Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space

Li, Ning; Murphy, Robert W.; Deng, Yunkai; Liu, Yabo; Li, Bochen; Wang, Chunle; Balz, Timo

doi:10.1117/1.jrs.8.083595

Cited by 11 publications

(5 citation statements)

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“…In addition, multispectral and Synthetic Aperture Radar (SAR) satellite images have been also used with great success. To recognize landslides in multispectral and very high resolution (VHR) optical images, the most commonly applied methods consist of visual interpretation (Fiorucci et al, 2011;Ma et al, 2016) or semiautomatic classification (segmentation) that exploits different radiometric signatures of stable and failed areas (Martha et al, 2011;Mondini et al, 2011;Alvioli et al, 2018). However, optical images have some disadvantages and cannot be used when the analyzed areas are covered by persistent clouds or affected by shadow effects.…”

Section: Introductionmentioning

confidence: 99%

A spaceborne SAR-based procedure to support the detection of landslides

Esposito

Marchesini

Mondini

et al. 2020

Nat. Hazards Earth Syst. Sci.

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Abstract. The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows for monitoring areas prone to geohydrological disasters, providing relevant information for risk evaluation and management. In cases of major landslide events, for example, spaceborne radar data can provide an effective solution for the detection of slope failures, even in cases with persistent cloud cover. The information about the extension and location of the landslide-affected areas may support decision-making processes during emergency responses. In this paper, we present an automatic procedure based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection of landslides over wide areas. Specifically, the procedure evaluates changes of radar backscattered signals associated with land cover modifications that may be also caused by mass movements. After a one-time calibration of some parameters, the processing chain is able to automatically execute the download and preprocessing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a georeferenced map. This map should help decision makers and emergency managers to organize field investigations. The process of automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of open-source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that was struck by a severe seismic sequence in February–March 2018. In the area, we simulated a periodic survey of about 7 months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidence of widespread land cover changes that occurred just after the most severe seismic events. Most of the detected changes can be interpreted as mass movements triggered by the seismic shaking.

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Section: Introductionmentioning

confidence: 99%

A spaceborne SAR-based procedure to support the detection of landslides

Esposito

Marchesini

Mondini

et al. 2020

Nat. Hazards Earth Syst. Sci.

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show abstract

“…When the target characteristics are determined, the scattering matrix is steady and both the incident and scattered waves are fully polarized waves, the coherent target decomposition theory can be used to process PolSAR data. Li et al [19] analyzed the scattering mechanism of landslides using the coherent target decomposition method for automatic extraction of a large-scale regional landslide. The second category is incoherent target decomposition.…”

Section: Introductionmentioning

confidence: 99%

Using InSAR and PolSAR to Assess Ground Displacement and Building Damage after a Seismic Event: Case Study of the 2021 Baicheng Earthquake

et al. 2022

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During unexpected earthquake catastrophes, timely identification of damaged areas is critical for disaster management. On the 24 March 2021, Baicheng county was afflicted by a Mw 5.3 earthquake. The disaster resulted in three deaths and many human injuries. As an active remote sensing technology independent of light and weather, the increasingly accessible Synthetic Aperture Radar (SAR) is an attractive data for assessing building damage. This paper aims to use Sentinel-1A radar images to rapidly assess seismic damage in the early phases after the disaster. A simple and robust method is used to complete the task of surface displacement analysis and building disaster monitoring. In order to obtain the coseismic deformation field, differential interferometry, filtering and phase unwrapping are performed on images before and after the earthquake. In order to detect the damage area of buildings, the Interferometric Synthetic Aperture Radar (InSAR) and Polarimetric Synthetic Aperture Radar (PolSAR) techniques are used. A simple and fast method combining coherent change detection and polarimetric decomposition is proposed, and the complete workflow is introduced in detail. In our experiment, we compare the detection results with the ground survey data using an unmanned aerial vehicle (UAV) after the earthquake to verify the performance of the proposed method. The results indicate that the experiment can accurately obtain the coseismic deformation field and identify the damaged and undamaged areas of the buildings. The correct identification accuracy of collapsed and severely damaged areas is 86%, and that of slightly damaged and undamaged areas is 84%. Therefore, the proposed method is extremely effective in monitoring seismic-affected areas and immediately assessing post-earthquake building damage. It provides a considerable prospect for the application of SAR technology.

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“…Successful applications were described by Yamaguchi (2012), Shimada et al (2014), Li et al (2014) and Plank et al (2016).…”

Section: Introductionmentioning

confidence: 99%

A semi-automatic procedure to support the detection of rapid-moving landslides using spaceborne SAR imagery

Esposito

Marchesini

Mondini

et al. 2020

Preprint

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Abstract. The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows monitoring areas prone to geo-hydrological disasters, providing relevant information for risk evaluation and management. In case of major landslide events, for example, spaceborne radar data can provide an innovative solution for the detection of slope failures, even in case of persistent cloud cover. The information about extension and location of the landslide-affected areas may support decision-making processes during the emergency responses. In this paper, we present a semi-automatic procedure, based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed to facilitate the detection of rapid-moving landslides. The procedure evaluates changes of radar backscattered signals associated to land cover modifications, that may be also caused by mass movements. The procedure requires an initial manual selection of some parameters, and is able to execute automatically the download and pre-processing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a geo-referenced map. This map should help decision-makers and emergency managers to organize field investigations. The processes automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of Open Source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that in February/March 2018 was struck by a severe seismic sequence that triggered numerous widespread landslides. In the area, we simulated a periodic survey of about seven months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidences of widespread land cover changes occurred just after the most severe seismic events. Most of them can be interpreted as mass movements triggered by the main seismic shocks.

show abstract

Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space

Cited by 11 publications

References 0 publications

A spaceborne SAR-based procedure to support the detection of landslides

A spaceborne SAR-based procedure to support the detection of landslides

Using InSAR and PolSAR to Assess Ground Displacement and Building Damage after a Seismic Event: Case Study of the 2021 Baicheng Earthquake

A semi-automatic procedure to support the detection of rapid-moving landslides using spaceborne SAR imagery

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