Recent availability of multisource high-resolution remote sensing data and of flood detection algorithms (D’Addabbo A. et al. 2016; Rajapaksha, J., & Dampegama 2016; Mason, D. et al. 2012; Martinis, S. Et al. 2006; Nico, G. et al. 2000), poses the problem of how to integrate them into ready to use emergency flood maps. We present a flood map of the event occurred on December 2013 in Basilicata (southern Italy) that documents both the ground effects (Figure 1) and the spatial evolution of the inundated areas through time (Figure 2). The multilayer map, consisting of four 1:25.000 scale different layers, was prepared using image processing, visual image interpretation and field survey controls. We used two COSMO-SkyMed synthetic aperture radar (SAR), stripmap (3 m resolution) images, acquired during the event, and a Plèiades-1B High Resolution (2 m) satellite optical image, acquired at the end of the event. We also included data on vulnerability obtained through out the OpenStreetMap (OSM) database update, and then integrating it within the flood map. Our map shows how recent advances in flood detection algorithms, and the availability of high resolution Optical and SAR data can be integrated to have a flood event synoptic representation, but also a ready-to-use map in a relatively short time, to be used immediately after the event for hazard, vulnerability and damage assessment. Figure 1 (A) Optical satellite detail image acquired on 5 December 2013, showing different ground effect traces; (B) derived inundation map, showing different ground effects observed by visual image interpretation. Figure 2 Inundation map details which show water evidences decrease from the image acquired during flood event peak (1-2 Dec. 2013) until the last image acquired far from the event; (A & B) show water evidence observed in RGB SAR composition, obtained from 2 December and 3 December SAR image elaboration; (C) water evidences observed from Plèiades optical satellite image acquired on 5 December 2013. References D'Addabbo, A., Refice, A., Pasquariello, G., Lovergine, F. P., Capolongo, D., & Manfreda, S. (2016). A bayesian network for flood detection combining SAR imagery and ancillary data. IEEE Transactions on Geoscience and Remote Sensing, 54(6), 3612-3625. Martinis, S., Twele, A., & Voigt, S. (2009). Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data. Natural Hazards and Earth System Sciences, 9(2), 303-314. Mason, D. C., Davenport, I. J., Neal, J. C., Schumann, G. J. P., & Bates, P. D. (2012). Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images. IEEE transactions on Geoscience and Remote Sensing, 50(8), 3041-3052. Nico, G., Pappalepore, M., Pasquariello, G., Refice, A., & Samarelli, S. (2000). Comparison of SAR amplitude vs. coherence flood detection methods-a GIS application. International Journal of Remote Sensing, 21(8), 1619-1631. Rajapaksha, J., & Dampegama, L. S. S. Emergency flood mapping from synthetic aperture radar; a simple fuzzy logic approach. Conference Paper October 2016; Conference: Asian Conference on Remote Sensing, At Colombo, Volume: 37.
REMOTELY SENSED FLOOD MAPS IN THE METAPONTO PLAIN (BASILICATA)
Nicoletta Maria de Musso;Domenico Capolongo;Luigi Pennetta
2017-01-01
Abstract
Recent availability of multisource high-resolution remote sensing data and of flood detection algorithms (D’Addabbo A. et al. 2016; Rajapaksha, J., & Dampegama 2016; Mason, D. et al. 2012; Martinis, S. Et al. 2006; Nico, G. et al. 2000), poses the problem of how to integrate them into ready to use emergency flood maps. We present a flood map of the event occurred on December 2013 in Basilicata (southern Italy) that documents both the ground effects (Figure 1) and the spatial evolution of the inundated areas through time (Figure 2). The multilayer map, consisting of four 1:25.000 scale different layers, was prepared using image processing, visual image interpretation and field survey controls. We used two COSMO-SkyMed synthetic aperture radar (SAR), stripmap (3 m resolution) images, acquired during the event, and a Plèiades-1B High Resolution (2 m) satellite optical image, acquired at the end of the event. We also included data on vulnerability obtained through out the OpenStreetMap (OSM) database update, and then integrating it within the flood map. Our map shows how recent advances in flood detection algorithms, and the availability of high resolution Optical and SAR data can be integrated to have a flood event synoptic representation, but also a ready-to-use map in a relatively short time, to be used immediately after the event for hazard, vulnerability and damage assessment. Figure 1 (A) Optical satellite detail image acquired on 5 December 2013, showing different ground effect traces; (B) derived inundation map, showing different ground effects observed by visual image interpretation. Figure 2 Inundation map details which show water evidences decrease from the image acquired during flood event peak (1-2 Dec. 2013) until the last image acquired far from the event; (A & B) show water evidence observed in RGB SAR composition, obtained from 2 December and 3 December SAR image elaboration; (C) water evidences observed from Plèiades optical satellite image acquired on 5 December 2013. References D'Addabbo, A., Refice, A., Pasquariello, G., Lovergine, F. P., Capolongo, D., & Manfreda, S. (2016). A bayesian network for flood detection combining SAR imagery and ancillary data. IEEE Transactions on Geoscience and Remote Sensing, 54(6), 3612-3625. Martinis, S., Twele, A., & Voigt, S. (2009). Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data. Natural Hazards and Earth System Sciences, 9(2), 303-314. Mason, D. C., Davenport, I. J., Neal, J. C., Schumann, G. J. P., & Bates, P. D. (2012). Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images. IEEE transactions on Geoscience and Remote Sensing, 50(8), 3041-3052. Nico, G., Pappalepore, M., Pasquariello, G., Refice, A., & Samarelli, S. (2000). Comparison of SAR amplitude vs. coherence flood detection methods-a GIS application. International Journal of Remote Sensing, 21(8), 1619-1631. Rajapaksha, J., & Dampegama, L. S. S. Emergency flood mapping from synthetic aperture radar; a simple fuzzy logic approach. Conference Paper October 2016; Conference: Asian Conference on Remote Sensing, At Colombo, Volume: 37.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.