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53 results for “copernicus”
Set of Copernicus Sentinel-1 images around Iceland
<p>Set of Sentinel-1 images downloaded from the Copernicus API. They are set around Iceland and intended to validate and test ice block detection algorithms</p>
Collocated model and observation datasets for the validation of the Copernicus Mediterranean Sea Waves Analysis and Forecast for the period 2018-2020.
<p>The collocated values are used for skill evaluation of the Mediterranean Sea Waves Analysis and Forecast system for a three-year-long period (Korres et al., 2022). The list of datasets includes:</p> <ol> <li>The collocated model (analysis) – buoy values for significant wave height Hs (Insitu_Hs.mat)</li> <li>The collocated model (analysis) – buoy values for spectral moments (0,2) wave period Tm (Insitu_Tm.mat)</li> <li>The collocated model (first – guess) – satellite values for significant wave height Hs (Satellite_Hs.mat)</li> <li>The collocated model – satellite values for wind speed U10 (Satellite_U10.mat)</li> </ol> <p>Each .mat file contains a header for the variables included. Collocations can be used to estimate standard quality metrics (e.g. scatter index, bias, root-mean-squared-difference). Procedures to produce these model-observation collocated datasets and determine the overall skill assessment are described in detail in Ravdas et al. (2018) and Oikonomou et al. (2022). The buoy (in-situ) measurements are obtained from the product INSITU_GLO_WAV_DISCRETE_MY_013_045 (EU Copernicus Marine Service Product, 2022a), and associated variables contain a quality flag (“time_qc”, “position_qc”, “buoy_Hs_qc”, “buoy_Tm_qc”) (de Alfonso et al., 2022a,b). In addition, the model first-guess significant wave height and the wind speed forcing (Hersbach et al., 2023) are collocated with available satellite observations (EU Copernicus Marine Service Product, 2022b) over the entire model domain.</p> <p>References</p> <p>de Alfonso, M., Manzano, F., and Gallardo, A. (2022a): EU Copernicus Marine Service Quality Information Document for the In Situ TAC Product, INSITU_GLO_WAV_DISCRETE_MY_013_045, Issue 5.0, Mercator Ocean International, <a href="https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-INS-QUID-013-045.pdf">https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-INS-QUID-013-045.pdf</a></p> <p>de Alfonso, M., Manzano, F., Gallardo, A., and In Situ TAC (2022b): EU Copernicus Marine Service Product User Manual for Multi-Year WAVE In Situ Product, INSITU_GLO_WAV_DISCRETE_MY_013_045, Issue 2.0, Mercator Ocean International, <a href="https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-INS-PUM-013-045.pdf">https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-INS-PUM-013-045.pdf</a></p> <p>EU Copernicus Marine Service Product (2022a): Multi-Year WAVE In Situ Product, Mercator Ocean International, [dataset], <a href="https://doi.org/10.17882/70345">https://doi.org/10.17882/70345</a></p> <p>EU Copernicus Marine Service Product (2022b): Global Ocean L 3 Significant Wave Height From Reprocessed Satellite Measurements, Mercator Ocean International, [dataset], <a href="https://doi.org/10.48670/moi-00176">https://doi.org/10.48670/moi-00176</a></p> <p>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47 (Accessed on 26-09-2023)</p> <p>Korres, G., Oikonomou, C., Denaxa, D., & Sotiropoulou, M. (2022): Mediterranean Sea Waves Analysis and Forecast (CMEMS MED-Waves, MEDWAΜ4 system) (Version 1) [Data set]. Copernicus Monitoring Environment Marine Service (CMEMS). <a href="https://doi.org/10.25423/CMCC/MEDSEA_ANALYSISFORECAST_WAV_006_017_MEDWAM4">https://doi.org/10.25423/CMCC/MEDSEA_ANALYSISFORECAST_WAV_006_017_MEDWAM4</a></p> <p>Oikonomou, C., Denaxa D., and Korres, G. (2022): EU Copernicus Marine Service Quality Information Document for the Mediterranean Sea Waves Reanalysis, MEDSEA_ANALYSISFORECAST_WAV_006_017, Issue 2.2, Mercator Ocean International, <a href="https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-MED-QUID-006-017.pdf">https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-MED-QUID-006-017.pdf</a>.</p> <p>Ravdas, M., Zacharioudaki, A., and Korres, G. (2018): Implementation and validation of a new operational wave forecasting system of the Mediterranean Monitoring and Forecasting Centre in the framework of the Copernicus Marine Environment Monitoring Service, Nat. Hazards Earth Syst. Sci., 18, 2675–2695, <a href="https://doi.org/10.5194/nhess-18-2675-2018">https://doi.org/10.5194/nhess-18-2675-2018</a></p> <p> </p>
Copernicus Global Land Service: Land Cover 100m: epoch 2016: Africa demo (deprecated)
