ABSTRACT:In recent years, 3D virtual indoor/outdoor urban modelling becomes a key spatial information framework for many civil and engineering applications such as evacuation planning, emergency and facility management. For accomplishing such sophisticate decision tasks, there is a large demands for building multi-scale and multi-sourced 3D urban models. Currently, Building Information Model (BIM) and Geographical Information Systems (GIS) are broadly used as the modelling sources. However, data sharing and exchanging information between two modelling domains is still a huge challenge; while the syntactic or semantic approaches do not fully provide exchanging of rich semantic and geometric information of BIM into GIS or vice-versa. This paper proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graphs. The novelty of the proposed solution comes from the benefits of integrating BIM and GIS technologies into one unified model, so-called Integrated Geospatial Information Model (IGIM). The proposed approach consists of three main modules: BIM-RDF and GIS-RDF graphs construction, integrating of two RDF graphs, and query of information through IGIM-RDF graph using SPARQL. The IGIM generates queries from both the BIM and GIS RDF graphs resulting a semantically integrated model with entities representing both BIM classes and GIS feature objects with respect to the target-client application. The linkage between BIM-RDF and GIS-RDF is achieved through SPARQL endpoints and defined by a query using set of datasets and entity classes with complementary properties, relationships and geometries. To validate the proposed approach and its performance, a case study was also tested using IGIM system design. * Corresponding Author
This review compares and evaluates eleven Low Impact Development (LID) models on the basis of: (i) general model features including the model application, the temporal resolution, the spatial data visualization, the method of placing LID within catchments; (ii) hydrological modelling aspects including: the type of inbuilt LIDs, water balance model, runoff generation and infiltration; and (iii) hydraulic modelling methods with a focus on the flow routing method. Results show that despite the recent updates of existing LID models, several important features are still missing and need improvement. These features include the ability to model: multi-layer subsurface media, tree canopy and processes associated with vegetation, different spatial scales, snowmelt and runoff calculations. This review provides in-depth insight into existing LID models from a hydrological and hydraulic point of view, which will facilitate in selecting the best-suited model. Recommendations on further studies and LID model development are also presented.
Spatial information for coastal risk assessment is inherently uncertain. This uncertainty may be due to different spatial and temporal components of geospatial data and to their semantics. The spatial uncertainty can be expressed either quantitatively or qualitatively. Spatial uncertainty in coastal risk assessment itself arises from poor spatial representation of risk zones. Indeed, coastal risk is inherently a dynamic, complex, scale-dependent, and vague, phenomenon in concept. In addition, representing the associated zones with polygons having well-defined boundaries does not provide a realistic method for efficient and accurate representing of the risk. This paper proposes a conceptual framework, based on fuzzy set theory, to deal with the problems of ill-defined risk zone boundaries and the inherent uncertainty issues. To do so, the nature and level of uncertainty, as well as the way to model it are characterized. Then, a fuzzy representation method is developed where the membership functions are derived based on expert-knowledge. The proposed approach is then applied in the Perce region (Eastern Quebec, Canada) and results are presented and discussed.
To face the current economic context and better respond to market demand, many companies have started creating collaborations with different organizations inside and outside their supply chain. The objective is to have a greater visibility over supply chain operations, decision making and planning with positive impacts on the productivity and performance. In this paper, a collaborative framework is proposed to improve the business competitiveness of supply chains. Different dimensions including business and marketing, interfirm collaborative aspects, and quality and conformity in this framework are taken into account. Competence as an encompassing factor for human aspect to implement and operate the proposed framework is also scrutinized. All stated dimensions are then put together under one umbrella and implemented within a decision support system using online analytical processing database. The wood industry in Quebec North Shore region is chosen as an example of a supply chain and the case study throughout this paper.Index Terms-Competence, decision support system (DSS), interfirm collaborations, online analytical processing (OLAP), system of systems (SoS), wood supply chain.
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