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 Science

Volumn 9, Issue 2, 2009, Pages 303-314

  Martinis, S ^a   Twele, A ^a   Voigt, S ^a  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; DIGITAL ELEVATION MODEL; DISASTER MANAGEMENT; FLOOD DAMAGE; FLOOD FORECASTING; HISTOGRAM; IMAGE CLASSIFICATION; IMAGE RESOLUTION; REAL TIME; SATELLITE DATA; SATELLITE IMAGERY; SYNTHETIC APERTURE RADAR;

ENGLAND; UNITED KINGDOM;

EID: 76249130100     PISSN: 15618633     EISSN: 16849981     Source Type: Journal    
DOI: 10.5194/nhess-9-303-2009     Document Type: Article

References (23)

1. Baatz, M. and Schäpe, A.: Object-oriented and multi-scale image analysis in semantic networks, in: Proceedings of the 2nd International Symposium on Operationalization of Remote Sensing, Enschede, Netherlands, 16-20 August 1999.
2. Bazi, Y., Bruzzone, L., and Melgani, F.: An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images, IEEE T. Geosci. Remote, 43, 874-887, 2005.
3. Bazi, Y., Bruzzone, L., and Melgani, F.: Image thresholding based on the EM alg-orithm and the generalized Gaussian distribution, Pattern Recogn., 40, 619-634, 2007.
4. Bovolo, F. and Bruzzone, L.: A split-based approach to unsupervised change detection in large-size multitemporal images: Application to tsunami-damage assessment, IEEE T. Geosci. Remote, 45, 1658-1669, 2007.
5. Brivio, P. A., Colombo, R., Maggi, M., and Tomasoni, R.: Integration of remote sensing data and GIS for accurate mapping of flooded areas, Int. J. Remote Sens., 23, 429-441, 2002.
6. Chen, P., Liew, S. C., and Lim, H.: Flood detection using multitemporal Radarsat and ERS SAR data, in: Proceedings of the 20th Asian Conference of Remote Sensing, Hong Kong, China, 1185-1189, 22-25 November 1999.
7. Definiens AG: Defniens Developer 7 User Guide, Document Version 7.0.5.968, Munich, Germany, 2008.
8. Henry, J. B., Chastanet, P., Fellah, K., and Desnos, Y. L.: ENVISAT multi-polarised ASAR data for flood mapping, Int. J. Remote Sens., 27, 1921-1929, 2006.
9. Kittler, J. and Illingworth, J.: Minimum error thresholding, Pattern Recogn., 19, 41-47, 1986.
10. Lee, J. S.: Speckle suppression and analysis for SAR images, Opt. Eng., 25, 636-643, 1986.
11. Lopes, A., Nezry, E., Touzi, R., and Laur, H.: Maximum A Posteriori speckle filtering and first order texture models in SAR images, International Geoscience and Remote Sensing Symposium (IGARSS), Maryland, USA, 2409-2412, 24-28 May 1990.
12. Mason, M. S., Horritt, J. T., Dall'Amico, Scott, T. R., and Bates, P. D.: Improving river flood extent delineation from synthetic aperture radar using airborne laser altimetry, IEEE T. Geosci. Remote, 45, 3932-3943, 2007.
13. Mason, M. S., Speck, R., Schumann, G., Neal, J., and Bates, P. D.: Using TerraSAR-X data for improved urban flood model validation, in: Proceedings of the 3rd TerraSAR-X ScienceTeam Meeting, DLR Oberpfaffenhofen, Germany, 25-26 November 2008.
14. Matgen, P., Schumann, G., Henry, J. B., Hoffmann, L., and Pfister, L.: Integration of SAR derived river inundation areas, highprecision topographic data and a river flow model toward near real-time flood management, Int. J. Appl. Earth Obs., 9(3), 247-263, 2007.
15. Meinel, G. and Neubert, M.: A comparison of segmentation programs for high resolution remote sensing data, in: Proceedings of the ISRPS Annual Conference, Istanbul, Turkey, 19-23 July 2004.
16. Miasnikov, A. D., Rome, V., and Haralick, R. M.: A hierarchical projection pursuit clustering algorithm, in: Proceedings of the 17th International Conference on Pattern Recognition, Cambridge, England, 268-271, 23-26 August 2004.
17. Melgani, F., Moser, G., and Serpico, S. B.: Unsupervised changedetection methods for remote-sensing images, Opt. Eng., 41, 3288-3297, 2002.
18. Moser, G. and Serpico, S. B.: Generalized minimum-error thresholding for unsupervised change detection from SAR amplitude imagery, IEEE T. Geosci. Remote, 44, 2972-2982, 2006.
19. Nico, G., Pappalepore, M., Pasquariello, G., Refice, S., and Samarelli, S.: Comparison of SAR amplitude vs. coherence flood detection methods - a GIS application, Int. J. Remote Sens., 21, 1619-1631, 2000.
20. Pal, N. R. and Pal, S. K.: A review on image segmentation techniques, Pattern Recogn., 26, 1277-1294, 1993.
21. Sahoo, P. K., Soltani, S., Wong, A. K. C., and Chen, Y. C.: A survey of thresholding techniques, Comput. Vision Graph., 41, 233-260, 1988.
22. Townsend, P. A.: Estimating forest structure in wetlands using multitemporal SAR, Remote Sens. Environ., 79, 288-304, 2002.
23. Wang, Y., Colby, J. D., and Mulcahy, K. A.: An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data, Int. J. Remote Sens., 23, 3681-3696, 2002.