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Manual wheelchair users are more vulnerable, in situations such as road crossings, hazardous sidewalks or curbs and crossing of buildings and facilities threshold. Geospatial assistive technology (GAT) can help with route planning. However, it is important to ensure the usability of such products, as well as the satisfaction of persons with reduced mobility. The study's aim was (1) to develop and validate a questionnaire on the satisfaction of GAT, in English and French, and to (2) assess satisfaction, efficacy and efficiency of a GAT with manual wheelchair users following a filmed trial in a dense urban area.A methodological study was conducted (development of the questionnaire, assessment of its content validity, feasibility and practicability) followed by a trial and post-observations with the videos. Two questionnaires (English, French) were concurrently validated by two groups of experts (The Evaluation of satisfaction with geospatial assistive technology (ESGAT) consists in a user profile and their experience with the technology, followed by 12 satisfaction criteria rated from 1-not satisfied to 5-very satisfied. Both questionnaires were rated as feasible and practicable to complete. The usability of Google Maps Pedestrian routeing tool was measured as "moderate" by manual wheelchairs since the total satisfaction score at the ESGAT was 3.9/5 (quite satisfied). The items with the lowest score were navigation assistance, hands-free function and security. The GAT was effective (87.5% have completed their destination) but not efficient (37.5% needed help).IMPLICATIONS FOR REHABILITATIONFor manual wheelchair users paired with geospatial assistive technology:• A 10 minutes questionnaire was developed and validated to assess their satisfaction after testing aid in an urban area.• Satisfaction criteria to address are ease of access (service), learnability, hands-free function, ease of use for planning as well for navigating, transportability/ appearance, content, geographic information, effectiveness, efficiency, navigation assistance and security• A field test is necessary to ensure the effectiveness of the technology in avoiding or announcing potential obstacles such as sidewalk crossing ramp, damaged and congested sidewalk; sidewalk tilt (side slopes); thresholds at destination; verbal indication too soon or too late; incorrect indication; the arrow does not indicate the right direction; readjustment of the route needed; a lack of indication; and human intervention needed.

Purpose: To advance knowledge of specific usability criteria for Geospatial Assistive Technologies (GATs) and manual wheelchair users, and to develop a profile and expectations for potential future...

Background: Wheelchair users are increasingly using route planners and navigation systems to help them get around the city. The absence of a list of usability criteria for wheelchair user-centred design and recommending geospatial assistive technologies creates uncertainty about the choices to be made by rehabilitation clinicians and geographic information systems specialists. The aim of this study was to compile such a list by identifying usability criteria from standardized questionnaires linked to user interfaces and geospatial assistive technologies (GATs).Material and methods: We conducted a scoping review in ACM Digital Library, Inspec/Compendex and PsycINFO for the period 2005-2016 using keyword strategies. From 84 articles identified, after screening and exclusion procedures, 15 articles were selected. Data were extracted from them and reported in table 1 (relevant questionnaires listed in alphabetical order, type of user interface, population studied, psychometric properties, type of measurement scale and information about the construct, number of subscales and items) and in table 2 (usability criteria up to 20 items for the questionnaires, scales or constructs, pointing criteria as gold standard in physical rehabilitation and as in geographic information).Results: We identified 87 usability criteria in 12 standardized questionnaires in 15 articles (with at least two types of psychometric properties). There are 54 usability criteria that could be used in clinical situations concerning their potential applicability to GATs for wheelchair users: 20 are familiar to rehabilitation clinicians who recommend assistive technologies, 21 are generic to GATs while 13 are specific to mobile applications or voice recognition systems. It remains 34 criteria that are not actually familiar to clinicians: actual use, content (including content-clarity, content-color, content-consistency, content-credibility, content-legibility, content-relevance, content-trustworthy, and content-understandable), control-obviousness, customer service behavior, delivery format, design-application, ease of navigation, entry-point type, everyday words, fingertip-size controls, font, functions-expected, functions-integration, gestalt, graphics, habit, hierarchy, input, network externality, speech characteristics, structure, subtle animation, time spent waiting, transition, user goal orientation and verbosity.Conclusions: More research is needed to develop a questionnaire specific to geospatial assistive technologies for wheelchair users linked with mobile applications and information content.Implications for rehabilitationFor manual wheelchair users paired with geospatial assistance technology, "effectiveness, efficiency, learnability and satisfaction" are essential criteria for route planning and navigation task.Clinicians can optimize the selection of a geospatial assistance technology considering 16 criteria: appearance, assistance-human support, comfort, ease of holding, ease of use, emotional aspect, endurance, facilitating conditions, intention to use, minimal memory load, physical effort, price value, simplicity, social influence, training and usefulness.Clinicians should have in mind that WC users want to plan a route with as few obstacles as possible. Information on the screen should be accessible to WC users (text, contrast, symbols, graphics, photos, voice, vibration, route views). Hands are occupied with the hand rims, WC users would prefer "listen to verbal" instructions to continue their route instead of looking on their electronic device. 34 criteria are specific for route planning and navigation task.

