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7 results for “geohazard”
EAST-WEST and VERTICAL deformation maps of Alto Tiberina Fault supersite: The Post-Proc service in Geohazard Exploitation Platform applied to Sentinel-1 dataset
<p>In the framework of the ESA funded project “MEMpHIS - Multi Scale and Multi Hazard Mapping Space based Solutions ”, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) together with TRE-ALTAMIRA, generated the EAST-WEST and VERTICAL deformation maps of Alto Tiberina Fault supersite. The two maps of ground velocity were derived thanks to the adoption of a specific tool named "Post-Proc", implemented in MEMPHIS and with the support of Terradue, that is able to automatically re-project on the east-west and vertical directions the ascending and descending InSAR time series. In particular, the output refers to the deformation maps calculated by processing with SqueeSAR (TM) method, a large dataset acquired by the ESA Sentinel-1 mission.</p> <p>The Post-Proc tool also calculates the mean accelerations associated to each persistent scatterer in the scenes. Some additional features are also available from this tool:</p> <p>- Change the coherence threshold for selecting a subset of persistent scatterers</p> <p>- Activate a geometrical distortion filter to take into account the layover and foreshortening effects</p> <p>- Change the reference point (position and coherence)</p> <p>- Choose between two types of accelerations: 2<sup>nd</sup> order model or velocity derivative</p> <p>- Choose among three different projection: east-west, vertical, and downslope.</p> <p>The present dataset is composed of the EAST-WEST and VERTICAL acceleration maps. The data are in shapefile format: for each record (PS) the topography, velocity, acceleration, and InSAR coherence is reported.</p>
SNAPPING PSI surface motion measurements over selected sites presented in MDPI Remote Sensing paper "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping"
<p>SNAPPING PSI surface motion measurements over selected sites as presented in the paper with the title "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping" by Michael Foumelis, Jose Manuel Delgado Blasco, Fabrice Brito, Fabrizio Pacini, Elena Papageorgiou, Panteha Pishehvar and Philippe Bally on Remote Sensing Open Access Journal.</p> <p>Whenever using this dataset, please cite its original paper (<a href="https://doi.org/10.3390/rs14236075">https://doi.org/10.3390/rs14236075</a>) and include the reference to this dataset (<a href="https://doi.org/10.5281/zenodo.7369653">https://doi.org/10.5281/zenodo.7369653</a>).</p> <p>This dataset includes average Line-of-Sight velocities for the following sites and dates:</p> <table> <tbody> <tr> <td><strong>Site name</strong></td> <td><strong>Country</strong></td> <td><strong>Period</strong></td> <td><strong>Relative orbit</strong></td> <td><strong>Orbit direction</strong></td> </tr> <tr> <td>Cap-Haïtien</td> <td>Haiti</td> <td>Jan-2017 / Dec-2019</td> <td>106</td> <td>ascending</td> </tr> <tr> <td>Gran Renaissance Ethiopian Dam</td> <td>Ethiopia</td> <td>Jan-2019 / Jun-2021</td> <td>50</td> <td>descending</td> </tr> <tr> <td>La Palma Volcano</td> <td>Spain</td> <td>Jun-2019 / Dec-2021</td> <td>169</td> <td>descending</td> </tr> <tr> <td>Santorini Volcano</td> <td>Greece</td> <td>Apr-2015 / May-2021</td> <td>29</td> <td>ascending</td> </tr> <tr> <td>San Francisco</td> <td>USA</td> <td>Jan-2016 / Dec-2020</td> <td>115</td> <td>descending</td> </tr> <tr> <td>Thessaloniki International Airport (SKG)</td> <td>Greece</td> <td>Apr-2015 / Dec-2020</td> <td>102</td> <td>ascending</td> </tr> </tbody> </table>
Data : Planktic-benthic foraminifera ratio (%P) as a tool for the reconstruction of paleobathymetry and geohazard: A case study from Taiwan
