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15 results for “Pléiades”
Subsample of the maximum Water Area Extent of Telangana Rainwater Harvesting System from Pléiades DEM
<p>Small Reservoirs maximum water area extent polygones composing the Rainwater Harvesting System over the Telangana state, South-India. Maximum Water Area Extent are elevation isolines selected by hand from Very High Resolution Digital Elevation Model (VHR DEM at 2 meters resolution) derived from pairs of stereoscopic Pléiades images at 50cm resolution (10.5281/zenodo.10403040). The selection is made to find the area that contain both MWAE derived from Sentinel-2 (10.5281/zenodo.10402199) and Landsat archives (Global Surface Water, <span><a href="https://doi.org/10.1038/nature20584" target="_blank" rel="noopener">10.1038/nature20584</a></span>) curated from rivers and big dams (10.5281/zenodo.10402096).</p>
Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages
<p><strong>Introduction:</strong></p><p>On the 10th of July 2023, at 16:40, an eruption started in the Reykjanes Peninsula, Iceland, next to the mountain "Litla-Hrútur". As part of the response, the CIEST2 french initiative was activated (Gouhier et al., 2022). Once activated, Pléiades stereoimages were tasked and scheduled for fast delivery within the area of Interest. On the 20th of August 2023 an additional stereopair of images from Pléiades was acquired and processed after the eruption had stopped.</p><p>Once acquired and delivered, the Pléiades images were processed following the methods described in the section below. This repository contains the near-real time results of DEMs, difference maps compared to a pre-eruption DEM, and lava outlines digitized from the difference map and the orthoimage.</p><p> </p><p><strong>Methods</strong>:</p><p>The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <i>parallel_stereo </i>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <i>point2dem</i>. Besides default parameters, the <i>parallel_stereo</i> parameters used for creation of the DEMs were the standard parameters, plus the following ones: </p><p><i>--stereo-algorithm asp_mgm --corr-tile-size 300 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</i></p><p>Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean's co-registration routines (<a href="https://github.com/dshean/demcoreg">https://github.com/dshean/demcoreg</a>, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.</p><p>The pre-eruption DEM used for this study is a survey done on the 27th of September 2022, data collected Birgir Óskarsson and Robert A. Askew (Icelandic Institute of Natural History) and processed by Sydney R. Gunnarsson and Joaquín M.C. Belart (National Land Survey of Iceland). Metadata of this dataset is available here: https://gatt.lmi.is/geonetwork/srv/eng/catalog.search#/metadata/c59da6cf-18ee-44af-a085-afbad0de029a</p><p>Lava outlines were manually digitized from the co-registered Pléiades orthoimages, The lava outlines are available as GeoPackages in the "GPKG" branch of the repository.</p><p>At the moment, the results from Pléiades are used by the Institute of Earth Sciences of the Univesity of Iceland (Jarðvisindustofnun Háskoli Íslands) to estimate lava volumes and effusion rate, following the methods described in Pedersen et al. (2022). Please contact the authors if these data are intended to be used for a similar purpose, in order to avoid conflict of interests or duplicate work. We encourage collaboration and data sharing for the purpose of the monitoring of the eruption and for research applications.</p><p><strong>Data naming convention:</strong></p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align.tif: DEM obtained from the processing, co-registered to the reference pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align_diff.tif: Difference of elevation between the Pléiades DEM and the pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmm.gpkg: Polygon containing the lava outlines, extracted from the Pléiades orthoimage and the map of elevation difference.