Recent advances in geospatial technologies have made available large amount of geospatial data. Meanwhile, new developments in Internet and communication technologies created a shift from isolated geospatial databases to ad hoc networks of geospatial data sources, where data sources can join or leave the network, and form groups to share data and services. However, effective integration and sharing of geospatial data among these data sources and their users are hampered by semantic heterogeneities. These heterogeneities affect the spatial, temporal and thematic aspects of geospatial concepts. There have been many efforts to address semantic interoperability issues in the geospatial domain. These efforts were mainly focused on resolving heterogeneities caused by different and implicit representations of the concepts. However, many approaches have focused on the thematic aspects, leaving aside the explicit representation of spatial and temporal aspects. Also, most semantic interoperability approaches for networks have focused on automating the semantic mapping process. However, the ad hoc network structure is continuously modified by source addition or removal, formation of groups, etc. This dynamic aspect is often neglected in those approaches. This paper proposes a conceptual framework for real time semantic interoperability in ad hoc networks of geospatial data sources. The conceptual framework presents the fundamental elements of real time semantic interoperability through a hierarchy of interrelated semantic states and processes. Then, we use the conceptual framework to set the discussion on the achievements that have already been made, the challenges that remain to be addressed and perspectives with respect to these challenges.

Recent advances in sensor and platform technologies, such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data being produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally referred to Common DataBase, which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high-performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as the run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0, which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

One of the main challenges in Coastal Erosion Risk Assessment (CERA) is integrating and analysis of conflicting data in various time periods and spatial scales through dissimilar environmental, social, and economic criteria. Currently, Geographical Information Systems (GIS) are widely used in risk assessment despite their drawbacks and limitations as transactional systems for multi-scales, multi-epochs, and multi-themes analysis. Hence, an analytical conceptual framework is proposed in this paper based on geospatial business intelligence paradigm to develop a Spatial Multidimensional Conceptual Model (SMCM) to assess coastal erosion risk. The model is designed based on Spatial On-Line Analytical Processing (SOLAP) platform, on the top of both analytical and transactional paradigms, to allow fast synthesis of cross-tabulated data and easy comparisons over space, scales, epochs, and themes. This objective is achieved through a comprehensive integration of multiple environmental, social, and economic criteria as well as their interactions at various scales. It also takes into account multiple elements at risk such as people, infrastructure, and built environment as different dimensions of analysis. Using this solution allows decision makers to benefit from on-demand, interactive, and comprehensive information in a way that is not possible using GIS alone. The developed model can easily be adapted for any other coastal region through the proposed framework to perform risk assessment. The advantages and drawbacks of the proposed framework are also discussed and new research perspectives are presented.

GIScience 2016 Short Paper Proceedings Modelling Vague Shape Dynamic Phenomena from Sensor Network data using a Decentralized Fuzzy Rule-Based Approach Roger Cesarie Ntankouo Njila 1 , Mir Abolfazl Mostafavi 1 , Jean Brodeur 1 Centre de Recherche en Geomatique, 2314 Pavillon Casault; Universite Laval, Quebec, Canada, G1K 7P4 Email: roger-cesarie.ntankouo-njila.1@ulaval.ca, Mir-Abolfazl.Mostafavi@scg.ulaval.ca, recherchegeosemantic@videotron.ca Abstract Modelling dynamic phenomena of vague shape from sensor data is still a challenging problem for many applications. In this paper, we propose a decentralized fuzzy rule-based approach based on fuzzy object model to build a more realistic spatiotemporal representation for such phenomena. This approach has been successfully implemented in a simulation case of bushfire monitoring, showing advantages for spatial decision making in a disaster management context. Keywords: sensors, sensor data, fuzzy objects, disaster management, spatial decision support 1. Introduction Extracting geospatial information from geosensor data can help to better understand a complex phenomenon for real time decision making process (Sadeq et al. 2013). Several approaches are used for the extraction of geospatial information from sensor data. Many of these approaches are developed based on the assumption that monitored phenomena are of crisp shape with well- defined boundaries. However, many dynamic phenomena have vague spatial boundaries, and their accurate detection and extraction from sensor data is a challenging problem. In this paper we propose a decentralized fuzzy rule-based approach to address this problem. In the proposed method, sensors detect vague shape phenomena using a fuzzy logic reasoning approach and collaborate with their neighboring sensors to infer vague spatial extent of the phenomena and its dynamics. We adopt Crisp-Fuzzy objects (Pauly and Schneider 2008) as a more realistic model for large scale and vague shape dynamic phenomena. This paper is organized as follows. After a brief background presented in section 2, section 3 describes the proposed approach implemented in section 4 for a bushfire simulation case showing it applicability for real time spatial decision process in disaster management. Section 5 presents conclusions and future works. 2. Background Spatial computing can be undertaken in a sensor system following a centralized (all data are sent to process center), a decentralized (located at sensor site or other site) or a hybrid approach (Chong and Kumar 2003). Crisp vector objects are extracted in the existing approaches using statistics or filters (Chintalapudi and Govindan 2003) or qualitative reasoning (Guan and Duckham 2009). Real-world phenomena are inherently uncertain (Carniel et al. 2015). Crisp-Fuzzy objects model (Pauly and Schneider 2008) is an interesting candidate for the representation of such phenomenon. In this model the geometry of object is composed of a kernel and a conjecture part, the kernel part belongs definitely and always to the vague object but one can’t say with certainty whether conjecture part considered as the broad boundary belongs to the vague object.

