for 59% of the variance of objective performance scores as measured by teams’ season record. From a theoretical standpoint, findings resulted in a parsimonious view of team dynamics, which may represent an initial step towards clarifying the epistemological roots and nomological network of various team-level properties. From an applied standpoint, results suggest that team expertise starts with the establishment of team cohesion. Following the establishment of cohesiveness, teammates are able to advance team-related schemas and a collective sense of confidence. Limitations and key directions for future research are outlined

Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users