<p><strong><em>This demo dataset over Africa is deprecated. Please see <a href="https://doi.org/10.5281/zenodo.3518025">this global dataset</a> instead.</em></strong></p> <p>Demonstration land cover maps over Africa at 100m resolution for epoch year 2016, from the global component of the Copernicus Land Service and derived from PROBA-V satellite observations.</p> <p>The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers (e.g. density of input data).</p> <p>For the consolidated epoch 2016, the classifier and regression models of base year 2015 are used, and the time window of the classified metrics covers one full year prior (2015) and pastor (2017) data. The layers with the probability of the discrete classification and the standard deviation of the cover fractions are only provided for the base year (epoch 2015). The Change Consistency Layer that checks consistency between classifier and break detection, is only available for the most recent (near-real time) year (epoch 2018).</p> <p> </p> <p><a href="https://africa.lcviewer.vito.be/2016">View the maps and area statistics</a></p> <p><a href="https://land.copernicus.eu/global/documents/lcc100/all/pum">Product User Manual</a></p> <p><a href="https://land.copernicus.eu/global/products/lc">More land cover change product information and documentation</a></p> <p> </p>
Project Panormos Archaeological Survey: Satellite Image (gis-copernicus)
<p>This forms part of the preliminary open data release for the Project Panormos archaeological survey.</p> <p>This "panormos/gis-copernicus" repository contains a raster used as a background for mapping the survey data. This image was derived from <a href="https://scihub.copernicus.eu">Copernicus Sentinel Data</a>, and is redistributed in compliance with the legal notice on the use of Copernicus Sentinel Data</p> <p> </p>
Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2016: Globe
<p>Consolidated epoch 2016 from the Collection 3 of annual, global 100m land cover maps.</p> <p>Other available epochs: <a href="https://doi.org/10.5281/zenodo.3939038">2015</a> <a href="https://doi.org/10.5281/zenodo.3518036">2017</a> <a href="https://doi.org/10.5281/zenodo.3518038">2018</a> <a href="https://doi.org/10.5281/zenodo.3939050">2019</a></p> <p>Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.</p> <p>The maps include</p> <ul> <li>a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,</li> <li>a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes</li> <li>a forest type layer</li> <li>quality layers on input data density and on the confidence of the detected land cover change</li> </ul> <p><a href="https://land.copernicus.eu/global/lcviewer">Click here to view the maps</a></p> <p><a href="https://land.copernicus.eu/global/lcviewer">More information about the land cover maps</a></p> <p><a href="https://doi.org/10.5281/zenodo.3606295">Product User Manual</a></p>
COPERNICUS GRASSLAND LAYER FOR CHANGE DETECTION ON "MURGIA ALTA" - TIME T1 DATA
<p><strong>Time T1 data:</strong> Copernicus Natural Grasslands layer at 20 meters spatial resolution; year 2012; subset of the "Murgia Alta" protected area; reprojected in WGS84/UTM33.</p>
Land Subsidence PSI Measurements (2021-2023) in Oran, Algeria, Using Copernicus Sentinel-1 Data and SNAPPING Service
<p>We have processed data from the Copernicus Sentinel-1 satellite, covering the period from January 2021 to September 2023, over the borader area (around 48400 square kilometers) of Oran, Algeria. This analysis utilized the SNAPPING Persistent Scatterers Interferometry (PSI) service from the Geohazards Exploitation Platform (GEP; accessible at <a href="https://geohazards-tep.eu">https://geohazards-tep.eu</a>). Processing was performed by the EO.Lab of AUTh. </p> <p>Measurements contain average Line-of-Sight (LoS) velocities, corresponding uncertainties, and the complete displacement time series. The dataset contains ~3M points covering approximately 7800 sq.km (density of 385 points/km). </p> <p>References</p> <p>[1] Foumelis, M.; Delgado Blasco, J.M.; Brito, F.; Pacini, F.; Papageorgiou, E.; Pishehvar, P.; Bally, P. SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping. Remote Sens. 2022, 14, 6075. <a href="https://doi.org/10.3390/rs14236075">https://doi.org/10.3390/rs14236075</a></p> <p>[2] SNAPPING – Surface motioN mAPPING Sentinel-1 on-demand processing service, Online tutorial, <a href="https://docs.terradue.com/geohazards-tep/tutorials/Snapping.html">https://docs.terradue.com/geohazards-tep/tutorials/Snapping.html</a>.</p>
Copernicus EMS flood activations delimitations (2012 - 2020) rasterised at 30m and aggregated per year and season
<p>This dataset was created as part of the <a href="https://opendatascience.eu/">Geo-harmonizer project</a>, with the scope of making open data easier to access. It contains all the flood activations mapped by the <a href="https://emergency.copernicus.eu/mapping/list-of-activations-rapid">Copernicus Emergency Rapid Mapping Service</a> between 2012 and 2020. To obtain these GeoTIFFs, the vector data packages from CEMS were individual downloaded, rasterized and mosaicked per year and season, resampled at 30-m and reprojected to <a href="https://epsg.io/3035">EPSG 3035: ETRS89-extended / LAEA Europe</a>. If no CEMS flood activation was identified in a specific year and season, the raster was not created. The rasters are provided as COG files, type=16Int, the flooded area pixels have value 100, nodata value is 255.</p> <p>To allow an easier and faster search through all 2012 - 2020 CEMS flood activations, we have prepared a point vector layer (geojson) containing one point for each flood activation area of interest with the following attributes attached: CEMS identification number <ems_id>, area of interest defined by CEMS <ems_aoi>, URL link to the CEMS activation <ems_link>, year of the event <year_start>, <year_end> , <season> and the name of the <geo_harmonizer_raster> where the 30m rasterised delimitations of the flooded areas of the corresponding flood activation can be found. </p> <p>For any additional questions regarding the data, please contact the author at codrina.ilie[at]terrasigna.com.</p> <p>The Copernicus Emergency Rapid Mapping Service data access policy is available <a href="https://emergency.copernicus.eu/mapping/sites/default/files/files/CopernicusEMS-Data_and_Dissemination_Policy.pdf">here</a>.</p>
