Investigating effectiveness of spatial big data in cloud computing / Mohamed Soliman Wahba Hawash ; Supervised Osman Hegazy Othman , Eman Mohamed Elamir

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Systems

Spatial Big Data refers the huge amount of Big Data extracted from many digital resources all of them related to location which lead to new challenges for researches, innovation and business development for its five characters: Volume, Velocity, Variety, Veracity and Value. Having different kinds of spatial big data sources adds new challenges for researchers to be able to overcome its challenges and opportunities such as SBD extraction, transformation, analysis and visualization. Advanced survey tools open new approaches and opportunities for Geoscience researchers to create new Models, Systems Architecture and frameworks to support the lifecycle of spatial big data. One of SBD data sources is Mobile Mapping Systems, which uses LIDAR technology to provide efficient and accurate way to collect geographic features and its attribute from field, this help city planning departments and surveyors to design and update city GIS maps with a high accuracy. There are many challenges not only about heterogenic increase in the volume of point cloud data, but also it refers to several other characteristics such as its velocity and variety. Cloud Computing has provided a new paradigm to publish and consume new spatial models as a service plus big data utilities , services which can be utilized to overcome Point Cloud data analysis and visualization challenges. This research uses the capacities of current spatial model and enhance it with Cloud based Spatial services, big data Services, using spatial join services capabilities to relate the analysis results to its location on map, describe how Cloud Computing supports the visualizing and analyzing spatial big data and review the related scientific model{u2019}s examples

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