Advances in environmental monitoring systems from remote sensing to pervasive real and virtual sensor networks are enlarging the amount and types of data available at local and global scale at increasingly higher temporal and spatial resolution. However, accessing and integrating these data for modeling and operational purposes can be challenging and highly time consuming, particularly in complex physical and institutional contexts, where data are from different sources. This research focuses on the design of a web geo- service architecture, based on Free and Open Source Software (FOSS), to enable collection and sharing of data coming from complex water resources domains and managed by multiple institutions. The heterogeneous nature of these data requires the combination of different geospatial data servers (Catalog Service for the Web, Web Map Service, Web Feature service, Web Coverage Service, Sensor Observations Service,) and interface technologies that enable interoperability of all complex resources data types. This is a key feature of web geo- service tools in multidata and multiowners environment. Besides the storage of the available hydrological data according to the Open Geospatial Consortium standards, the architecture provides a platform for comparatively analyzing alternative water supply and demand management strategies. The architecture is developed for the Lake Como system (Italy), a regulated lake serving multiple and often competing water uses (irrigation, hydropower, flood control) in northern Italy. . This research gives important insights on currently operating GEOSS (Global Earth Observation System of Systems) architectures, demonstrating that Spatial Data Infrastructures using FOSS are a feasible and effective alternative to data and metadata collection, storage, sharing and visualization in complex water resources management contexts, using open international standards.
Brovelli, Maria Antonia; Arias, Carolina; Giuliani, Matteo; and Castelletti, Andrea, "A FOSS Based Web Geo- Service Architecture For Data Management In Complex Water Resources Contexts" (2014). CUNY Academic Works.