The Experts below are selected from a list of 394206 Experts worldwide ranked by ideXlab platform
Sylvain Palominos - One of the best experts on this subject based on the ideXlab platform.
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OnoM@p : a Spatial Data Infrastructure dedicated to noise monitoring based on volunteers measurements
2016Co-Authors: Erwan Bocher, Gwendall Petit, Nicolas Fortin, Judicaël Picaut, Gwenael Guillaume, Sylvain PalominosAbstract:This talk presents an ideal Spatial Data Infrastructure (SDI) dedicated to noise monitoring based on volunteers measurements. Called OnoM@P, it takes advantage of the geospatial standards and open source tools to build an integrated platform to manage the whole knowledge about a territory and to observe its dynamics. It intends also to diffuse good practices to organize, collect, represent and process geospatial Data in field of acoustic researches. OnoM@p falls within the framework of the Environmental Noise Directive (END) 2002/49/CE. The system relies on the NoiseCapture Android application developed for allowing each citizen to estimate its own noise exposure with its smartphone.
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OnoM@p : a Spatial Data Infrastructure dedicated to noise monitoring based on volunteers measurements
2016Co-Authors: Erwan Bocher, Gwendall Petit, Nicolas Fortin, Judicaël Picaut, Gwenael Guillaume, Sylvain PalominosAbstract:The present paper proposes an ideal Spatial Data Infrastructure (SDI) dedicated to noise monitoring based on volunteers measurements. Called OnoM@P, it takes advantage of the geospatial standards and open source tools to build an integrated platform to manage the whole knowledge about a territory and to observe its dynamics. It intends also to diffuse good practices to organize, collect, represent and process geospatial Data in field of acoustic researches. OnoM@p falls within the framework of the Environmental Noise Directive (END) 2002/49/CE. The system relies on the NoiseCapture Android application developed for allowing each citizen to estimate its own noise exposure with its smartphone and to contribute to the production of community noisemaps.
Azadeh Keshtiarast - One of the best experts on this subject based on the ideXlab platform.
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Transport sustainability indicators for an enhanced urban analytics Data Infrastructure
Sustainable Cities and Society, 2020Co-Authors: Marzieh Reisi, Abbas Rajabifard, Soheil Sabri, Muyiwa Elijah Agunbiade, Yiqun Chen, Mohsen Kalantari, Azadeh KeshtiarastAbstract:Abstract This paper examines capabilities of a new Spatial Data Infrastructure called Urban Analytics Data Infrastructure (UADI 1 ), through deriving and evaluating transport sustainability indicators. The UADI was developed in Australia to support multi-disciplinary and cross-jurisdictional analytics to overcome the challenges related to model generalisation, Data accessibility, Data integration, Data heterogeneity and city performance benchmarking. In this paper, the UADI were evaluated through 5 technical lenses of: Data accessibility; integration; harmonisation; Data reliability and model reliability. The paper shows that using open geospatial standards in UADI enabled transport sustainability indicators to be derived through accessing and integrating different spatial Data layers and the process of mapping Data to ontology facilitated Data harmonisation. In addition, the input Data, tool processing, and output of ontology-based transport sustainability indicators could be traced in UADI, which addresses the challenge of model and Data reliability. The paper highlights the role of spatial Data Infrastructures in decision support systems for uncertainty analysis and promoting smart cities and resilient environment.
Abbas Rajabifard - One of the best experts on this subject based on the ideXlab platform.
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Spatial Data Infrastructure
TORUS 2 – Toward an Open Resource Using Services, 2020Co-Authors: Abbas RajabifardAbstract:© 2012 The International Federation of Surveyors (FIG) and the Global Spatial Data Infrastructure Association (GSDI)
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Transport sustainability indicators for an enhanced urban analytics Data Infrastructure
Sustainable Cities and Society, 2020Co-Authors: Marzieh Reisi, Abbas Rajabifard, Soheil Sabri, Muyiwa Elijah Agunbiade, Yiqun Chen, Mohsen Kalantari, Azadeh KeshtiarastAbstract:Abstract This paper examines capabilities of a new Spatial Data Infrastructure called Urban Analytics Data Infrastructure (UADI 1 ), through deriving and evaluating transport sustainability indicators. The UADI was developed in Australia to support multi-disciplinary and cross-jurisdictional analytics to overcome the challenges related to model generalisation, Data accessibility, Data integration, Data heterogeneity and city performance benchmarking. In this paper, the UADI were evaluated through 5 technical lenses of: Data accessibility; integration; harmonisation; Data reliability and model reliability. The paper shows that using open geospatial standards in UADI enabled transport sustainability indicators to be derived through accessing and integrating different spatial Data layers and the process of mapping Data to ontology facilitated Data harmonisation. In addition, the input Data, tool processing, and output of ontology-based transport sustainability indicators could be traced in UADI, which addresses the challenge of model and Data reliability. The paper highlights the role of spatial Data Infrastructures in decision support systems for uncertainty analysis and promoting smart cities and resilient environment.
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expanding the sdi environment comparing current spatial Data Infrastructure with emerging indoor location based services
International Journal of Digital Earth, 2016Co-Authors: David J. Coleman, Abbas Rajabifard, Kris W KolodziejAbstract:ABSTRACTThe authors compare key elements of the emerging field of Indoor Location-Based Services (Indoor LBS) to those currently found in spatial Data Infrastructure (SDI) programs. After a brief review of SDIs and Location-Based Services, the corresponding drivers, characteristics and emerging issues within the field of Indoor LBS are introduced and discussed. A comparative framework relates the two in terms of the criteria ‘People’, ‘Data', ‘Technologies', ‘Standards' and ‘Policies/Institutional Arrangements'. After highlighting key similarities and differences, the authors suggested three areas – definition of common framework Datasets in Indoor LBS, more effective use of volunteered geographic information by SDI programs and development of appropriate privacy policies by both communities – that may benefit from sharing ‘lessons learned'.
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spatial Data Infrastructure to facilitate coastal zone management
Coastal Zone Asia Pacific Conference, 2004Co-Authors: Ian Williamson, Abbas Rajabifard, Lisa StrainAbstract:The coastal zone is a complex area, consisting of both the marine and terrestrial environments. It is also home for an increasing number of activities, rights and interests, and according to the UN Atlas of the Ocean 44% of the worlds population. Worldwide countries are realising the need to balance development and exploitation of resources in the coastal zone with environmental and social needs.. It has been established that access to spatial Data aids in decision making for management and administration. Tools and systems such as the cadastre and spatial Data Infrastructure (SDI) have been developed that allow access and sharing of spatial Data. Many countries are implementing these tools at national, state and local levels, however most of these initiatives stop at the high water mark. The need for access to spatial Data for improved decision-making and management does not stop at the high water mark. This paper examines the concept and nature of SDI as a framework to facilitate marine management. It discusses the processes that link people to Data in the terrestrial environment and how these can be applied to marine spatial Data, with the view of including a marine or coastal dimension at the national level of an SDI model. Underpinning the need for better and more integrated management of the coastal zone, is the need for access to and interoperability of spatial Data that relates to the land and marine environments. The development of an SDI that contains spatial Data from land, coastal and marine environments will satisfy this need.
Erwan Bocher - One of the best experts on this subject based on the ideXlab platform.
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OnoM@p : a Spatial Data Infrastructure dedicated to noise monitoring based on volunteers measurements
2016Co-Authors: Erwan Bocher, Gwendall Petit, Nicolas Fortin, Judicaël Picaut, Gwenael Guillaume, Sylvain PalominosAbstract:This talk presents an ideal Spatial Data Infrastructure (SDI) dedicated to noise monitoring based on volunteers measurements. Called OnoM@P, it takes advantage of the geospatial standards and open source tools to build an integrated platform to manage the whole knowledge about a territory and to observe its dynamics. It intends also to diffuse good practices to organize, collect, represent and process geospatial Data in field of acoustic researches. OnoM@p falls within the framework of the Environmental Noise Directive (END) 2002/49/CE. The system relies on the NoiseCapture Android application developed for allowing each citizen to estimate its own noise exposure with its smartphone.
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OnoM@p : a Spatial Data Infrastructure dedicated to noise monitoring based on volunteers measurements
2016Co-Authors: Erwan Bocher, Gwendall Petit, Nicolas Fortin, Judicaël Picaut, Gwenael Guillaume, Sylvain PalominosAbstract:The present paper proposes an ideal Spatial Data Infrastructure (SDI) dedicated to noise monitoring based on volunteers measurements. Called OnoM@P, it takes advantage of the geospatial standards and open source tools to build an integrated platform to manage the whole knowledge about a territory and to observe its dynamics. It intends also to diffuse good practices to organize, collect, represent and process geospatial Data in field of acoustic researches. OnoM@p falls within the framework of the Environmental Noise Directive (END) 2002/49/CE. The system relies on the NoiseCapture Android application developed for allowing each citizen to estimate its own noise exposure with its smartphone and to contribute to the production of community noisemaps.
Dev Raj Paudyal - One of the best experts on this subject based on the ideXlab platform.
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Spatial Data Infrastructure for Pro-poor Land Management
2010Co-Authors: Dev Raj Paudyal, Kevin McdougallAbstract:SUMMARY Various organisations are working to improve the living conditions of informal settlement and move them into the formal system. UN-HABITAT is one of the organisations working for the Habitat Agenda and has launched a pro-poor land management concept to improve the lives of slum dwellers through a flexible approach. City authorities generally consider slum or informal settlement as illegal. There is a general lack of reliable information necessary for planning and policy formulation required for upgrading and regularisation of these areas. Spatial Data Infrastructure (SDI) is critical to planning and decision making for pro-poor land management. However, the conventional spatial Data Infrastructure (SDI) concept is inadequate for informal settlement upgrading and regularisation. Therefore it is important to explore an appropriate SDI to accommodate new forms of legal evidence, utilisation of new technologies and open spatial information services. The aim of this paper is to explore a SDI model for pro-poor land management in developing countries. In this context, a case study methodology has been adopted. Two cities Kathmandu Valley, Nepal and Allahabad, India are selected for the study. In both of the cities, the informal settlers live without tenure rights, in very poor conditions, and mostly occupy public land. A model of spatial Data Infrastructure for pro-poor land management has been suggested and its characteristics are described.
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Facilitating sustainable catchment management through spatial Data Infrastructure design and development
2009Co-Authors: Dev Raj PaudyalAbstract:This research paper discusses the importance of spatial Data and Spatial Data Infrastructure (SDI) for catchment management. It reviews four SDI theories including hierarchical spatial theory, diffusion theory, evolution theory and principal-agent (P-A) theory and discusses their characteristics and potential utilisation for catchment management. As catchment management issues are characterised by multi-level stakeholder participation in SDI implementation, the theory of hierarchy and the P-A theory may assist in exploring in greater depth the context of building SDI at the catchment level. Based upon existing SDI theory, it explores a conceptual framework and its implications for more effective development of catchment-based SDI. The framework which is based upon hierarchical theory, investigates the communitygovernment interaction between various catchment and administrative/political levels for developing SDI. Such a framework is complex and potentially has many levels. Additionally, the cross-jurisdictional linkages required to implement this framework within the existing administrative/political SDI framework also need to be carefully examined. The framework is explored through a case study of the Murray-Darling Basin in Australia, one of the world’s largest catchments. The challenges for developing an SDI which effectively supports the decision making within and across this catchment will be discussed and the potential strengths and weakness of the proposed framework identified in the context of this case study.
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Building spatial Data Infrastructure to support sustainable catchment management
2008Co-Authors: Dev Raj Paudyal, Kevin McdougallAbstract:Catchment management is characterised by multiple stakeholders and multiple goals which cut across traditional as well as administrative boundaries. It requires an integrated management approach as different institutions and individuals work together towards sustainable catchment outcomes. Spatial Data plays an important role in formulating many catchment decisions. An increasingly problematic issue for catchment decisions is the availability and access of spatial Data. Although the spatial Data may be available, they may not be useful due to different standards, content or scale. The importance of spatial Data to solving multiple issues concerning catchment management creates a growing need to organise Data across disciplines and organisations through the development of Spatial Data Infrastructures (SDI). Due to the increasing development of land and natural resources, the management of rights, restrictions and responsibilities between people and land is becoming an important issue under the catchment management domain. This paper discusses SDI and its importance to catchment management. The role of catchment management authorities is explored and where these groups fit within the SDI development. A case study in Banepa Municipality, Nepal is examined to understand how spatial Data Infrastructure can assist in catchment decision making and management.