<p>Details of the core sites used in this study, gear used for recovery, sediment horizon analyzed, coordinates, water depth and foraminiferal data for the size fractions of >125 µm and >63 µm (only a subset of all the sites). Study sites are divided into East Taiwan that comprises the Southern Okinawa Trough (1), Nanao-Hoping-Hateruma Basins (2), and Taitung-Hualien (3). The area of West Taiwan is consisted of the Gaoping (4), Changchun sand Ridge (5), and Henghun Ridge (6) sectors. Gear for recovery are Box core (BC); Gravity core (GC) and Grab (G). Italic numbers in TOC column (in red) are average values, italic numbers in the Laboratory column show the laboratory where the TOC and C/N were analysed, namely Geosciences-NTU (1) , Institute of Oceanography-NTU (2) and National Sun-yat sen University (3). NaN= no available data. </p>
Automated processing of aerial imagery for geohazards monitoring: Results from Fagradalsfjall eruption, SW Iceland, August 2022
<p><strong>1-</strong> <strong>Dataset Summary</strong><br> Here we present a dataset of DEMs (Digital Elevation Models), orthomosaics, and lava area outlines for the August 2022 eruption at Fagradalsfjall, SW Iceland. The dataset consists of: (1) five aerial surveys collected over the course of the August 2022 Fagradalsfjall eruption, (2) one survey carried out on 14 August 2022 using Pléiades satellite stereo images, and (3) a larger aerial survey, covering the 2021 and 2022 eruption sites in late September 2022 after the volcanic activity concluded.</p> <p><strong>2- Background</strong></p> <p>The volcano at Fagradalsfjall, SW-Iceland, began erupting on 3 August 2022 at 13:20 following 10 months of quiescence. As part of the response plan, a series of photogrammetric surveys were conducted in rapid, operational mode throughout the duration of the eruption. Subsequent production of data products for natural hazards monitoring (lava maps, lava volumes, effusion rates) were calculated within hours and reported to the Icelandic Civil Defense, following a similar approach that described in Pedersen et al., 2022a and in Gouhier et al., 2022. At the start of the 2022 eruption, GCPs had not yet been placed around the new fissure, but reference data (orthomosaics and DEMs) which had been georeferenced using targets measured with differential GNSS existed of the eruption site from September 2021 from Pedersen et al. (2022b) were available to use as a reference in the new workflow instead of GCPs. Due to the urgent need from authorities for information about the new eruption, a processing method that avoids the time-consuming task of manual GCP selection using a reference image for georeferencing was preferable in this instance. Besides the acquisition of aerial photographs, the CIEST2 initiative was also re-activated to collect Pléiades stereo images in emergency mode (Gouhier et al., 2022).</p> <p><strong>3 – Overview of data collection</strong></p> <p>Table 1 contains the overview of the surveys collected and presented in this repository.</p> <p> Table 1. Summary of surveys included in this dataset, by survey date.</p> <table align="center"> <tbody> <tr> <td> <p><strong>Date & Time</strong><br> <strong>YYYYMMDD HH:MM</strong></p> </td> <td> <p><strong>Sensor</strong></p> </td> <td> <p><strong>Platform</strong></p> </td> <td> <p><strong>Flight alt.