OBIA Flood Delimitation Assisted by Threshold Determination with Principal Component Analysis

Roque, Dora; Afonso, Nuno; Fonseca, Ana Maria; Heleno, Sandra

doi:10.14358/pers.80.6.551-557

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…These simple robust methods have limited applicability in difficult case studies, such as with complex topography or abundant vegetation, and therefore were modified or adapted in more complex methods [4], [5]. Recent examples of complex flood mapping methods used ancillary data and region growing [6], local correction algorithms of radar layover, and emergent vegetation [7], elevation-based filtering and processing in local tiles [8], or classification, including multistep classification, often followed by data transformation [9]- [12]. The disadvantages of complex methods are limited repeatability due to a lack of ready-to-use software and the need to provide parameter values (for some of the methods).…”

Section: Introductionmentioning

confidence: 99%

“…Long-term SAR sensor missions, such as PALSAR, Radarsat, and Sentinel 1, provide an opportunity to produce flooding map time series, which have been utilized in studies focusing on flood monitoring and ecology [13]- [18]. The time series has also been very useful for hydrodynamic model calibration and validation [9], [19], [20]. A deeper analysis of the time-series approach revealed that high spatial resolution of SAR data is more important than its temporal resolution in model calibration [21].…”

Section: Introductionmentioning

confidence: 99%

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Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations

Berezowski

Bieliński

Osowicki

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The flooding extent area in a river valley is related to river gauge observations such as discharge and water elevations. The higher the water elevations, or discharge, the larger the flooding area. Flooding extent maps are often derived from synthetic aperture radar (SAR) images using thresholding methods. The thresholding methods vary in complexity and number of required parameters. We proposed a simple thresholding method that takes advantage of the correlation between the river gauge and the flooding area. To show the applicability of the method, we used a 2014-2018 time series of 161 Sentinel 1 SAR images acquired over a wetland floodplain located in Northeast Poland. We validated the method by extracting local water line elevations from a high-resolution digital elevation model for three river gauges, which resulted in a root-mean-square error of 0.16 m, a bias of 0.07 m, and a correlation of 0.86 for the best scenario. The scenario analysis showed that the most important factor affecting the method's accuracy was a proper delineation of the zone in which the flooding extent area was calculated. This was because other water sources, uncorrelated with river flow, were present in the floodplain as open water. Additionally, higher accuracy was obtained for the VV than VH polarization. The discharge can be used instead of water elevations as a river gauge variable, but this results in more bias in the water extent estimates.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations

Berezowski

Bieliński

Osowicki

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Besides on-site images used for the water-level image analysis, image-based flooding information includes large-scale aerial and remote images from satellites [ 12 , 31 , 32 ] and synthetic aperture radars (SARs) [ 33 – 36 ], which are normally used for a large-scale geographic analysis on the flood overflow area. However, due to the complex obtaining process, the time delay caused by the large amount of post-processing work, satellite or aerial images are usually used in non-instant applications, such as meteorology, hydrology, and disaster management.…”

Section: Introductionmentioning

confidence: 99%

Cyber Surveillance for Flood Disasters

Lin

et al. 2015

Sensors

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Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective.

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Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods

Berezowski

Gierszewska

Bieliński

2021

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS

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OBIA Flood Delimitation Assisted by Threshold Determination with Principal Component Analysis

Cited by 3 publications

References 13 publications

Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations

Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations

Cyber Surveillance for Flood Disasters

Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods

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