Flooding extent cartography with Landsat TM imagery and regularized kernel Fisher's discriminant analysis

Aizerman, M.A., Braverman, E.A., Rozonoer, L., 1964. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Remote Control 821–837. Bachmann, 2005, Exploiting manifold geometry in hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, 43, 441, 10.1109/TGRS.2004.842292 Bandos, 2009, Classification of hyperspectral images with regularized linear discriminant analysis, IEEE Transactions on Geoscience and Remote Sensing, 47, 862, 10.1109/TGRS.2008.2005729 Bruzzone, 2000, Automatic analysis of the difference image for unsupervised change detection, IEEE Transactions on Geoscience and Remote Sensing, 38, 1171, 10.1109/36.843009 2009 Chormanski, J., Okruszko, T., Ignar, S., Batelaan, O., Rebel, K.T., J., W.M., 2011. Flood mapping with remote sensing and hydrochemistry: a new method to distinguish the origin of flood water during floods. Ecological Engineering 37, 1334–1349. Currey, 1977, Identifying flood water movement, Remote Sensing of Environment, 6, 51, 10.1016/0034-4257(77)90019-0 Dey, C., Jia, X., Fraser, D., Wang, L., 2009. Mixed pixels analysis for flood mapping using extended support vector machines. In: DICTA, Melbourne (AUS), pp. 291–295. Fisher, 1936, The use of multiple measurements in taxonomic problems, Annals of Eugenics, 7, 179, 10.1111/j.1469-1809.1936.tb02137.x Foody, 2004, Thematic map comparison, Photogrammetric Engineering & Remote Sensing, 70, 627, 10.14358/PERS.70.5.627 Foody, 2004, Toward intelligent training of supervised image classifications, Remote Sensing of Environment, 93, 107, 10.1016/j.rse.2004.06.017 Friedman, 1989, Regularized discriminant analysis, Journal of the American Statistical Association, 84, 165, 10.1080/01621459.1989.10478752 Frohn, 2011, Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ imagery, International Journal of Remote Sensing, 32, 1471, 10.1080/01431160903559762 Gianinetto, 2007, Rapid response flood assessment using minimum noise fraction and composed spline interpolation, IEEE Transactions on Geoscience and Remote Sensing, 45, 3204, 10.1109/TGRS.2007.895414 Gianinetto, 2006, Postflood damage evaluation using Landsat TM and ETM+ and data integrated with DEM, IEEE Transactions on Geoscience and Remote Sensing, 44, 236, 10.1109/TGRS.2005.859952 Hess, 1995, Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar, IEEE Transactions on Geoscience and Remote Sensing, 33, 894, 10.1109/36.406675 Huang, S.Y., Hwang, C.R., 2006. Kernel fisher discriminant analysis in Gaussian reproducing kernel Hilbert spaces—theory. Technical Report. Institute of Statistical Sciences, Academia sinica, Taipei, China. Hudson, 2003, Flood delineation in a large and complex alluvial valley, lower Pánuco basin, Mexico, Journal of Hydrology, 280, 229, 10.1016/S0022-1694(03)00227-0 Hughes, 1968, On the mean accuracy of statistical pattern recognizers, IEEE Transactions on Information Theory, 14, 55, 10.1109/TIT.1968.1054102 Ip, 2006, Flood detection and monitoring with the autonomous sciencecraft experiment onboard EO-1, Remote Sensing of Environment, 101, 463, 10.1016/j.rse.2005.12.018 Kanevski, 2009 Khan, 2011, Satellite remote sensing and hydrologic modeling for flood inundation mapping in lake victoria basin, IEEE Transactions on Geoscience and Remote Sensing, 49, 85, 10.1109/TGRS.2010.2057513 Longbotham, 2012, Multi-modal change detection, application to the detection of flooded areas, IEEE Journal of Selected Topics in Applied Earth Observations, 5, 1 Martinis, 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, 303, 10.5194/nhess-9-303-2009 Mika, S., Rätsch, G., Müller, K.R., 2000. A mathematical programming approach to the kernel fisher algorithm. In: NIPS, Denver (USA), pp. 591–597. Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Müller, K.R., 1999. Fisher discriminant analysis with kernels. In: Proceedings of the IEEE Neural Networks Signal, Madison (USA), pp. 41–48. de Morsier, F., Borgeaud, M., Küchler, C., Gass, V., Thiran, J.P., 2012. Semi-supervised and unsupervised novelty detection using nested support vector machine. In: IEEE IGARSS, Munich (D), pp. 7337–7340. O'Grady, 2011, Use of ENVISAT ASAR global monitoring mode to complement optical data in the mapping of rapid broad-scale flooding in Pakistan, Hydrology and Earth System Sciences, 15, 3475, 10.5194/hess-15-3475-2011 Petropoulos, 2011, Burnt area delineation from a uni-temporal perspective based on Landsat TM imagery classification using support vector machines, International Journal of Applied Earth Observation, 13, 70, 10.1016/j.jag.2010.06.008 Petropoulos, 2012, Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery, Geocarto International, 1 Pulvirenti, 2011, Flood monitoring using multi-temporal COSMO-SkyMed data, Remote Sensing of Environment, 115, 990, 10.1016/j.rse.2010.12.002 Pulvirenti, 2011, An algorithm for operational flood mapping from synthetic aperture radar (SAR) data using fuzzy logic, Natural Hazards and Earth System Sciences, 11, 529, 10.5194/nhess-11-529-2011 Radke, 2005, Image change detection algorithms, IEEE Transactions on Image Processing, 14, 294, 10.1109/TIP.2004.838698 Sanders, 2005, National flood modelling for insurance purposes, Hydrology and Earth System Sciences, 9, 449, 10.5194/hess-9-449-2005 Schölkopf, 2002 Shawe-Taylor, 2004 Singh, 1989, Digital change detection techniques using remotely sensed data, International Journal of Remote Sensing, 10, 989, 10.1080/01431168908903939 Sugiyama, 2007, Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis, Journal of Machine Learning Research, 8, 1027 Taubenböck, 2011, Flood risks in urbanized areas—multi-sensoral approaches using remotely sensed data for risk assessment, Natural Hazards and Earth System Sciences, 11, 431, 10.5194/nhess-11-431-2011 Tuia, 2011, A survey of active learning algorithms for supervised remote sensing image classification, IEEE Journal of Selected Topics in Signal Processing, 5, 606, 10.1109/JSTSP.2011.2139193 Volpi, 2012, Unsupervised change detection with kernels, IEEE Transactions on Geoscience and Remote Sensing Letters, 9, 1026, 10.1109/LGRS.2012.2189092 Volpi, 2012, Memory-based cluster sampling for remote sensing image classification, IEEE Transactions on Geoscience and Remote Sensing, 50, 3016, 10.1109/TGRS.2011.2179661 Volpi, 2013, Supervised change detection in VHR images using contextual information and support vector machines, International Journal of Applied Earth Observation, 20, 77, 10.1016/j.jag.2011.10.013 Yamagata, 1988, Flood damage analysis using multitemporal Landsat Thematic Mapper data, International Journal of Remote Sensing, 9, 503, 10.1080/01431168808954871 Zwenzner, 2009, Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data, Hydrology and Earth System Sciences, 13, 567, 10.5194/hess-13-567-2009