Nicolaus Copernicus Monument
Processing 1281 images in 7h https://youtu.be/oDbP5c-IXEY The Nicolaus Copernicus Monument in Kraków, Poland was designed by sculptor Cyprian Godebski in 1899 and completed in 1900. It has become a landmark of the city, as it commemorates one of the most famous alumni of the Jagiellonian University of Kraków. Nicolaus Copernicus (1473-1543) was a Renaissance scientist and scholar. His heliocentric model of the universe was revolutionary and contributed greatly to the emergence and development of modern science. He was an astronomer, mathematician, translator, physician, economist, and had a doctorate in canon law. A true polymath, or "Renaissance man", whose life and work has become a part of cultural heritage of the world. The 3D model features the monument of Copernicus wearing a purple bowtie. It was put on it as a part of an artistic happening organized by the University's students to promote upcoming Juvenalia, a yearly student festival celebrating youth culture, freedom of expression and creativity. Source: Objaverse 1.0 / Sketchfab
Copernicus Climate Change Service data for the pypsa-entsoe Github repository
<p>Files needed for the https://github.com/matteodefelice/pypsa-entsoe repository.</p>
Data Archive for James and Ross, 2023 (submitted): The Timing of the ENSO Spring Barrier in the Copernicus Dynamical Models
<p>This archive contains data used in creating figures for James and Ross, 2023 (submitted): The Timing of the ENSO Spring Barrier in the Copernicus Dynamical Models.</p> <p>The data are provided in csv files, and the file "README" explains the contents of each file.</p> <p> </p>
(Copernicus - WEkEO Hackathon 22 – 23 JUNE 2023 ) Digital Cartography Simulation of Essential ocean variables (EOV) (educational support resource in space oceanography)
<p>Description of idea : The multidimensional view of the Earth and its immediate environment that is provided by space borne sensors, operating at many wavelengths and directed at many different phenomena, has revolutionized man's understanding of his planet and the surrounding space environment.<strong>(John H. McElroy.,1985),</strong></p> <p>Earth observation satellites measuring in the visible and infrared spectral domain provide a global perspective for many required to determine the role of the ocean in the global climate system, as well as the effects on the ocean of a changing climate <strong>(James A. Yoder and all.,2014).</strong></p> <p>Data visualization by video graphics technology is a digital modeling technique also a description or analogy used to help visualize something that cannot be observed directly which exploits the bases of scientific knowledge in a data processing system by the use of mathematical and statistical tools and analysis and forecasting methods to visualize what is hidden behind the data. This work is inspired by the general principle of numerical modeling and data processing, which takes into consideration (the observation of natural phenomena, and the statistical processing of scientific data, which are at the base of the functioning of natural variation).</p> <p>We see on the same simulation scale several other spatial and temporal scale, for example the simulation of SST of several years with a large gap between the years, also the simulation of the displacement of surface currents with the variations of the SST, in other words the document can be used in pedagogy.</p> <p> </p> <p>Bibliographic reference:<br> -Monitoring Earth's Ocean, Land, and Atmosphere from Space-Sensors, Systems, and Applications, edited by Abraham Schnapf, American Institute of Aeronautics and Astronautics, 1985<br> -Optical Radiometry for Ocean Climate Measurements, Elsevier Science & Technology, 2014</p> <p> </p> <p> </p>
Copernicus X-Ray Observations
Copernicus was the third satellite in the OAO program. It was launched the 21 august of 1972 and operated till 1981. The main instrument was an ultraviolet telescope with a spectrometer to measure interstellar absorption lines in the spectra of stellar objects. However it carried also an X-ray experiment provided by University College of London/MSSL consisted in 4 co-aligned experiments sensitive in the 1-10 keV energy range. This database accesses the raw FITS file containing data obtained from the UCL X-ray Experiment (UCLXE) package on board Copernicus. This is a service provided by NASA HEASARC .
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