Large volumes of geospatial data are increasingly made available through dynamic networks, such as ad hoc networks. Consequently, new adapted query propagation approaches that take into account geospatial aspects of data are needed. Different existing query propagation approaches use various criteria to select relevant sources. In addition, many approaches rely on existing semantic mappings between sources; however, in ad hoc networks, sources move autonomously and in a dynamic fashion. Our goal is rather to reduce the number of sources that must be accessed to answer a query and, therefore, to reduce the volume of semantic mappings that needs to be computed to answer the query. In this paper, we propose three real time query propagation strategies to address this issue. Those strategies reproduce the behavior of members of a social network. The strategies are designed to be part of a real time semantic interoperability framework for ad hoc networks of geospatial databases. The strategies have been formalized with the Lightweight Coordination Calculus (LCC), which support distributed interactions based on social norms and constraints. The implementation and testing of the strategies show that they complement each other to provide optimal query answers.

Efficient collaboration between participants is fundamental for urban planning and design processes, but it is not necessarily easy to achieve. This limitation depends on several factors including differences in participants' backgrounds and the limitations and the complexity of the tools used to support those process. Furthermore, the collaborative component of urban planning and design projects is often limited to meetings where designs and plans are assembled and discussed. The solution presented in this paper, aims at overcoming those problems through a collaborative geospatial augmented reality application. The proposed system integrates innovative technologies of augmented reality with 3D modelling and spatial analysis tools. Results of our experimentations demonstrate the potential of such a system for improving interactive and collaborative urban design. This paper provides a comparison of our approach with existing ones and proposes future developments in the field. RESUME. Si la bonne collaboration entre participants est fondamentale dans les processus d'amenagement et de design, elle n'est pas toujours facile a mettre en œuvre. Differents facteurs expliquent cette difficulte, allant des differences d'origines des participants, a la complexite des outils utilises par les experts. Par ailleurs, la composante collaborative des projets d'amenagement et de design est souvent limitee aux seules phases d'assemblage et de discussions sur les plans. Precisement, dans cet article nous proposons une solution fondee sur une application de realite augmentee geospatiale collaborative. Le systeme propose associe des technologies de realite augmentee innovantes et des outils de modelisation 3D et d'analyse spatiale. Les resultats de nos tests montrent la pertinence de ce type de systeme pour ameliorer l'interaction et la collaboration en design urbain. Cet article fournit une comparaison entre l'approche developpee et les approches existantes et propose finalement des voies de developpement futures.

Geospatial modelling of the marine pelagic ecosystem is challenging due to its dynamic and volumetric nature. Consequently, conventional oceanographic spatial analysis of this environment is in a 2D environment, limited to static cutting planes in horizontal and vertical sections to present various phenomena. In this paper, we explore the contribution of recent 3D development in GIS and in scientific visualization tools for representation and analyses of oceanographic data sets. The advantages of a 3D solution are illustrated with a 3D geospatial voxel representation of water masses distribution in the southeastern Beaufort Sea (west of the Canadian Arctic).

