Title | ||
---|---|---|
Development and validation of multitemporal image analysis methodologies for multirisk monitoring of critical structures and infrastructures |
Abstract | ||
---|---|---|
In the framework of the monitoring of structures and infrastructures from environmental disasters, the COSMO-SkyMed constellation has a huge potential, thanks to up to metric spatial resolution, short revisit time, and the day/night all-weather acquisition capability ensured by SAR. This paper focuses on the scientific results of the project “Development and validation of multitemporal image analysis methodologies for multirisk monitoring of critical structures and infrastructures,” funded by the Italian Space Agency. Several change-detection, data-fusion, and feature-extraction techniques, which were developed and experimentally validated in the project for COSMO-SkyMed imagery and for their integration with other data sources (including very high resolution optical data), are described and examples of processing results are discussed. |
Year | DOI | Venue |
---|---|---|
2012 | 10.1109/IGARSS.2012.6352359 | Geoscience and Remote Sensing Symposium |
Keywords | Field | DocType |
critical infrastructures,data acquisition,disasters,feature extraction,geophysical image processing,image fusion,radar imaging,remote sensing by radar,risk management,synthetic aperture radar,terrain mapping,COSMO-SkyMed constellation,COSMO-SkyMed imagery,Italian Space Agency,SAR,all-weather acquisition capability,change detection,critical infrastructure,critical structure,data fusion,data sources,environmental disaster,feature extraction technique,infrastructure monitoring,multirisk monitoring,multitemporal image analysis method,revisit time,spatial resolution,very high resolution optical data,Multirisk monitoring,change detection,data fusion,feature extraction,infrastructures,urban areas | Computer vision,Change detection,Image fusion,Synthetic aperture radar,Computer science,Data acquisition,Remote sensing,Sensor fusion,Feature extraction,Risk management,Constellation,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4673-1158-8 | 978-1-4673-1158-8 | 0 |
PageRank | References | Authors |
0.34 | 8 | 20 |
Name | Order | Citations | PageRank |
---|---|---|---|
Sebastiano B. Serpico | 1 | 749 | 64.86 |
Lorenzo Bruzzone | 2 | 4952 | 387.72 |
Giovanni Corsini | 3 | 299 | 40.26 |
William J. Emery | 4 | 248 | 31.44 |
Paolo Gamba | 5 | 682 | 92.97 |
Andrea Garzelli | 6 | 574 | 41.36 |
Grégoire Mercier | 7 | 605 | 52.49 |
Josiane Zerubia | 8 | 2032 | 232.91 |
Nicola Acito | 9 | 191 | 22.58 |
Bruno Aiazzi | 10 | 275 | 27.84 |
Francesca Bovolo | 11 | 739 | 70.89 |
Fabio Dell'Acqua | 12 | 478 | 57.84 |
Michaela De Martino | 13 | 14 | 4.28 |
Marco Diani | 14 | 261 | 30.99 |
Vladimir A. Krylov | 15 | 133 | 14.81 |
Gianni Lisini | 16 | 207 | 21.99 |
Carlo Marin | 17 | 33 | 6.95 |
Gabriele Moser | 18 | 919 | 76.92 |
Aurelie Voisin | 19 | 55 | 3.91 |
Claudia Zoppetti | 20 | 0 | 2.37 |