</p><p>0_faf_YYYYMMDD_hhmmss_hhmmss_*fig.png: A figure showing the latest map of elevation difference, overlaid with a hillshade of the latest Pléiades DEM and the latest lava outlines, result of the processing of the Pléiades stereoimages. The figure was created using the tool imviewer.py from the GitHub repository https://github.com/dshean/imview (Shean et al., 2016).</p><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: LZW</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><p><strong>Acknowledgements</strong>: </p><p>Pléiades images from July 2023 were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (<a href="https://en.poleterresolide.fr/">https://en.poleterresolide.fr/</a>). Pléiades images from August 2023 were provided under the CEOS Volcano Supersite (https://ceos.org/ourwork/workinggroups/disasters/gsnl/). Image Pléiades©CNES2023, distribution AIRBUS DS.</p><p><strong>Dataset Attribution</strong>:</p><p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).</p><p><strong>Citation:</strong></p><p>Please cite this repository as described below:</p><p>Joaquin M.C. Belart, Virginie Pinel, Hannah. I. Reynolds, Etienne Berthier, & Sydney R. Gunnarson. (2023). Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages (1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10133203</p>
Gummern - Digital elevation model 0.5 m, created from Pléiades Neo tri-stereo satellite imagery
<h2>Abstract</h2> <p>Digital surface model, spatial resolution 0.5 m, produced from Pleiades Neo Tri-Stereo imagery & Ground control points for Pleiades Neo tri-stereo orientation.</p> <p>This depositry contains data generated within the European S34 project.</p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>Gummern_PleiadesNeo_DSM05m & Gummern_PleiadesNeo_GCPs</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>Digital surface model, spatial resolution 0.5 m, produced from Pleiades Neo Tri-Stereo imagery & Ground control points for Pleiades Neo tri-stereo orientation</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>surface model, Pleiades Neo, tri-stereo</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Gummern</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>Gummern_PleiadesNeo_GCPs</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Elevation & GNSS</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>1.10.2023 (27.10.2023 – GNSS)</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>1.12.2023 (6.11.2023 – GNSS)</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Raster / Vector</p> </td> </tr> <tr> <td> <p>Fromat</p> </td> <td> <p>GeoTIFF / CSV</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>0.5m</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p>0.30m (0.01m – GNSS)</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p>EPSG 25833</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p>Dejan Grigillo (dejan.grigillo@fgg.uni-lj.si)</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>UL</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Dejan Grigillo (dejan.grigillo@fgg.uni-lj.si)</p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Snow depth and land surface cover in Tuolumne basin (California) from Pléiades images
<p>This dataset contains products calculated from Pléiades images.</p> <p>Details about the products are available in https://doi.org/10.5194/tc-2020-15.</p> <p>These products were used in Figure 4.</p> <p>- pleiades_elevation_difference_raw_winter_minus_summer.tif : raw difference of digital elevation models (DEMs) calculated from Pléiades stereo images.</p> <p>- pleiades_snow_depth_winter.tif : difference of DEMs on snow terrain only (where pleiades_land_surface_cover_winter.tif==1 with morphological erosion)</p> <p>- pleiades_land_surface_cover_winter.tif : land cover surface in the winter images (1= snow, 2=forest, 3= stable terrain, 4=water)</p> <p>- pleiades_land_surface_cover_summer.tif : land cover surface in the summer images (1= snow, 2=forest, 3= stable terrain, 4=water) </p> <p>- elevation_difference_style.qml : qgis style used for elevation difference and snow depth.</p> <p>- land_surface_cover_style.qml : qgis style used for land cover surface.</p> <p> </p>
