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The map can be used to spatially manage in-field agricultural activities such as nitrogen fertiliser, seeding density and irrigation. The map is the result of a multi-year product derived from the processing of Copernicus Sentinel-2 data. A first prototype was obtained in the H2020 FATIMA project (grant no. 633945) and further refined in the FFG ASAP16 ARmEO project. Products derived from other date ranges are available on request from the Institute of Geomatics, University of Natural Resources and Life Sciences, BOKU (Austria).","keywords":[],"license":"CC-BY-SA-4.0","providers":[{"url":"https://eodc.eu/","name":"EODC","roles":["host"]},{"url":"https://boku.ac.at/","name":"BOKU","roles":["licensor"]}],"summaries":{},"extent":{"spatial":{"bbox":[[8.675376233657454,45.81979116602317,17.89480854415766,49.62308593333951]]},"temporal":{"interval":[["2017-01-01T00:00:00Z","2020-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|INTRA_FIELD_CROP_GROWTH_POTENTIAL"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|INTRA_FIELD_CROP_GROWTH_POTENTIAL/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/INTRA_FIELD_CROP_GROWTH_POTENTIAL/queryables"}]},{"type":"Collection","id":"EODC|RUCIO_SENTINEL2_MFCOVER","stac_extensions":["https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/eo/v1.0.0/schema.json","https://stac-extensions.github.io/raster/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.2.0/schema.json"],"stac_version":"1.0.0","title":"Monthly Composite of Fraction of Vegetation Cover","description":"Monthly composite of fraction of vegetation cover. 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This product is most applicable to users interested in remote sensing applications and is also suitable for calibration purposes. The products are calibrated and corrected for the SAR antenna pattern and range-spreading loss. Radar backscatter can be derived from the products for geophysical modelling, but no correction is applied for terrain-induced radiometric effects. The images are not geocoded, and terrain distortion (foreshortening and layover) has not been removed. The pixel size is 12.5 m (range - across track) x 12.5 m (azimuth - along track).\n\n[https://earth.esa.int/eogateway/catalog/ers-1-2-sar-im-precision-l1-sar_imp_1p-?text=ERS](https://earth.esa.int/eogateway/catalog/ers-1-2-sar-im-precision-l1-sar_imp_1p-?text=ERS).","keywords":["ers","esa","sar"],"license":"proprietary","providers":[{"url":"https://earth.esa.int/web/guest/home","name":"ESA","roles":["producer","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host","processor"]}],"summaries":{"platform":["ERS"],"proj:epsg":[4326],"providers":[{"url":"https://earth.esa.int/web/guest/home","name":"ESA","roles":["producer","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host","processor"]}],"published":{"maximum":"None","minimum":"2025-02-26T14:43:51Z"},"end_datetime":{"maximum":"2011-07-04T00:00:00Z","minimum":"1991-07-27T00:00:00Z"},"constellation":["ERS"],"start_datetime":{"maximum":"2011-07-04T00:00:00Z","minimum":"1991-07-27T00:00:00Z"},"sat:orbit_state":["ascending","descending"],"processing:level":["L1"],"sar:product_type":["SAR_IMP_1P"],"sar:polarizations":["HH","VV"],"sar:frequency_band":["C"],"sat:absolute_orbit":[1,84719],"processing:datetime":{"maximum":"None","minimum":"2025-02-26T14:43:51Z"},"sar:instrument_mode":["IM"],"sar:resolution_range":[30]},"extent":{"spatial":{"bbox":[[9.5,46.4,17.2,49.0]]},"temporal":{"interval":[["1991-07-27T00:00:00Z","2011-07-04T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SAR_IMP_1P"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SAR_IMP_1P/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"license","href":"https://earth.esa.int/eogateway/documents/20142/1564626/Terms-and-Conditions-for-the-use-of-ESA-Data.pdf","title":"ESA's Earth Observation Terms and Conditions"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SAR_IMP_1P/queryables"}]},{"type":"Collection","id":"EODC|SAR_IMS_1P","stac_extensions":["https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/timestamps/v1.1.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/processing/v1.2.0/schema.json","https://stac-extensions.github.io/archive/v1.0.0/schema.json#","https://stac-extensions.github.io/alternate-assets/v1.1.0/schema.json"],"stac_version":"1.0.0","title":"ERS-1/2 SAR Image Mode Single Look Complex Level-1","description":"The SAR_IMS_1P product from ERS-1/2 is a single look complex acquired in Image Mode. It is a digital image, with slant range and phase preserved, generated from raw SAR data using up-to-date auxiliary parameters. This product is intended for users wishing to perform SAR quality assessment, calibration and interferometric applications. The pixel size is 8 m (range - across track) x 4 m (azimuth - along track). The scene area is 100 km (range) x at least 102.5 km (azimuth). The pixel depth is 32 bits signed integer (16 bits I, 16 bits Q). The total product volume is 575 MB. The projection is slant range. The number of looks is 1.