This volume collects the scientific contributions presented at the Workshop “Explo- ration of Spatio-Temporal Environmental Conditions: Harmonized Databases and Analytical Techniques (ECoST-DATA)”, held at the University of Bari on July 3-4, 2025, as Satellite event of DUST 2025. It is a key result of the ECoST- DATA Project, funded by European Union – NextGenerationEU with the Cascade Open Calls published by ALMA MATER STUDIORUM – University of Bologna, inside the Project GRINS within the PNRR – Mission 4, Component 2, Investment 1.3 “Partnership extended to Universities, Research Centers, Firms and research projects funding”, D.D. 341 of 15/03/2022, CUP: J33C22002910001. The contents are dedicated to advanced tools and techniques for analyzing and predicting environmental variables with a spatial or spatio-temporal structure. In particular, they include theoretical reviews on spatio-temporal covariance modelling as well as innovative approaches for assessing environmental quality and its effects on climate change by integrating georeferenced data from multiple sources.
Exploration of Spatio-Temporal Environmental Conditions: Harmonized Databases and Analytical Techniques
De Iaco S.;Palma M.;Posa D.
2025-01-01
Abstract
This volume collects the scientific contributions presented at the Workshop “Explo- ration of Spatio-Temporal Environmental Conditions: Harmonized Databases and Analytical Techniques (ECoST-DATA)”, held at the University of Bari on July 3-4, 2025, as Satellite event of DUST 2025. It is a key result of the ECoST- DATA Project, funded by European Union – NextGenerationEU with the Cascade Open Calls published by ALMA MATER STUDIORUM – University of Bologna, inside the Project GRINS within the PNRR – Mission 4, Component 2, Investment 1.3 “Partnership extended to Universities, Research Centers, Firms and research projects funding”, D.D. 341 of 15/03/2022, CUP: J33C22002910001. The contents are dedicated to advanced tools and techniques for analyzing and predicting environmental variables with a spatial or spatio-temporal structure. In particular, they include theoretical reviews on spatio-temporal covariance modelling as well as innovative approaches for assessing environmental quality and its effects on climate change by integrating georeferenced data from multiple sources.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