Pléiades co- and post-eruption survey in Cumbre Vieja volcano, La Palma, Spain
<p><strong>Introduction</strong>: </p> <p>This repository consists of a series of topographic surfaces of the Cumbre Vieja volcano (La Palma, Spain), presented as a series of Digital Elevation Models (DEMs) obtained from multiple Pléiades stereoscopic surveys acquired from the 22<sup>nd</sup> of September 2021 until the 14<sup>th</sup> of January 2022. We also present a series of grids showing the difference of elevation between the pre-eruption surface and the co- and post-eruption surface, which reveal the lava thickness of the eruption. This was used to calculate the lava volume and effusion rate or Time Average Discharge Rate (TADR) at the time of the Pléiades surveys.</p> <p> </p> <p><strong>Data</strong>: </p> <p>1 – Pléiades stereo images: </p> <p>A pre-eruption Pléiades stereopair was collected from 2013. A total of ten stereopairs were collected between the 23<sup>th</sup> of September 2021 and 2<sup>nd</sup> of October 2021 as part of the CIEST<sup>2</sup> initiative (https://www.poleterresolide.fr/ciest-2-nouvelle-generation-2/). Four additional pairs were acquired between the 11<sup>th</sup> of December 2021 and the 14<sup>th</sup> of January 2022 as part of the Dinamis initiative (https://dinamis.data-terra.org/). However, only some of these stereopairs were acquired with sufficiently large cloud-free areas around the eruption site. The following Pléiades stereo images were processed and are presented in this repository: </p> <p> </p> <table> <tbody> <tr> <td> <p>Date </p> </td> <td> <p>Sensor </p> </td> <td> <p>IDs </p> </td> </tr> <tr> <td> <p>2013-06-30, 12h02m </p> </td> <td> <p>PHR1B </p> </td> <td> <p>5944045101 & 5944046101 </p> </td> </tr> <tr> <td> <p>2021-09-26, 11h58m </p> </td> <td> <p>PHR1B </p> </td> <td> <p>5962414101 & 5962415101 </p> </td> </tr> <tr> <td> <p>2021-10-02, 12h02m </p> </td> <td> <p>PHR1B </p> </td> <td> <p>5988066101 & 5988067101 </p> </td> </tr> <tr> <td> <p>2022-01-01, 12h02m </p> </td> <td> <p>PHR1A </p> </td> <td> <p>6122469101 & 6122470101 </p> </td> </tr> <tr> <td> <p>2022-01-14, 12h02m </p> </td> <td> <p>PHR1B </p> </td> <td> <p>6135055101 & 6135057101 </p> </td> </tr> </tbody> </table> <p>Table 1: Date, sensor and image ID of the Pléiades stereoimages used in this repository. </p> <p> </p> <p>2 – Lidar pre-eruption surface: </p> <p>A lidar survey acquired in 2016 by the Spanish Mapping Agency (IGN, Spain) was downloaded through the portal: <a href="http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do?Serie=LIDAR">http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do?Serie=LIDAR</a>#. Specifically, we used the Digital Surface Model (DSM) product, available in 2x2 m Ground Sampling Distance (GSD). This means that trees and human structures were removed based using classification of the multiple returns of the lidar pulses. The coordinate reference system is REGCAN (UTM zone 28N, EPSG: 32628), and the heights are orthometric, using the height reference system REDNAP, built upon the geoid EGM08. Using the REDNAP geoid model, we converted the heights to meters above ellipsoid (WGS84), since the Pléiades data is acquired with satellite attitudes referred to the ellipsoid WGS84. </p> <p> </p> <p><strong>Methods</strong>:</p> <p>The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <em>parallel_stereo </em>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <em>point2dem</em>. Besides default parameters, the <em>parallel_stereo</em> parameters used for creation of the DEMs were the standard parameters, plus the following ones: </p> <p><em>--corr-tile-size 2048 --sgm-collar-size 256 --corr-seed-mode 3 --corr-max-levels 2 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</em></p> <p>Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean’s co-registration routines (<a href="https://github.com/dshean/demcoreg">https://github.com/dshean/demcoreg</a>, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.