Deriving Spatial Data from Volunteered Geographic .. (VGI_SLAM)
Deriving Spatial Data from Volunteered Geographic Information
Date du début: 1 sept. 2013,
Date de fin: 31 août 2015
Recent years have seen the widespread engagement of large numbers of private citizens in the creation of spatial data. These contributors, commonly referred to as “citizen sensors”, often have no formal qualifications in performing a task which was traditionally reserved to official mapping agencies. This paradigm of crowd sourced spatial data is commonly referred to as Volunteered Geographic Information (VGI) (Goodchild, 2007). The greatest concern when using any form of spatial data is its quality. Therefore the data derived from VGI should be of the highest possible quality and it is necessary to be able to make statements about this quality. These tasks are complicated by the fact that VGI may be captured with inaccurate devices, lacking detail and in some cases inconsistent. Consequently there exists a degree of uncertainty associated with VGI which must be considered if one is to derive accurate spatial data.The overall objective of the proposed research project is the development of new methodologies for deriving spatial data from VGI using a probabilistic formulation. We proposed to draw heavily from methodologies developed in the domain of robotics and specifically the sub-domain of Simultaneous Localization And Mapping (SLAM).Dr. Corcoran has much previous research experience in VGI and SLAM, and therefore is a suitable candidate to carry out the project in question. Prof. Leonard of Massachusetts Institute of Technology (MIT) and Dr. Bertolotto of University College Dublin (UCD) are experts in the areas of robotics and geographical information science respectively. Their institutes therefore represent suitable hosts for Dr. Corcoran. The result of this fellowship will be a significant and long lasting transfer of knowledge and skills from MIT to UCD.
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