130 research outputs found

    Rapid Damage Mapping for the 2015 M_w 7.8 Gorkha Earthquake Using Synthetic Aperture Radar Data from COSMO–SkyMed and ALOS-2 Satellites

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    The 25 April 2015 M_w 7.8 Gorkha earthquake caused more than 8000 fatalities and widespread building damage in central Nepal. The Italian Space Agency’s COSMO–SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area four days after the earthquake and the Japan Aerospace Exploration Agency’s Advanced Land Observing Satellite-2 SAR satellite for larger area nine days after the mainshock. We used these radar observations and rapidly produced damage proxy maps (DPMs) derived from temporal changes in Interferometric SAR coherence. Our DPMs were qualitatively validated through comparison with independent damage analyses by the National Geospatial-Intelligence Agency and the United Nations Institute for Training and Research’s United Nations Operational Satellite Applications Programme, and based on our own visual inspection of DigitalGlobe’s WorldView optical pre- versus postevent imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork

    Disaster debris estimation using high-resolution polarimetric stereo-SAR

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    AbstractThis paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099m3. Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs

    SENTINEL-1 DATA TO MAP FLOODED AREAS: THE ROLE OF INSAR COHERENCE AND POLARIMETRIC INFORMATION

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    Τα SAR δεδομένα παρατήρησης της Γης μπορούν να προσφέρουν χάρτες πλημμυρικής έκτασης και πληροφοριών υψηλής ποιότητας για την καλύτερη εκτίμηση του κινδύνου πλημμύρας κατά συνέπεια το σχεδιασμό, καθώς και για την υποστήριξη των πολιτικών αρχών υπέρ της προστασίας κατά τη φάση έκτακτης ανάγκης. Το πεδίο εφαρμογής του παρόντος εγγράφου είναι να δημιουργήσει χάρτες πλημμυρικής έκτασης από μια σειρά εικόνων SAR της λεκάνης του Έβρου, που αντιπροσωπεύει μια διασυνοριακή κοίτη πλημμυρών. Η μελέτη χρησιμοποιεί χρονολογικές σειρές εικόνων SAR του Copernicus δορυφορικού συστήματος Sentinel-1 που καλύπτει την περίοδο Οκτώβριος 2014-Μάιος 2015. Η μεθοδολογία προσπαθεί να προσδιορίσει την πλημμύρα που συμβαίνει σε τρεις κύριες κατηγορίες κάλυψης γης, όπως είναι οι αστικές περιοχές, γυμνά ή κακώς βλάστηση εδάφους και περιοχές με βλάστηση, εκμεταλλευόμενοι τα εναλλασσόμενη πόλωση SAR κανάλια backscattering, και τη συνάφεια συμβολομετρίας για τον καλύτερο χαρακτηρισμό του τοπίου. Χρησιμοποιώντας εναλλασσόμενη πόλωση SAR δεδομένα παρέχει την ευκαιρία να υπάρχει μια καλύτερη κατανόηση και ερμηνεία της ανίχνευσης πλημμύρας λόγω του διαφορετικού τρόπου που αντιδρά η κάλυψη γης σε διαφορετικές 1731 πολώσεις. Έτσι, με την εφαρμογή της εκτίμησης της συμβολομετρικής συνάφειας μπορούμε να επιτύχουμε ένα καλύτερη καταγραφή και γνώση των πλημμυρισμένων περιοχών, στη πάροδο του χρόνου, στη συγκεκριμένη περιοχή.SAR earth observation data can provide high quality flood maps and information to better assess the flood risk accordingly planning as well as to support civil protection authorities during emergency phase. The scope of this paper is to create flood extent maps from a series of SAR scenes of the Evros basin which represents a transboundary floodplain. The study uses time series SAR images of Sentnel-1 ESA’s Copernicus satellite system covering the period October 2014 to May 2015. The methodology tries to identify the flood that occurs in three main land cover classes, such as urban areas, bare or poorly vegetated soil and vegetated areas, taking advantage of co- and cross-polarized SAR backscattering channels, and the InSAR coherence to better characterize the landscape. Dual-pol SAR data provides the opportunity to have a better understanding and interpretation of flood detection due to way different land cover react to different polarizations. Thus, with the implementation of InSAR coherence estimation we may achieve a better record and knowledge of the flooded areas, over time, in the specific region.