</p> <p>Lava outlines were manually digitized from the co-registered Pléiades orthoimages, excluding kipukas and major building constructions which were not covered by the lavas. The lava outlines are available as GeoPackages in the “GPKG” branch of the repository.</p> <p>Lava volume calculations were done using the average lava thickness, multiplied by the area covered by the lavas. The uncertainty in volume was assumed to be the Normalized Mean Absolute Deviation (NMAD, Höhle and Höhle, 2009), multiplied by the lava area. The TADR was calculated as the total volume divided by the time, in seconds, between the start of the eruption, defined as 2021-09-19 11:58:00 local time, and the acquisition of the Pléiades images. For the total TADR, we used the volume extracted from the Pléiades images from the 1<sup>st</sup> of January 2022, divided by the observed time of beginning and end of the eruption, defined as 2021-12-13 22:21:00, local time. The TADR values shown in this repository do not account for submarine lavas nor tephra deposits.</p> <p>In addition, another set of DEMs were produced automatically as soon as the images were made available by the on-demand processing service DSM-OPT provided by <a href="mailto:ForM@Ter">ForM@Ter</a> (https://en.poleterresolide.fr/on-demand-processing/#/mns). This processing is based on Micmac (D. Michéa and J.-P. Malet / EOST; E. Pointal, IPGP, Rupnik, 2017). The DEMs produced correspond to the file created automatically “A2_dsm_denoised.tif”. They were obtained in 1x1 m GSD, and they were cropped over the area of interest. These DEMs have not been co-registered. These data are available in the “MM” branch in the repository. </p> <p> </p> <p><strong>Results: Lava area, volumes and effusion rate:</strong> </p> <p> </p> <table> <tbody> <tr> <td> <p>Date </p> </td> <td> <p>Lava Area (km2) </p> </td> <td> <p>Lava thickness (m) </p> </td> <td> <p>Lava volume (10e+6 m3) </p> </td> <td> <p>TADR </p> <p>(m3 s-1) </p> </td> </tr> <tr> <td> <p>2021-09-26, 11h58m </p> </td> <td> <p>2.6 </p> </td> <td> <p>11.4±1.1 </p> </td> <td> <p>29.8±2.8 </p> </td> <td> <p>49.2±4.7 </p> </td> </tr> <tr> <td> <p>2021-10-02, 12h02m </p> </td> <td> <p>4.3 </p> </td> <td> <p>10.0±1.4 </p> </td> <td> <p>43.0±6.1 </p> </td> <td> <p>38.2±5.4 </p> </td> </tr> <tr> <td> <p>2022-01-01, 12h02m </p> </td> <td> <p>12.25 </p> </td> <td> <p>16.6±1.1 </p> </td> <td> <p>203.3±13.9 </p> </td> <td> <p>27.5±1.9 </p> </td> </tr> </tbody> </table> <p>Table 2: results of lava area, thickness, lava volume and TADR since the start of the eruption. </p> <p> </p> <p><strong>Repository structure:</strong></p> <p>zenodo_lapalma/<br> ├── ASP<br> │ ├── 20130630_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20210926_1158_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20210926_1158_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20211002_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20211002_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20220101_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ ├── 20220101_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> │ ├── 20220114_1202_lapalma_PL_2x2m_UTM28N_ASP_DEM.tif<br> │ └── 20220114_1202_lapalma_PL_2x2m_UTM28N_thickness.tif<br> ├── GPKG<br> │ ├── 20210925_1202_lapalma_PL_UTM28N_outline.gpkg<br> │ ├── 20211002_1202_lapalma_PL_UTM28N_outline.gpkg<br> │ └── 20220101_1202_lapalma_PL_UTM28N_outline.gpkg<br> └── MM<br> ├── 20130630_1202_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20210926_1158_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20211002_1230_PL_1x1m_UTM28N_MM_DEM.tif<br> ├── 20220101_1202_PL_1x1m_UTM28N_MM_DEM.tif<br> └── 20220114_1202_PL_1x1m_UTM28N_MM_DEM.tif</p> <p> </p> <p><strong>Acknowledgements</strong>: </p> <p>Pléiades images were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (<a href="https://en.poleterresolide.fr/">https://en.poleterresolide.fr/</a> ) and supported by ISDeform National Service of Observation) for the reference image acquired in 2013 and from the 23<sup>rd</sup> of September to the 2<sup>nd</sup> of October 2021, and through the Dinamis program (CNES, France) from the 12<sup>th</sup> of December 2021 to the 14<sup>th</sup> of January 2022 (image Pléiades©CNES2013,©CNES2021,©CNES2022, distribution AIRBUS DS) </p> <p> </p> <p><strong>Dataset Attribution</strong> </p> <p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).<br> Attribution required for copies and derivative works:</p> <p>The underlying dataset from which this work has been derived includes Pleiades material ©CNES (2013,2021,2022), distributed by AIRBUS DS, and data provided by the Spanish Mapping Agency (IGN, Spain), all rights reserved.</p> <p> </p> <p><strong>Dataset Citation</strong> </p> <p>Belart and Pinel (2022). “Pléiades co- and post-eruption survey in Cumbre Vieja volcano, La Palma, Spain”. Dataset distributed on Zenodo: 10.5281/zenodo.5833771</p> <p> </p> <p><strong>References:</strong> </p> <p>Höhle, J. and Höhle, M.: Accuracy assessment of digital elevation models by means of robust statistical methods, ISPRS J. Photogramm. Remote Sens., 64, 398–406, https://doi.org/10.1016/j.isprsjprs.2009.02.003, 2009.</p> <p>Nuth, C. and Kääb, A.: Co-registration and bias corrections of satellite elevation datasets for quantifying glacier thickness change, The Cryosphere, 5, 271–290, https://doi.org/10.5194/tc-5-271-2011, 2011.</p> <p>Rupnik, E., Daakir, M., & Deseilligny, M. P.: MicMac – a free, open-source solution for photogrammetry. Open Geospatial Data, Software and Standards, 2(1), 1-9, 2017.</p> <p>Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., and Morin, P.: An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery, ISPRS J. Photogramm. Remote Sens., 116, 101–117, https://doi.org/10.1016/j.isprsjprs.2016.03.012, 2016. </p>
Digital Elevation Model from Pléiades stereo images - Upper Tuolumne basin, California, 2017-08-13
<p><br> Digital Elevation Model (DEM) derived from a triplet of stereo images of the Pléiades satellite.<br> The images were acquired on 13th August 2017 and cover a part of the upper Tuolumne basin (California).<br> The DEM was calculated at a 3 m resolution with the Ames Stereo Pipeline software (Beyer et al., 2018).<br> Details about the processing of the images and the accuracy of the DEM are given in Deschamps-Berger et al. (2020).</p> <p> </p> <p>References<br> Beyer, R. A., Alexandrov, O., and McMichael, S. (2018). The Ames Stereo Pipeline: NASA’s open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537–548. https://doi.org/10.1029/2018EA00040</p> <p>Deschamps-Berger, C., Gascoin, S., Berthier,<br> E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M. (2020).<br> Snow depth mapping from stereo satellite imagery in mountainous terrain :<br> evaluation using airborne lidar data. <em>The Cryosphere</em>, (February):1–28. https://doi.org/10.5194/tc-14-2925-2020</p>
Tracking the 2018-2019 lava dome of Merapi volcano, Indonesia, using TanDEM-X and Pléiades
<p>This repository consists of a series of topographic surfaces of Merapi volcano (Indonesia), presented as a series of Digital Elevation Models (DEMs) differences with respect to a reference DEM of 2013. They are obtained from multiple Pléiades stereoscopic surveys acquired in 2019 and from TanDEM-X acquisitions between 2018-2019. These DEMs differences (5 Pléiades and 15 TandEM-X) are used to calculate thicknesses of a lava dome that appeared in August 2018. We then computed volumes and effusion rates from these DEMs.</p> <p>The resolution of the DEMs is 3*3 m pixel size and DEMs are georeferenced and provided under TIFF format.</p> <p>Pléiades DEMs have been masked (Nans) on areas covered by clouds.