\n\n[https://earth.esa.int/eogateway/catalog/ers-1-2-sar-im-single-look-complex-l1-sar_ims_1p-](https://earth.esa.int/eogateway/catalog/ers-1-2-sar-im-single-look-complex-l1-sar_ims_1p-).","keywords":["ers","esa","sar"],"license":"proprietary","providers":[{"url":"https://earth.esa.int/web/guest/home","name":"ESA","roles":["producer","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host","processor"]}],"summaries":{"platform":["ERS"],"proj:epsg":[4326],"providers":[{"url":"https://earth.esa.int/web/guest/home","name":"ESA","roles":["producer","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host","processor"]}],"published":{"maximum":"None","minimum":"2025-02-26T14:48:08Z"},"end_datetime":{"maximum":"2011-07-04T00:00:00Z","minimum":"1991-07-27T00:00:00Z"},"constellation":["ERS"],"start_datetime":{"maximum":"2011-07-04T00:00:00Z","minimum":"1991-07-27T00:00:00Z"},"sat:orbit_state":["ascending","descending"],"processing:level":["L1"],"sar:product_type":["SAR_IMS_1P"],"sar:polarizations":["HH","VV"],"sar:frequency_band":["C"],"sat:absolute_orbit":[1,84719],"processing:datetime":{"maximum":"None","minimum":"2025-02-26T14:48:08Z"},"sar:instrument_mode":["IM"],"sar:resolution_range":[30]},"extent":{"spatial":{"bbox":[[9.5,46.4,17.2,49.0]]},"temporal":{"interval":[["1991-07-27T00:00:00Z","2011-07-04T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SAR_IMS_1P"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SAR_IMS_1P/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"license","href":"https://earth.esa.int/eogateway/documents/20142/1564626/Terms-and-Conditions-for-the-use-of-ESA-Data.pdf","title":"ESA's Earth Observation Terms and Conditions"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SAR_IMS_1P/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_ALPS_WETSNOW","stac_extensions":["https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.0.0/schema.json"],"stac_version":"1.0.0","title":"Sentinel-1 Alps WetSnow","description":"Sentinel-1 based Wet Snow Maps in the EODC Data Catalogue are available for the full Alpine domain (50°N / 4°E – 43°N / 18°E) for the melting seasons (March – July) 2019 and 2021.\n\nThe Wet Snow Map (WSM) provides binary information on the snow melt extent, based on Sentinel-1 C-band Synthetic Aperture Radar (SAR) repeat pass data, at the image acquisition time (given in UTC). At C-band, the typical one-way penetration depth of the radar signal into a dry seasonal snow pack is about 20 m, but reduces to only 3 cm for a wet snow pack with a liquid water content of 5% by volume (Mätzler, 1987). This means that for wet snow, the C-band radar signal is reflected and scattered at the surface and the uppermost centimetres of the snowpack. But for dry seasonal snow, a main contribution of the measured signal comes from the snow / ground interface, constraining a reliable discrimination of dry snow areas and snow free ground from Sentinel-1 SAR satellite data. The WSM generated with the change detection method of Nagler et al. (2016) indicates if there is any melt layer within the snowpack.\n\nProducts are generated per Sentinel-1 track with a pixel spacing of 100 m x 100 m. Sentinel-1A and Sentinel-1B data from ascending (afternoon acquisitions) and descending (morning acquisitions) orbits are used for the WSM product generation. WSM products are generated every 6 days per Sentinel-1 track for the melting seasons 2019 and 2021.\n\nTo avoid misclassifications in the valleys, e.g. due to agricultural activities, an a priori information on the snow-covered area per pixel is added. Information on the areal snow cover fraction per pixel is generated from daily optical satellite data of Sentinel-3 A&B SLSTR & OLCI with a pixel spacing of 200 m x 200 m. The fractional snow cover (FSC) per pixel is generated with a multi-spectral unmixing approach with locally adaptive end-member selection (Keuris et al., 2023). Earth observations by optical satellite data can be limited by clouds, while SAR satellite measurements are independent of cloud coverage or daylight. To fully exploit the Sentinel-1 SAR time series for the WSM generation, the snow cover fraction for cloud covered pixels in the optical satellite data is assimilated using a snowpack model driven by ERA5 reanalysis data of gridded temperature and precipitation fields. From the resulting map of the same date as the Sentinel-1 acquisition, pixels with at least 40% FSC are considered for the wet snow classification from Sentinel-1 data. The three categories 1) snow free pixels, 2) pixels with less than 40% FSC, and 3) pixels with dry snow are merged into one class in the WSM product.