47 research outputs found

    Mapping and Describing Geospatial Data to Generalize Complex Models: The Case of LittoSIM-GEN

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    For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding model (LittoSIM) to new territories. From this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into ABMs

    Mapping and Describing Geospatial Data to Generalize Complex Models: The Case of LittoSIM-GEN

    Get PDF
    For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding model (LittoSIM) to new territories. From this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into ABMs

    Urban Climate, Human behavior & Energy consumption: from LCZ mapping to simulation and urban planning (the MapUCE project)

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    International audienceThe MApUCE project aims to integrate in urban policies and most relevant legal documents quantitative data from urban microclimate, climate and energy.The primary objective of this project is to obtain climate and energy quantitative data from numerical simulations, focusing on urban microclimate and building energy consumption in the residential and service sectors, which represents in France 41% of the final energy consumption. Both aspects are coupled as building energy consumption is highly meteorologically dependent (e.g. domestic heating, air-conditioning) and heat waste impact the Urban Heat Island. We propose to develop, using national databases, a generic and automated method for generating Local Climate Zones (LCZ) for all cities in France, including the urban architectural, geographical and sociological parameters necessary for energy and microclimate simulations.As will be presented, previous projects on adaptation of cities to climate change have shown that human behavior is a very potent level to address energy consumption reduction, as much as urban forms or architectural technologies. Therefore, in order to further refine the coupled urban climate and energy consumption calculations, we will develop within TEB (and its Building Energy Module) a model of energy consumer behavior.The second objective of the project is to propose a methodology to integrate quantitative data in urban policies. Lawyers analyze the potential levers in legal and planning documents. A few “best cases” are also studied, in order to evaluate their performances. Finally, based on urban planning agencies requirements, we will define vectors to include quantified energy-climate data to legal urban planning documents. These vectors have to be understandable by urban planners and contain the relevant information.To meet these challenges, the project is organized around strongly interdisciplinary partners in the following fields: law, urban climate, building energetics, architecture, sociology, geography and meteorology, as well as the national federation of urban planning agencies.In terms of results, the cross-analysis of input urban parameters and urban micro-climate-energy simulated data will be available on-line as standardized maps for each of the studied cities. The urban parameter production tool as well as the models will be available as open-source. LCZ and associated urban (and social!) indicators may be integrated within the WUDAPT database
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