</p> <p>TanDEM-X DEMs have been masked (Nans) on areas that have not been unwrapped. They have also been corrected from a vertical offset by susbstracting the mean of non deformed areas to the initial DEM.</p> <p>Files are formatted as followed :</p> <p>-for Pléiades : YYYYMMDD_PL_msk.tiff</p> <p>-for TanDEM-X : YYYYMMDD_TDX_offset.tiff</p> <p>For the methodology to produce these DEMs, and for the applications of these DEMs, please refer to the recentely published paper "Tracking the evolution of the summit lava dome of Merapi volcano between 2018 and 2019 using DEMs derived from TanDEM-X and Pléiades data" with the following doi : https://doi.org/10.1016/j.jvolgeores.2022.107732</p> <p>or the following URL : https://www.sciencedirect.com/science/article/pii/S0377027322002633</p>
Pléiades DEM of 23 March 2017 - Khumbu region, Nepal
<p>This digital elevation model (DEM) was generated from a Pléiades stereo acquisition of 23 March 2017. The stereo processing was done using Amses Stereo pipeline. The DEM is posted at a 4 m resolution in UTM45\WGS84.</p>
Pléiades Digital Elevation Models of South Lhonak Lake (Sikkim, India)
<h1>Data and methods</h1> <p>On 3 October 2023, the collapse of a frozen lateral moraine into South Lhonak Lake triggered a multi-hazard cascade in the Sikkim Himalaya, India (Sattar et al, 2025). This repository contains two DEMs derived from Pléiades satellite images that were acquired before and after the event. </p> <ul> <li>A post-event DEM computed from a pair of PHR1A stereoscopic images acquired on 2023-10-29 (20231029.tif)</li> <li>A pre-event DEM computed from a triplet of PHR1A stereoscopic images acquired on 2022-10-18 (20221018.tif)</li> </ul> <p>The DEMs (height above the WGS84 ellipsoid) were posted at 1.0 m with UTM 45N projection (EPSG:32645) and coregistered to the GLO30 Copernicus DEM. They were computed with the MicMac software in the DSM-OPT service using the following configuration: correlation window size: 3x3, regularization factor: 0.05, vertical uncertainty: 0.1, potential accuracy threshold: 0.4 (Rupnik et al. 2017).</p> <p>These DEMs allow the analysis of topographic changes in the lake area. We included examples of such analysis with the addition of the High Mountain Asia 8 m DEM (Shean 2017).</p> <h1>Acknowledgements </h1> <p>Pléiades images were acquired and processed thanks to the CIEST2 service developed and performed with the French Space Agency (CNES) by FormaTerre, Solid Earth component of the Data Terra Research Infrastructure.</p> <h1>References</h1> <div> <p>Sattar et al. (2025) The Sikkim flood of October 2023: Drivers, causes and impacts of a multihazard cascade. Science, eads2659, https://doi.org/10.1126/science.ads2659</p> Rupnik, E., Daakir, M., & Pierrot Deseilligny, M. (2017). MicMac–a free, open-source solution for photogrammetry. <em>Open geospatial data, software and standards</em>, <em>2</em>, 1-9. https://doi.org/10.1186/s40965-017-0027-2</div> <div> </div> <div>Shean, D. (2017). High Mountain Asia 8-meter DEM Mosaics Derived from Optical Imagery, Version 1 [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/KXOVQ9L172S2. Date Accessed 07-29-2024.</div>
Spot6 and Pléiades Digital Elevation Models (DEMs) and elevation change grid to understand the South Lhonak lake (Sikkim) flood of October 2023
<p>===========================</p> <p>Introduction</p> <p> </p> <p>On 3 October 2023, a multi-hazard cascade in the Sikkim Himalaya, India, was triggered by the collapse of a frozen lateral moraine into South Lhonak Lake</p> <p>We share here the SPOT6 and Pléiades DEMs and the elevation change maps derived from these images. The collection includes four files:</p> <p>Two pre-event DEMs from SPOT6</p> <p>2018-12-01_Lhonak_DEM_SGM_4m_on_Cop30_BiasCorr_NoData_aligned.tif</p> <p>2018-12-08_Lhonak_DEM_SGM_4m_on_Cop30_BiasCorr_NoData_aligned.tif</p> <p>One post-event mosaic DEM from Pléiades </p> <p>Post-Event_DEM_SGM_october2023.tif</p> <p>One grid of elevation change from 2018 to 2023</p> <p>dh_mosaic_Lhonak_SGM_median.tif</p> <p> </p> <p>===========================</p> <p>Methods</p> <p>The