</strong><br> <strong>(m asl)</strong></p> </td> <td> <p><strong>Images</strong></p> </td> <td> <p><strong>Surveyed</strong><br> <strong>km<sup>2</sup></strong></p> </td> </tr> <tr> <td> <p>20220803 17:05</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-203*</p> </td> <td> <p>~ 850</p> </td> <td> <p>46</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>20220804 11:00</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-203</p> </td> <td> <p>~ 2100</p> </td> <td> <p>32</p> </td> <td> <p>35</p> </td> </tr> <tr> <td> <p>20220813 09:00</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-203</p> </td> <td> <p>~ 750</p> </td> <td> <p>123</p> </td> <td> <p>9</p> </td> </tr> <tr> <td> <p>20220814 13:00</p> </td> <td> <p>Pléiades</p> </td> <td> <p>PHR1B</p> </td> <td> <p>n/a</p> </td> <td> <p>2</p> </td> <td> <p>14</p> </td> </tr> <tr> <td> <p>20220815 08:15</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-203</p> </td> <td> <p>2100</p> </td> <td> <p>20</p> </td> <td> <p>23</p> </td> </tr> <tr> <td> <p>20220816 10:06</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-203</p> </td> <td> <p>2100</p> </td> <td> <p>19</p> </td> <td> <p>26</p> </td> </tr> <tr> <td> <p>20220926 12:00</p> </td> <td> <p>A6D</p> </td> <td> <p>TF-BMW**</p> </td> <td> <p>2100</p> </td> <td> <p>~20</p> </td> <td> <p>18</p> </td> </tr> </tbody> </table> <p>* TF-203: Savannah S aircraft</p> <p>** TF-BMW: Vulcanair P68 Observer 2 aircraft, operated by Garðaflug ehf.</p> <p><strong>4- Methods</strong></p> <p><strong>4.1 Processing of the aerial photographs from 3-16 Aug 2022</strong><br> Throughout the eruption, aerial surveys were conducted using a Hasselblad A6D 100 MP camera with 35 mm focal lens, from a height of 750 – 2,100 m above ground over the active lava field from an ultralight aircraft with a window in the bottom to allow for vertical photos to be taken (see supplement of Pedersen et al., 2022a for details and images of the setup). The camera was manually triggered to give ~70% overlap, and approximate flight lines were prepared beforehand for use with a handheld GPS during the flight to give ~30 % side overlap.<br> <br> An automated processing pipeline was created in python, which leverages tools from the Ames Stereo Pipeline (ASP, Shean et al., 2016) and Agisoft Metashape stand-alone Python API (v. 1.8.4). The processing and georeferencing of the aerial data were done in three steps, with all steps being automated except for the digitization of lava outlines. First, using a very high-resolution reference orthomosaic and DEM created in September 2021 and georeferenced with ground control points (Pedersen et al., 2022b), interest points (IPs) in each image were matched with the reference dataset, using the ASP routine <em>ipfind. </em>This created GCPs for each image over stable terrain. Second, hillshades were created from both the reference DEM and the source dataset DEM and matches in IPs were found in both, creating a second round of ground control points to refine the georeferencing of the entire block. Finally, the alignment of the source DEM was refined using the <em>dem_align</em> (demcoreg) protocol from Shean et al. (2016) by applying a bulk linear shift in X, Y and Z which minimizes the vertical difference in stable terrain between the source and reference DEM.</p> <p><strong>4.2 Processing of the Pléiades stereo images</strong><br> The Pléiades stereo images were processed using the Ames Stereo Pipeline, using the general workflow of <em>mapproject </em>and <em>parallel_stereo </em>(e.g., Deschamps-Berger et al., 2020). The <em>parallel_stereo </em>routine used default arguments, plus the following arguments:</p> <p><em>--stereo-algorithm asp_mgm -t rpcmaprpc --corr-seed-mode 3 --corr-max-levels 2 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</em></p> <p>We used the DEM from 4 Aug 2022 as the reference for <em>mapproject </em>and for the final DEM co-registration applied to the produced Pléiades DEM.