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Full-Text Articles in Databases and Information Systems
Big Data Applications And Challenges In Giscience (Case Studies: Natural Disaster And Public Health Crisis Management), Amir Masoud Forati
Big Data Applications And Challenges In Giscience (Case Studies: Natural Disaster And Public Health Crisis Management), Amir Masoud Forati
Theses and Dissertations
This dissertation examines the application and significance of user-generated big data in Geographic Information Science (GIScience), with a focus on managing natural disasters and public health crises. It explores the role of social media data in understanding human-environment interactions and in informing disaster management and public health strategies. A scalable computational framework will be developed to model extensive unstructured geotagged data from social media, facilitating systematic spatiotemporal data analysis.The research investigates how individuals and communities respond to high-impact events like natural disasters and public health emergencies, employing both qualitative and quantitative methods. In particular, it assesses the impact of socio-economic-demographic …
Mapping And Describing Geospatial Data To Generalize Complex Models: The Case Of Littosim-Gen, Ahmed Laatabi, Nicolas Becu, Nicolas Marilleau, Cécilia Pignon-Mussaud, Marion Amalric, Xavier Bertin, Brice Anselme, Elise Beck
Mapping And Describing Geospatial Data To Generalize Complex Models: The Case Of Littosim-Gen, Ahmed Laatabi, Nicolas Becu, Nicolas Marilleau, Cécilia Pignon-Mussaud, Marion Amalric, Xavier Bertin, Brice Anselme, Elise Beck
International Journal of Geospatial and Environmental Research
For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding …