An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Pulvirenti, Luca; Pierdicca, Nazzareno; Chini, Marco; Guerriero, L.

doi:10.5194/nhess-11-529-2011

Cited by 234 publications

(153 citation statements)

References 33 publications

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“…In this method all pixels with a backscatter coefficient lower than a specified threshold in an intensity image are mapped as water [70,71]. This technique is useful for producing results quickly and inexpensively [72], but is only suitable for calm open water with a specular backscatter response [73]. A user-selected threshold was chosen to map surface water in the case study we present because it offered a flexible, efficient, and user controlled, scene specific approach.…”

Section: Surface Watermentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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Abstract:Wetlands are an important natural resource that requires monitoring. A key step in environmental monitoring is to map the locations and characteristics of the resource to better enable assessment of change over time. Synthetic Aperture Radar (SAR) systems are helpful in this way for wetland resources because their data can be used to map and monitor changes in surface water extent, saturated soils, flooded vegetation, and changes in wetland vegetation cover. We review a few techniques to demonstrate SAR capabilities for wetland monitoring, including the commonly used method of grey-level thresholding for mapping surface water and highlighting changes in extent, and approaches for polarimetric decompositions to map flooded vegetation and changes from one class of land cover to another. We use the Curvelet-based change detection and the Wishart-Chernoff Distance approaches to show how they substantially improve mapping of flooded vegetation and flagging areas of change, respectively. We recommend that the increasing availability SAR data and the proven ability of these data to map various components of wetlands mean SAR should be considered as a critical component of a wetland monitoring system.

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Section: Surface Watermentioning

confidence: 99%

A Collection of SAR Methodologies for Monitoring Wetlands

et al. 2015

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“…Usually the choice of the threshold values of a fuzzy set (x 1 and x 2 ) based on SAR data for flooded vegetation is a critical aspect, because these thresholds depend on system parameters (frequency band, polarization and observation angle), as well as on environmental parameters of the study area (season/vitality of vegetation and topography) (Pulvirenti et al 2011). To find suitable threshold values, the first attempt was performed by using a single image, which only considers the absolute backscatter values.…”

Section: The Backscatter Values Based Fuzzy Setsmentioning

confidence: 99%

“…To deal with this ambiguity of the radars signature for flooded areas beneath vegetation a semiautomatic approach using a fuzzy logic classification algorithm is developed. Fuzzy logic is already successfully used in other studies focusing on the detection of inundation based on SAR data (Pierdicca et al 2008;Pulvirenti et al 2011;Martinis 2015 Twele et al (accepted)). The application of a fuzzy logic-based approach allows the combination of SAR backscatter information with ancillary information, such as land cover, topographic considerations and contextual information.…”

Section: Introductionmentioning

confidence: 99%

“…Most of this methods aim to detect flooded vegetation based on thresholds empirically derived and applied to SAR data. However, to reduce the subjectiveness in this kind of process an automatic determination of a suitable threshold value was attempted (Martinis & Twele 2010;Pulvirenti et al 2011;Schlaffer et al 2015). It is common to use only single temporal images to derive the threshold between flooded and non-flooded vegetation.…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy Logic-Based Approach for the Detection of Flooded Vegetation by Means of Synthetic Aperture Radar Data

Tsyganskaya¹,

Martinis²,

Twele³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper an algorithm designed to map flooded vegetation from synthetic aperture radar (SAR) imagery is introduced. The approach is based on fuzzy logic which enables to deal with the ambiguity of SAR data and to integrate multiple ancillary data containing topographical information, simple hydraulic considerations and land cover information. This allows the exclusion of image elements with a backscatter value similar to flooded vegetation, to significantly reduce misclassification errors. The flooded vegetation mapping procedure is tested on a flood event that occurred in Germany over parts of the Saale catchment on January 2011 using a time series of high resolution TerraSAR-X data covering the time interval from 2009 to 2015. The results show that the analysis of multi-temporal X-band data combined with ancillary data using a fuzzy logic-based approach permits the detection of flooded vegetation areas.

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“…The large swath width of the MODIS sensor allows for a short revisit period (1-2 days), and can be ideal for large continental scale flood assessments, but data are relatively coarse with a 250 m resolution. While [5] developed an algorithm for the almost automatic fuzzy classification of flooding from SAR (synthetic aperture radar) collected from the COSMO-SkyMed platform.…”

Section: Introductionmentioning

confidence: 99%

Real Time Estimation of the Calgary Floods Using Limited Remote Sensing Data

Schnebele

Cervone

Kumar

et al. 2014

Water

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Every year, flood disasters are responsible for widespread destruction and loss of human life. Remote sensing data are capable of providing valuable, synoptic coverage of flood events but are not always available because of satellite revisit limitations, obstructions from cloud cover or vegetation canopy, or expense. In addition, knowledge of road accessibility is imperative during all phases of a flood event. In June 2013, the City of Calgary experienced sudden and extensive flooding but lacked comprehensive remote sensing coverage. Using this event as a case study, this work illustrates how data from non-authoritative sources are used to augment traditional data and methods to estimate flood extent and identify affected roads during a flood disaster. The application of these data, which may have varying resolutions and uncertainities, provide an estimation of flood extent when traditional data and methods are lacking or incomplete. When flooding occurs over multiple days, it is possible to construct an estimate of the advancement and recession of the flood event. Non-authoritative sources also provide flood information at the micro-level, which can be difficult to capture from remote sensing data; however, the distibution and quantity of data collected from these sources will affect the quality of the flood estimations.

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An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Cited by 234 publications

References 33 publications

A Collection of SAR Methodologies for Monitoring Wetlands

A Collection of SAR Methodologies for Monitoring Wetlands

A Fuzzy Logic-Based Approach for the Detection of Flooded Vegetation by Means of Synthetic Aperture Radar Data

Real Time Estimation of the Calgary Floods Using Limited Remote Sensing Data

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