Name
Title | ||
|---|---|---|
Small-Catchment Flood Forecasting And Drainage Network Extraction Using Computational Intelligence |
Abstract | ||
|---|---|---|
Forecast, detection and warning of severe weather and related hydro-geological risks is becoming one of the major issues for civil protection. The use of computational intelligence techniques such as artificial neural network and cellular automata algorithm can be suitable for such problems especially for real time forecasting system.Nowcasting (short-term forecasting) of extreme rainfall events is an example that invites to exploit remote sensing systems from satellites, such geostationary and low-orbit radiometers. A rainfall estimation algorithm based on artificial neural network has been developed for this purpose. Satellite data sources can be globally provided but at a quite coarse spatial resolution, therefore, the coupling of rain remote sensing data with regional raingauge networks is also essential for ensuring a calibration of remotely sensed rainfall fields in terms of ground effects. An overwhelming issue is the spatial integration of these rainfall data sources having different space-time resolution and variable accuracies. In this work a cellular automata based algorithm has been used to integrate these heterogeneous data.A flood forecast chain, developed at the Centre of Excellence for Remote Sensing and Hydro-Meteorology Modelling and based on coupled mesoscale atmospheric model and distributed hydrological model with in-situ and remote sensing data integration is presented, with the emphasis on the integration of numerical models and retrieval algorithms using integrated tools based on computational intelligence techniques. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IJCNN.2006.246773 | 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 |
Keywords | Field | DocType |
flood forecasting,real time,artificial neural network,spatial resolution,space time,weather forecasting,neural nets,atmospheric modeling,remote sensing,computational intelligence,cellular automata | Data integration,Data mining,Computational intelligence,Computer science,Flood forecasting,Atmospheric model,Artificial intelligence,Artificial neural network,Weather forecasting,Machine learning,Nowcasting,Geostationary orbit | Conference |
ISSN | Citations | PageRank |
2161-4393 | 1 | 0.43 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erika Coppola | 1 | 1 | 0.43 |
| Barbara Tomassetti | 2 | 1 | 0.43 |
| Marco Verdecchia | 3 | 1 | 0.43 |
| Frank S. Marzano | 4 | 41 | 15.92 |
| G. Visconti | 5 | 2 | 1.14 |