</p> <p><strong>4.3 Processing of the 26 September 2022 dataset</strong><br> The survey from 26 September 2022 was collected and processed using direct georeferencing from an on-board GPS antenna. The final alignment of the block was refined using the dem_align (demcoreg) protocol from Shean et al. (2016) by applying a bulk linear shift in X, Y and Z which minimizes the vertical difference in stable terrain between the source and reference DEM. Because this survey covered a much larger area, the reference DEM for the final coregistration was the <a href="https://atlas.lmi.is/mapview/?application=DEM">ÍslandsDEM </a>v.1.0 (Landmælingar Íslands, 2022).</p> <p><strong>4.4. Maps of the lava outlines, lava thickness, lava volume, Time Average Effusion Rate (TADR)</strong><br> For each survey, a differential DEM (dDEM) showing elevation changes since the 2021 eruption was created by subtracting the reference DEM (ÍslandsDEM v.1.0, which includes the post-eruption DEM from Pedersen et al., 2022a) from the source DEM. Lava outlines, lava thickness lava volume, TADR and uncertainties were calculated using the methods described in Pedersen et al., 2022a. Table 2 summarizes calculations from this dataset.</p> <p> </p> <p>Table 2. Summary of survey results calculated from August 2022 Fagradalsfjall eruption DEMs and orthomosaics.</p> <table align="center"> <thead> <tr> <th> <p><strong> Date Start</strong></p> </th> <th> <p><strong>Date End</strong></p> </th> <th> <p><strong>Time </strong></p> <p><strong>Difference</strong></p> </th> <th> <p><strong>Lava </strong></p> <p><strong>Area<sup>*</sup> End </strong></p> <p><strong>(km<sup>2</sup>)</strong></p> </th> <th> <p><strong>dh<sup>**</sup> </strong></p> <p><strong>(m)</strong></p> </th> <th> <p><strong>Volume<sup>+</sup></strong></p> <p><strong>End<br> (1e+6 m<sup>3</sup>)</strong></p> </th> <th> <p><strong>TADR<sup>++</sup><br> (m<sup>3</sup>/s)</strong></p> </th> </tr> </thead> <tbody> <tr> <td> <p>20220803<br> 13:20</p> </td> <td> <p>20220803<br> 17:05</p> </td> <td> <p>0d 03h 45m</p> </td> <td> <p>0.07</p> </td> <td> <p>5.88</p> </td> <td> <p>0.43</p> <p>± 0.03</p> </td> <td> <p>32.1</p> <p>± 1.5</p> </td> </tr> <tr> <td> <p>20220803<br> 17:05</p> </td> <td> <p>20220804<br> 11:00</p> </td> <td> <p>0d 21h 40m</p> </td> <td> <p>0.14</p> </td> <td> <p>11.13 </p> </td> <td> <p>1.57</p> <p>± 0.05</p> </td> <td> <p>17.7</p> <p>± 0.8</p> </td> </tr> <tr> <td> <p>20220804<br> 11:00</p> </td> <td> <p>20220813<br> 09:00</p> </td> <td> <p>8d 22h 00m</p> </td> <td> <p>1.27<sup>#</sup></p> </td> <td> <p>6.90</p> </td> <td> <p>10.33</p> <p>± 0.6</p> </td> <td> <p>11.4</p> <p>± 0.7</p> </td> </tr> <tr> <td> <p>20220813<br> 13:08</p> </td> <td> <p>20220814<br> 13:00</p> </td> <td> <p>0d 23h 52m</p> </td> <td> <p>1.24</p> </td> <td> <p>7.28</p> </td> <td> <p>10.62</p> <p>± 0.70</p> </td> <td> <p>2.8</p> <p>± 0.8</p> </td> </tr> <tr> <td> <p>20220814<br> 13:00</p> </td> <td> <p>20220815<br> 08:15</p> </td> <td> <p>0d 19h 15m</p> </td> <td> <p>1.26</p> </td> <td> <p>7.46</p> </td> <td> <p>10.99</p> <p>± 0.55</p> </td> <td> <p>4.1</p> <p>± 0.8</p> </td> </tr> <tr> <td> <p>20220815<br> 08:15</p> </td> <td> <p>20220816<br> 10:16</p> </td> <td> <p>1d 2h 01m</p> </td> <td> <p>1.28</p> </td> <td> <p>7.49</p> </td> <td> <p>11.13</p> <p>± 0.53</p> </td> <td> <p>2.0</p> <p>± 0.7</p> </td> </tr> <tr> <td> <p>20220816<br> 10:16</p> </td> <td> <p>20220821<br> 06:00<sup>##</sup></p> </td> <td> <p>4d 19h 44m</p> </td> <td> <p>1.28</p> </td> <td> <p>7.69</p> </td> <td> <p>11.39</p> <p>± 0.44</p> </td> <td> <p>0.653</p> <p>± 0.10</p> </td> </tr> </tbody> </table> <p><sup>*</sup>Total area of the lava field since 2022-08-03 before activity started.</p> <p><sup>**</sup>dh end is the mean thickness of the lava flow-field in the end of the given period.</p> <p><sup>+</sup>Volume erupted since 2022-08-03 before activity started.