LiDAR technology can provide very detailed and highly accurate geospatial information on an urban scene for the creation of Virtual Geographic Environments (VGEs) for different applications. However, automatic 3D modeling and feature recognition from LiDAR point clouds are very complex tasks. This becomes even more complex when the data is incomplete (occlusion problem) or uncertain. In this paper, we propose to build a knowledge base comprising of ontology and semantic rules aiming at automatic feature recognition from point clouds in support of 3D modeling. First, several modules for ontology are defined from different perspectives to describe an urban scene. For instance, the spatial relations module allows the formalized representation of possible topological relations extracted from point clouds. Then, a knowledge base is proposed that contains different concepts, their properties and their relations, together with constraints and semantic rules. Then, instances and their specific relations form an urban scene and are added to the knowledge base as facts. Based on the knowledge and semantic rules, a reasoning process is carried out to extract semantic features of the objects and their components in the urban scene. Finally, several experiments are presented to show the validity of our approach to recognize different semantic features of buildings from LiDAR point clouds.

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.

Semantic interoperability is needed to support meaningful data exchanges in distributed environments such as ad hoc networks of geospatial databases and geospatial web services. Even with the increasing popularity of ontologies to capture semantics, semantics of geospatial data are often too weak to support meaningful exchanges. In this chapter, the authors argue that semantically weak geospatial data can be enriched to enhance semantic interoperability. They propose a conceptual architecture designed to support enhanced semantic interoperability in dynamic networks that focuses on semantic enrichment. The proposed conceptual architecture includes a coalition management module, an ontology enrichment module, and a semantic mapping module; the modules perform different types of semantic enrichment and can support various semantic interoperability tasks. Within the different enrichment methods, the authors explain the role of global ontologies, arguing that they play a key role in a semantic interoperability framework. Finally, the authors illustrate with an application example the possibilities of such architecture.

Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available through distributed environments. It is also a challenge for the ongoing development of the Geospatial Semantic Web.Data brokers provide searchable repositories through which users can generally retrieve the requested data. But generally, these mechanisms lack the capacity to find and combine complementary data from multiple sources. However, such capacity is needed to answer complex queries. In this paper, we propose a new type of system that supports geospatial data retrieval from multiple and complementary sources. The system uses the Semantic Query-Enhanced Web Rule Language (SQWRL) to support reasoning with complex queries and to enable combination of complementary and heterogeneous data. We have developed and included in this system a query expansion method for the resolution of semantic heterogeneities. The proposed system is illustrated with an application example.

Tracking, monitoring and management of moving objects become increasingly important in modern geospatial application. An important example of such applications is monitoring and management of a dynamic scene captured bya network of videos or sensors for ensuring for example the security of the people during a public event, or for leading emergency or rescue teams in real environment. While current GIS are widely used to represent and manage spatiotemporal phenomena, their applications for 3D dynamic environments are very limited due to the 2D static nature of most of existing spatial data structures. In this paper, we first present a review of important requirements for efficient management of a dynamic scene. Next, we present a 3D kinetic data structure based on Delaunay tetrahedralization and Voronoi diagram that allows representation of static and moving objects and their interactions in a 3D dynamic environment, simultaneous tracking of a large number of moving objects, detection of the important events and collisions and other interesting analysis of a dynamic scene. Finally, we discuss other potentials and limitations of the proposed model and suggest some new research avenues regarding the improvement of the proposed model.

The effective management of disasters requires providing relevant and right information to the concerned decision makers. By its nature, disaster management involves multiple actors and organizations, potentially implying a significant volume of geospatial data coming from heterogeneous and autonomous geospatial data sources. Integration of these data sources is difficult not only because of the semantic heterogeneity of data but also because of the dynamic nature of the reality that is studied. The dynamic aspect of the reality has a direct impact in the conceptualisation of such a reality by adding different event categories to the domain ontology, thus making more complicated to apply existing methods for the mapping and integration of ontologies. In this article, we highlight some problems of heterogeneity that complicate the integration of ontologies composed of objects and events concepts; we also propose a similarity model designed to support mapping of these ontologies.

In a decision-making context, multidimensional geospatial databases are very important They often represent data coming from heterogeneous and evolving sources Evolution of multidimensional structures makes difficult, even impossible answering to temporal queries, because of the lack of relationships between different versions of spatial cubes created at different time This paper proposes a semantic similarity model redefined from a model applied in the ontological field to establish semantic relations between data cubes The proposed model integrates several types of similarity components adapted to different hierarchical levels of dimensions in multidimensional databases and also integrates similarity between features of concepts The proposed model has been applied to a set of specifications from different inventory in Montmorency Forest in Canada Results show that the proposed model improves precision and recall compared to the original model Finally, further investigation is suggested in order to integrate the proposed model to SOLAP tools as future works.