SPOT6 and Pléiades stereo-images were processed using the Ames Stereo Pipeline (ASP, Beyer et al., 2018), yielding a DEM in 4x4 m GSD. The processing was done using as only input the stereo-images and their orientation information, as Rational Polynomial Coefficients (RPCs). The parallel_stereo routine performs all the steps needed in the correlation of the stereo-images, yielding a pointcloud which is then interpolated using the routine point2dem. We used the semi global matching algorithm and the set of processing parameters from Deschamps-Berger et al. (2020)</p> <p>Beyer, R. A., Alexandrov, O., and McMichael, S.: The Ames Stereo Pipeline: NASA’s Open Source Software for Deriving and Processing Terrain Data, Earth and Space Science, 5, 537–548, https://doi.org/10.1029/2018EA000409, 2018.</p> <p>Deschamps-Berger, C., Gascoin, S., Berthier, E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M.: Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data, The Cryosphere, 14, 2925–2940, https://doi.org/10.5194/tc-14-2925-2020, 2020.</p> <p> </p> <p>===========================</p> <p>Data Specifications:</p> <p>Cartographic projection: UTM zone 45N (EPSG:32645)</p> <p>Origin of Elevation: meters above WGS84 ellipsoid</p> <p>Raster data format: GeoTIFF</p> <p>NoData value : -9999</p> <p> </p> <p>===========================</p> <p>Acknowledgements:</p> <p>Pléiades and SPOT6 images were acquired thanks to the CIEST2 service developed and performed with the French Space Agency (CNES) by FormaTerre, Solid Earth component of the Data Terra Research Infrastructure</p> <p> </p> <p>===========================</p> <p>Dataset Attribution:</p> <p>This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).</p> <p> </p>
GTnum Pléiades questionnaire
<p>Questionnaire sur la classe virtuelle pendant le confinement diffusé dans le cadre de la recherche GTnum Pléiades financée par la Direction du numérique éducatif (Ministère de l'Education Nationale, France) pilotée par le laboratoire Circeft.</p>
Plan de gestion de données du GTnum Pléiades
<p>Le plan de gestion de données du GTnum Pléiades décrit les données récoltées lors de la recherche, leur mode de stockage en spécifiant notamment celles qui sont partagées dans l'entrepôt Zenodo</p>
Plan de Gestion des Données du GTnum Pléiades
<p>Plan de gestion des données construit pour la recherche GTnum Pléiades (2020-2022)</p>
Map of the rate of elevation change of Mont-Blanc glaciers derived from Pléiades stereo-images
<p>This collection contains three map of elevation changes derived form Pléiades images acquired in 2012, 2021 and 2022 over the Mont-Blanc Massif (Alps) with a horizontal grid spacing of 4 m. They were derived from stereo-pairs acquired 19 August 2012, 15 August 2021, 12 October 2022, 8 August 2022 and 5 October 2022. No data are indicated by the -9999 value.</p> <p>We generated 4-m DEMs from five Pléiades stereo-pairs using the semi-global matching algorithm of the Ames Stereo Pipeline (Beyer et al., 2018) and the set of parameters defined in Deschamps-Berger et al. (2020). The DEMs were first coregistered on stable terrain, masking out glacierized areas using a glacier inventory from year 2015 (Paul et al., 2020). Spatially-coherent biases in the elevation difference maps were next corrected using a polynomial fit across-track and a spline fit in the along-track direction (Falaschi et al., 2023). </p> <p>Pléiades stereo-images were obtained thanks to DINAMIS Project, for “Dispositif Institutionnel National d’Approvisionnement Mutualisé en Imagerie Satellitaire”, a French platform that acquires and distributes very high resolution Earth satellite imagery for French and foreign institutional users under specific subscription conditions.</p>
Bibliothèque Zotero de la recherche GTnum Pléiades
<p>Ensemble des références bibliographiques entrées dans Zotero pour étayer les travaux de la recherche GTnum Pléiades.</p>
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