Classification of Landslide Activity on a Regional Scale Using Persistent Scatterer Interferometry at the Moselle Valley (Germany)

Kalia, Andre Cahyadi

doi:10.3390/rs10121880

Cited by 35 publications

(21 citation statements)

References 35 publications

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“…As areas where landslides occur are displayed as clusters in SAR amplitude images, spatial autocorrelation is a feasible approach to extract location of landslides [23]. Additionally, [66] applied Moran's I to identify clustered permanent scattering (PS) points and then distinguish various landslide activities. Accordingly, in this study, spatial autocorrelation was applied on the LR index images to extract spatial clusters of intensity change, where were the candidates of landslides.…”

Section: Object-based Feature Extractionmentioning

confidence: 99%

Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis

Lin

Lin²,

Gasselt

2021

Remote Sensing

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We present an object-based image analysis (OBIA) approach to identify temporal changes in radar-intensity images and to locate land-cover changes caused by mass-wasting processes at small to large scales, such as landslides. Our approach is based upon change detection in SAR intensity images that remain in their original imaging coordinate system rather than being georeferenced and map-projected, in order to reduce accumulation of filtering artifacts and other unwanted effects that would deteriorate the detection efficiency. Intensity images in their native slant-range coordinate frame allow for a consistent level of detection of land-cover changes. By analyzing intensity images, a much faster response can be achieved and images can be processed as soon as they are made publicly available. In this study, OBIA was introduced to systematically and semiautomatically detect landslides in image pairs with an overall accuracy of at least 60% when compared to in-situ landslide inventory data. In this process, the OBIA feature extraction component was supported by derived data from a polarimetric decomposition as well as by texture indices derived from the original image data. The results shown here indicate that most of the landslide events could be detected when compared to a closer visual inspection and to established inventories, and that the method could therefore be considered as a robust detection tool. Significant deviations are caused by the limited geometric resolution when compared to field data and by an additional detection of stream-related sediment redeposition in our approach. This overdetection, however, turns out to be potentially beneficial for assessing the risk situation after landslide events.

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Section: Object-based Feature Extractionmentioning

confidence: 99%

Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis

Lin

Lin²,

Gasselt

2021

Remote Sensing

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“…Approaches for the automatic detection of such irregular patterns in space and time have been developed already (Zhu et al, 2018), few also considering the interaction between geology and observed subsidence (Pratesi et el., 2016;North et al, 2017). While some approaches rely principally on the velocity estimates for clustering (Kalia, 2018;Aslan, 2020), other approaches consider the time series of the displacements for identifying different deformation regimes (Zhu et al, 2018). This information is particularly important for infrastructure analysis, as many factors may impact the deformation (e.g.…”

Section: State-of-the-artmentioning

confidence: 99%

Investigation of the Ground Motion Near the Leaning Tower of Bad Frankenhausen Using Sentinel-1 Persistent Scatterer Interferometry

Jänichen

Dubois

Wolsza

et al. 2020

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

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Abstract. Persistent Scatterer Interferometry (PSI) is a well-established technique for monitoring millimetre deformation of the Earth’s surface. The availability of free and open SAR data with a repeat cycle of 6–12 days from the Copernicus mission Sentinel-1, allows PSI to be used complementary to traditional surveying techniques. Whilst the data resolution may not allow a precise determination of the geolocation of the occurring deformation, observed deformation patterns can be analysed with auxiliary data and often show correlation with the location of geophysical processes or human activities. In this paper, we investigate the particular case of the church tower of Bad-Frankenhausen in the north of the Free State Thuringia, Germany, with PSI processing of Sentinel-1 data. Both pass directions (descending and ascending) are considered, and different motion models are tested in order to retrieve the most accurate displacement pattern around the church location. Deformation up to −6 mm/yr are observed near the church location for the period 2016–2019 in ascending direction.

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“…The first articles of using Sentinel-l SAR data for landslide monitoring have been presented by Monserrat et al (2016) and Barra et al (2016). Recently, Kalia (2018) applied 66 Sentinel acquisitions in a descending orbit mode for classification of landslide activity on a regional scale using PSI at the Moselle Valley in Germany.…”

Section: Introductionmentioning

confidence: 99%

Multi-temporal landslide activity investigation by spaceborne SAR interferometry: Polish Carpathians case study

Pawłuszek-Filipiak

Motagh

Borkowski

2020

Preprint

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Abstract. The main goal of this research is the activity state verification of existing landslide inventory maps using Persistent Scatterer Interferometry (PSI). The study was conducted in Małopolskie municipality, a rural setting with a sparse urbanization in Polish Flysch Carpathians. PSI have been applied using Synthetic Aperture Radar (SAR) data from ALOS PALSAR, and Sentinel 1A/B from different acquisition geometry (ascending and descending orbit) to increase PS coverage and overcome geometric effects due to layover and shadowing. The Line-Of-Sight PSI measurements were projected to the steepest slope, which allows to homogenize the results from diverse acquisition modes and to compare displacement velocities with different slope orientations. Additionally, landslide intensity (motion rate) and expected damages maps were generated and verified during filed investigations. High correlation between PSI results and in-situ damage observations has been confirmed. Activity state and landslide-related expected damage map have been confirmed for 43 out of a total of 50 landslides investigated in the field. The short temporal baseline provided by Sentinel satellite 1A/B data allows increasing of the PS density significantly. The study substantiates usefulness of SAR based landslide activity monitoring for land use and land development, even in rural areas.

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Classification of Landslide Activity on a Regional Scale Using Persistent Scatterer Interferometry at the Moselle Valley (Germany)

Cited by 35 publications

References 35 publications

Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis

Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis

Investigation of the Ground Motion Near the Leaning Tower of Bad Frankenhausen Using Sentinel-1 Persistent Scatterer Interferometry

Multi-temporal landslide activity investigation by spaceborne SAR interferometry: Polish Carpathians case study

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