Francesco Pasanisi

An Ontology Framework for Flooding Forecasting

Floods can cause significant damage and disruption as they often affect highly urbanized areas. The capability of knowledge using and sharing is the main reason why the ontologies are suited for supporting the phases of forecasting in (near-) real time disastrous flooding events and managing the flooding alert and emergency. This research work develops an ontology, FloodOntology for floods forecasting based on continuous measurements of water parameters gathered in the watersheds and in the sewers and simulation models. Concepts are captured across the main involved domains i.e. hydrological/hydraulic domains and SN-based monitoring domain. Classes hierarchies, properties and semantic constraints are defined related to all involved entities, obtaining a structured and unified knowledge-base on the flooding risk forecasting, to be integrated in expert systems.

SISI Project: Developing GIS-Based Tools for Vulnerability Assessment

In the framework of a wider research project, aimed at developing an high performance computing infrastructures in Southern Italy, the SISI project aims at developing customized GIS tools for vulnerable site selection in Italian territory. Vulnerable sites will be defined based on co-presence of different dangerous/vulnerable geographic features in given areas. Morphological and topological criteria will possibly be included in territorial diagnostics.

QMorphoStream: processing tools in QGIS environment for the quantitative geomorphic analysis of watersheds and river networks

The quantitative geomorphic analysis is a powerful tool for the study of geomorphology and landforms, as it provides objective methods to describe the main properties of drainage basins by means of an appropriate set of parameters. Over the last decades, GIS techniques and processing tools have been widely applied to the geomorphic analysis, and specific applications were developed, essentially using commercial software. In the present paper, the first experimental version of QMorphoStream, an originally developed set of processing tools for quantitative geomorphic analysis in QGIS environment, is presented. Besides the obvious advantage in terms of cost reduction, the choice of an open source development environment allowed us to integrate original algorithms with both QGIS built-in functions and processing tools available in the developers’ community.

Integration of Wireless Sensor Network and Hydrologic/Hydraulic Ontologies for Flooding Forecasting

Sensors are quickly becoming ubiquitous and can be found in a vast range of environments. The increase of sensor systems is accompanied by an increasing volume of data, as well as an increasing heterogeneity of devices, data formats, and measurement procedures. Shared semantic definitions help not only with data integration from multiple sources, but can also assist in integrating data into temporal and spatial contexts. It is well recognized that ontologies have an important role to play in data integration. In this research work, an ontology by integration is developed for floods risk prevision based on continuous measurements of water parameters gathered in the watersheds and along the sewers and delivered to simulation models. The objective of this ontology is to promote the interoperability of components across hydrologic/hydraulic and wireless sensor network domains in order to forecast flooding risk scenarios.