scholarly journals Assessment of Landslide-Induced Geomorphological Changes in Hítardalur Valley, Iceland, Using Sentinel-1 and Sentinel-2 Data

2020 ◽  
Vol 10 (17) ◽  
pp. 5848
Author(s):  
Zahra Dabiri ◽  
Daniel Hölbling ◽  
Lorena Abad ◽  
Jón Kristinn Helgason ◽  
Þorsteinn Sæmundsson ◽  
...  
Keyword(s):  
Significant Risk ◽  
Radar Data ◽  
Volume Estimation ◽  
Lake Area ◽  
Synthetic Aperture Radar Data ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Hazard And Risk ◽  
Geomorphological Changes ◽  
Sentinel 2

Landslide mapping and analysis are essential aspects of hazard and risk analysis. Landslides can block rivers and create landslide-dammed lakes, which pose a significant risk for downstream areas. In this research, we used an object-based image analysis approach to map geomorphological features and related changes and assess the applicability of Sentinel-1 data for the fast creation of post-event digital elevation models (DEMs) for landslide volume estimation. We investigated the Hítardalur landslide, which occurred on the 7 July 2018 in western Iceland, along with the geomorphological changes induced by this landslide, using optical and synthetic aperture radar data from Sentinel-2 and Sentinel-1. The results show that there were no considerable changes in the landslide area between 2018 and 2019. However, the landslide-dammed lake area shrunk between 2018 and 2019. Moreover, the Hítará river diverted its course as a result of the landslide. The DEMs, generated by ascending and descending flight directions and three orbits, and the subsequent volume estimation revealed that—without further post-processing—the results need to be interpreted with care since several factors influence the DEM generation from Sentinel-1 imagery.

scholarly journals Beyond 2D inventories : synoptic 3D landslide volume calculation from repeat LiDAR data

2020 ◽  
Author(s):  
Thomas G. Bernard ◽  
Dimitri Lague ◽  
Philippe Steer
Keyword(s):  
Point Cloud ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Aerial Images ◽  
3D Point Cloud ◽  
Volume Calculation ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Areal Mapping

Abstract. Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made during the last decades to develop landslide areal mapping methods, based on 2D satellite or aerial images, and to constrain empirical volume-area (V-A) allowing in turn to offer indirect estimates of landslide volume. Despite these efforts, some major issues remain including the uncertainty of the V-A scaling, landslide amalgamation and the under-detection of reactivated landslides. To address these issues, we propose a new semi-automatic 3D point cloud differencing method to detect geomorphic changes, obtain robust landslide inventories and directly measure the volume and geometric properties of landslides. This method is based on the M3C2 algorithm and was applied to a multi-temporal airborne LiDAR dataset of the Kaikoura region, New Zealand, following the Mw 7.8 earthquake of 14 November 2016. We demonstrate that 3D point cloud differencing offers a greater sensitivity to detect small changes than a classical difference of DEMs (digital elevation models). In a small 5 km2 area, prone to landslide reactivation and amalgamation, where a previous study identified 27 landslides, our method is able to detect 1431 landslide sources and 853 deposits with a total volume of 908,055 ± 215,640 m3 and 1,008,626 ± 172,745 m3, respectively. This high number of landslides is set by the ability of our method to detect subtle changes and therefore small landslides with a carefully constrained lower limit of 20 m2 (90 % with A 

Late Pleistocene–Holocene stress in the South American intraplate evidenced by tectonic instability in central Amazonia

2021 ◽  
pp. 1-17
Author(s):  
Dilce F. Rossetti ◽  
Francisco H. R. Bezerra ◽  
Márcio M. Valeriano ◽  
Eder Cassola Molina
Keyword(s):  
Late Pleistocene ◽  
Drainage Basin ◽  
Radar Data ◽  
Shuttle Radar Topography Mission ◽  
Plate Motion ◽  
Large Area ◽  
Synthetic Aperture Radar Data ◽  
Negro River ◽  
Digital Elevation ◽  
Central Amazonia

Abstract Documenting neotectonic instabilities and determining the style and time of deformation in the vast and difficult to access central Amazonia region is challenging. We focus on these issues by investigating a large area of the Negro River drainage basin, applying morphostructural analysis based on synthetic aperture radar data. The digital elevation models of the C-band Shuttle Radar Topography Mission and the L-band Protection System of Amazonia were used as the database. We also used subsurface magnetic information from the Earth Magnetic Anomaly Grid global model to validate the morphostructures. The results revealed NW-oriented morphostructural lineaments bounding multiple depositional valley fills. These were extensively fragmented to form regularly distributed en échelon rectangular blocks commonly offset horizontally by several kilometers. Strike-slip faults and oblique, either normal or reverse, faults are present. These structures were reactivated along the main NE- and SW-oriented regional structural trends due to N-S-oriented horizontal compression and E-W-oriented horizontal extension in the late Pleistocene and Holocene. The extensive neotectonic faulting results from the interplay of plate motion and Andean uplifting since the late Pleistocene, combined with local stresses.

scholarly journals GIS-BASED LANDSLIDE VOLUME ESTIMATION USING DIGITAL TERRAIN MODELS DERIVED FROM LIDAR AND RADAR SYSTEMS: CASE OF PIDIGAN, ABRA

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 109-115
Author(s):  
A. C. Dalagan ◽  
J. A. Principe
Keyword(s):  
Stability Analysis ◽  
Mass Transport ◽  
Digital Terrain Model ◽  
Large Mass ◽  
Southwest Monsoon ◽  
Volume Estimation ◽  
Synthetic Aperture Radar Data ◽  
Digital Terrain ◽  
Landslide Volume ◽  
Landslide Event