</p> <p><sup>++</sup>Time-averaged discharge rate for the given period</p> <p><sup>#</sup>Extrapolated value. Survey does not cover entire active lava area.</p> <p><sup>##</sup>End Time: 21 August 2022, 6:00. This time deduced from field observations from members of the Institute of Earth Sciences, University of Iceland. Values calculated from 26 September 2022 dataset.</p> <p>Figures and visual summaries of the processing method, resulting lava volumes, and uncertainties can be found in this poster: <a href="https://ftp.lmi.is/stm/Sydney/Fagradalsfjall_Aug2022/poster_faf_automated_proc2_srg_2022.pdf">Fagradalsfjall August 2022</a>.<br> <br> Orthomosaics from this dataset are viewable online at: <a href="https://atlas.lmi.is/mapview/?application=umbrotasja">https://atlas.lmi.is/mapview/?application=umbrotasja</a></p> <p><strong>Data naming conventions:</strong></p> <ul> <li>Data type: DEM, ortho, outline, diffDEM, lavafree, lava</li> <li>Acquisition date: YYYYMMDD_HHMM</li> <li>Platform/Sensor for data collection: Pléiades (PLE), Hasselblad A6D from aircraft (A6D)</li> <li>Resolution: 2x2 m (DEMs) and 30x30 cm (Orthomosaics)</li> <li>Folders (by survey): YYYYMMDD_HHMM_platform (during eruption) or 'posteruption'_platform (sensors/platform: A6D or PLE)</li> </ul> <p><strong>Data Specifications:</strong></p> <ul> <li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https:/epsg.io/3057">https://epsg.io/3057</a>)</li> <li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li> <li>Raster data format: GeoTIFF</li> <li>Raster compression system: ZSTD (<a href="http://facebook.github.io/zstd/">http://facebook.github.io/zstd/</a>)</li> <li>Vector data format: GeoPackage (<a href="https://www.geopackage.org/">https://www.geopackage.org/</a>)</li> <li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li> </ul>
Data from: Role of backbone fault system on earthquake spawning and geohazards in the Seoul metropolitan area
<p class="MsoNormal"><span>Major earthquakes in continental regions may cause significant damages. Preexisting fault system across megacity receives high attention for possible seismic damages. Earthquake occurrence mechanism is important to assess the geohazard potentials. Continental-scale Quaternary fault system is developed across the Seoul metropolitan area where the population is the largest in the Korean Peninsula. Historical seismic-damage records suggest potential seismic hazards in the Seoul metropolitan area. We investigate the fault motions and spatial distribution of earthquakes in the Seoul metropolitan area using a matched-filter technique that is based on stacked waveform crosscorrelation functions among densely-deployed seismic stations. The analysis detects 1,103 earthquakes that include 360 events with magnitudes (M<sub>L</sub>) of -0.6 to 2.0 around the Chugaryeong fault and 34 events with magnitudes of -0.5 to 2.7 around Wangsukcheon, Pocheon, and Yeseonggang faults. The seismicity suggests a set of near-vertical subparallel (or orthogonal) faults that develop from the major faults. The Major fault system behaves as a backbone structure that makes branch faults develop, producing seismicity including major earthquakes. The backbone structure may control the fault development that conforms to the ambient stress field. The backbone faults may play a role in increasing geohazard potentials.</span></p>
gmastrantoni/MultiHazard: Multi-Risk Ranking for Ground Instabilities through Geohazards and InSAR Ground Motion Data Fusion to Enhance Urban Resilience
<p>This release is a direct link with a Zenodo repository containing the input data.</p>
Data from: Role of backbone fault system on earthquake spawning and geohazards in the Seoul metropolitan area
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