    Modeling Watershed Response in Semiarid Regions With High-Resolution Synthetic Aperture Radars

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    In this paper, we propose a methodology devoted to exploit the outstanding characteristics of COSMO-SkyMed for monitoring water bodies in semiarid countries at a scale never experienced before. The proposed approach, based on appropriate registration, calibration, and processing of synthetic aperture radar (SAR) data, allows outperforming the previously available methods for monitoring small reservoirs, mainly carried out with optical data, and severely limited by the presence of cloud coverage, which is a frequent condition in wet season. A tool has been developed for computing the water volumes retained in small reservoirs based on SAR-derived digital elevation model. These data have been used to derive a relationship between storage volumes and surface areas that can be used when bathymetric information is unavailable. Due to the lack of direct measures of river's discharge, the time evolution of water volumes retained at reservoirs has been used to validate a simple rainfall-runoff hydrological model that can provide useful recommendation for the management of small reservoirs. Operational scenarios concerning the improvement in the efficiency of reservoirs management and the estimation of their impact on downstream area point out the applicative outcomes of the proposed method

    Sentinel-1 InSAR coherence to detect floodwater in urban areas: Houston and hurricane harvey as a test case

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    This paper presents an automatic algorithm for mapping floods. Its main characteristic is that it can detect not only inundated bare soils, but also floodwater in urban areas. The synthetic aperture radar (SAR) observations of the flood that hit the city of Houston (Texas) following the landfall of Hurricane Harvey in 2017 are used to apply and validate the algorithm. The latter consists of a two-step approach that first uses the SAR data to identify buildings and then takes advantage of the Interferometric SAR coherence feature to detect the presence of floodwater in urbanized areas. The preliminary detection of buildings is a pre-requisite for focusing the analysis on the most risk-prone areas. Data provided by the Sentinel-1 mission acquired in both Strip Map and Interferometric Wide Swath modes were used, with a geometric resolution of 5 m and 20 m, respectively. Furthermore, the coherence-based algorithm takes full advantage of the Sentinel-1 mission's six-day repeat cycle, thereby providing an unprecedented possibility to develop an automatic, high-frequency algorithm for detecting floodwater in urban areas. The results for the Houston case study have been qualitatively evaluated through very-high-resolution optical images acquired almost simultaneously with SAR, crowdsourcing points derived by photointerpretation from Digital Globe and Federal Emergency Management Agency's (FEMA) inundation model over the area. For the first time the comparison with independent data shows that the proposed approach can map flooded urban areas with high accuracy using SAR data from the Sentinel-1 satellite mission

    Robust algorithm for detecting floodwater in urban areas using Synthetic Aperture Radar images

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    Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. High resolution Synthetic Aperture Radar (SAR) sensors are able to detect flood extents in urban areas during both day- and night-time. If obtained in near real-time, these flood extents can be used for emergency flood relief management or as observations for assimilation into flood forecasting models. In this paper a method for detecting flooding in urban areas using near real-time SAR data is developed and extensively tested under a variety of scenarios involving different flood events and different images. The method uses a SAR simulator in conjunction with LiDAR data of the urban area to predict areas of radar shadow and layover in the image caused by buildings and taller vegetation. Of the urban water pixels visible to the SAR, the flood detection accuracy averaged over the test examples was 83%, with a false alarm rate of 9%. The results indicate that flooding can be detected in the urban area to reasonable accuracy, but that this accuracy is limited partly by the SAR’s poor visibility of the urban ground surface due to shadow and layover

    Submarine landslide megablocks show half of Anak Krakatau island failed on December 22nd, 2018

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    As demonstrated at Anak Krakatau on December 22nd, 2018, tsunamis generated by volcanic flank collapse are incompletely understood and can be devastating. Here, we present the first high-resolution characterisation of both subaerial and submarine components of the collapse. Combined Synthetic Aperture Radar data and aerial photographs reveal an extensive subaerial failure that bounds pre-event deformation and volcanic products. To the southwest of the volcano, bathymetric and seismic reflection data reveal a blocky landslide deposit (0.214 ± 0.036 km3) emplaced over 1.5 km into the adjacent basin. Our findings are consistent with en-masse lateral collapse with a volume ≥0.175 km3, resolving several ambiguities in previous reconstructions. Post-collapse eruptions produced an additional ~0.3 km3 of tephra, burying the scar and landslide deposit. The event provides a model for lateral collapse scenarios at other arc-volcanic islands showing that rapid island growth can lead to large-scale failure and that even faster rebuilding can obscure pre-existing collapse
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