Abstract. Southwest Monsoon (Habagat) and Typhoon Luis caused a deep-seated landslide that struck Sitio Kayang, Brgy. Immuli, Pidigan, Abra on August 15, 2018. Rainfall-induced deep-seated landslides displace partially at a time which necessitates the determination of remaining landslide volume along the slope. In this study, the potential landslide volume and mass transport were estimated using several remote sensing products, including SAR (Synthetic Aperture Radar) data and LiDAR-DTM (Light Detection and Ranging-Digital Terrain Model). The post-landslide DTM was generated using Sentinel-1 SAR data. The potential landslide volume and landslide failure surfaces were ascertained through the stability analysis using Scoops3D, while the mass transport volume was obtained from the pre- and post-landslide DTM. Results showed that the estimated total volume in all the landslide areas was 135,962 m3. Meanwhile, the remaining landslide volume (i.e., difference between potential volume from pre-landslide event and volume of transported mass) yielded illogical values due to the derived large mass transport values. This blunder may be attributed to the generalization of the transported volume (due to Sentinel-1 DTM coarse resolution), and decorrelation due to vegetation cover. Overall, the LiDAR-DTM data delivered a high-resolution estimation of the potential landslide volume and proved to be useful for landslide application studies. Future studies may incorporate field data (e.g., geotechnical parameters, groundwater, landslide actual measurements) for more accurate performance of stability analysis and may best to utilize LiDAR-DTM in post-landslide volume computation for a more reliable estimation of mass transport and potentially remaining landslide volume.

scholarly journals Topographic Evolution Involving Co-Seismic Landslide, Deformation, Long-Term Folding and Isostatic Rebound: A Case Study on the 2004 Chuetsu Earthquake

2021 ◽  
Vol 13 (6) ◽  
pp. 1073
Author(s):  
Jinghao Lei ◽  
Zhikun Ren ◽  
Takashi Oguchi ◽  
Peizhen Zhang ◽  
Shoichiro Uchiyama
Keyword(s):  
Hanging Wall ◽  
Volume Estimation ◽  
Catchment Scale ◽  
Epicentral Area ◽  
Landslide Volume ◽  
Digital Elevation ◽  
Geological Evolution ◽  
Seismically Induced Landslides ◽  
Seismic Landslide

Co-seismic landslide volume information is critical to understanding the role of strong earthquakes in topographic and geological evolution. The availability of both pre- and post-earthquake high-resolution digital elevation models (DEMs) provides us with the opportunity to develop a new approach to obtain robust landslide volume information. Here, we propose a method for landslide volume estimation and test it in the Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. First, we align the DEMs by reconstructing the horizontal difference. Then, we quantitatively obtain the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale denudation and the resulting long-term crustal rebound. Our findings reveal that the Chuetsu earthquake mainly roughens the topography in the low-elevation Chuetsu region. Our results indicate that the preserved topography not only is due to the uplift caused by fault-related folding on the hanging wall of the Muikamachi fault but also undergoes erosion caused by seismically induced landslides and crustal rebound also modifies the topography in the long term. This study confirms that the differential DEM method is a valuable approach for quantitative analysis of topographic and geological evolution.

scholarly journals Mapping of wheat lodging susceptibility with synthetic aperture radar data

2021 ◽  
Vol 259 ◽  
pp. 112427
Author(s):  
Sugandh Chauhan ◽  
Roshanak Darvishzadeh ◽  
Sander H. van Delden ◽  
Mirco Boschetti ◽  
Andrew Nelson
Keyword(s):  
Synthetic Aperture Radar ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Aperture Radar

scholarly journals Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1753
Author(s):  
Johnson Bailey ◽  
Armando Marino ◽  
Vahid Akbari
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Roc Curves ◽  
Radar Data ◽  
Open Ocean ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Synthetic Aperture Radar Data ◽  
Whitening Filter ◽  
Aperture Radar

Icebergs represent hazards to ships and maritime activities and therefore their detection is essential. Synthetic Aperture Radar (SAR) satellites are very useful for this, due to their capability to acquire data under cloud cover and during day and night passes. In this work, we compared six state-of-the-art polarimetric target detectors to test their performance and ability to detect small-sized icebergs <120 m in four locations in Greenland. We used four single-look complex (SLC) ALOS-2 quad-polarimetric images from JAXA for quad-polarimetric detection and we compared with dual-polarimetric detectors using only the channels HH and HV. We also compared these detectors with single-polarimetric intensity channels and we tested using two scenarios: open ocean and sea ice. Our results show that the multi-look polarimetric whitening filter (MPWF) and the optimal polarimetric detector (OPD) provide the most optimal performance in quad- and dual-polarimetric mode detection. The analysis shows that, overall, quad-polarimetric detectors provide the best detection performance. When the false alarm rate (PF) is fixed to 10-5, the probabilities of detection (PD) are 0.99 in open ocean and 0.90 in sea ice. Dual-polarimetric or single-polarimetric detectors show an overall reduction in performance (the ROC curves show a decrease), but this degradation is not very large (<0.1) when the value of false alarms is relatively high (i.e., we are interested in bigger icebergs with a brighter backscattering >120 m, as they are easier to detect). However, the differences between quad- and dual- or single-polarimetric detectors became much more evident when the PF value was fixed to low detection probabilities 10-6 (i.e., smaller icebergs). In the single-polarimetric mode, the HV channel showed PD values of 0.62 for open ocean and 0.26 for sea ice, compared to values of 0.81 (open ocean) and 0.77 (sea ice) obtained with quad-polarimetric detectors.

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