\n\nWater bodies, forested areas, and pixels affected by radar shadow, layover or foreshortening are masked in the WSM product. Water bodies are masked based on the maximum extent of permanent and seasonal water of the Copernicus Global Surface Water yearly classifications 2017 – 2021 (Pekel et al., 2016). The water layers with an original pixel spacing of about 30 m x 30 m are reprojected and aggregated to the grid of the WSM product, and considered as water if an aggregated pixel is covered by more than 30% water. Forests are masked based on the Copernicus Tree Cover Fraction product with an original pixel spacing of about 100 m x 100 m for the reference year 2019 (Buchhorn et al., 2020), based on optical satellite data acquired between 1 April 2017 and 31 March 2020.\n\n*Further information and links to access to satellite data and auxiliary layers used for the WSM generation:*\n\nSatellite input data are freely available after registration:\n- Copernicus Sentinel-1 SAR and Sentinel-3 SLSTR & OLCI data: [Copernicus Data Space Ecosystem | Europe's eyes on Earth](https://dataspace.copernicus.eu/)\n\nAuxiliary layers are freely available and accessible via the following links:\n- Copernicus Global Surface Water: [Global Surface Water - Data Access (global-surface-water.appspot.com)](https://global-surface-water.appspot.com/download))\n- Copernicus Tree Cover Fraction 2019: [Land Cover 2019 (raster 100 m), global, yearly – version 3 — Copernicus Land Monitoring Service](https://land.copernicus.eu/en/products/global-dynamic-land-cover/copernicus-global-land-service-land-cover-100m-collection-3-epoch-2019-globe)\n- ECMWF ERA5 data: [https://cds.climate.copernicus.eu/](https://cds.climate.copernicus.eu/)\n\n*References:*\n\n- Buchhorn, M., Bertels, L., Smets, B., De Roo, B., Lesiv, M., Tsendbazar, N. - E., Masiliunas, D., Li, L., 2020. Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Algorithm Theoretical Basis Document; 2020. DOI 10.5281/zenodo.3606361\n- Keuris, L., Hetzenecker, M., Nagler, T., Mölg, N., Schwaizer, G., 2023. An Adaptive Method for the Estimation of Snow-Covered Fraction with Error Propagation for Applications from Local to Global Scales. Remote Sensing 15, 1231. https://doi.org/10.3390/rs15051231\n- Mätzler, C., 1987. Applications of the interaction of microwaves with the natural snow cover. Remote Sensing Reviews 2, 259–387. https://doi.org/10.1080/02757258709532086\n- Nagler, T., Rott, H., Ripper, E., Bippus, G., Hetzenecker, M., 2016. Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR. Remote Sensing 8, 348. https://doi.org/10.3390/rs8040348\n- Pekel, J.-F., Cottam, A., Gorelick, N., Belward, A.S., 2016. High-resolution mapping of global surface water and its long-term changes. 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The preprocessing workflow includes following steps: applying precise orbit file, thermal noise removal, radiometric calibration, radiometric terrain correction, and geometric terrain correction. In the end, Gamma Nought backscatter are reprojected and resampled into Equi7 Grid system at 10m pixels spacing.","keywords":["sentinel-1","Backscatter","Gamma0","Radiometric Terrain Corrected","RTC","wizsard"],"license":"proprietary","providers":[{"url":"https://www.tuwien.at/mg/geo","name":"TU Wien","roles":["processor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["processor","host"]}],"summaries":{"eo:bands":[{"name":"VV","common_name":"Gamma0_VV","description":"Gamma0 Nought in VV polarization","center_wavelength":55465.76},{"name":"VH","common_name":"Gamma0_VH","description":"Gamma0 Nought in VH polarization","center_wavelength":55465.76},{"name":"HH","common_name":"Gamma0_HH","description":"Gamma0 Nought in HH polarization","center_wavelength":55465.76},{"name":"HV","common_name":"Gamma0_HV","description":"Gamma0 Nought in HV polarization","center_wavelength":55465.76},{"name":"LIA","common_name":"Local Incidence Angle","description":"Local incidence angle image for backscatter image"},{"name":"Mask","common_name":"Mask","description":"Mask image for backscatter image"}],"platform":["sentinel-1a","sentinel-1b","sentinel-1c"],"constellation":["sentinel-1"]},"extent":{"spatial":{"bbox":[[9,46,24,50]]},"temporal":{"interval":[["2014-10-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GMR0"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GMR0/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_GMR0/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_GRD","stac_extensions":["https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/timestamps/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.0.0/schema.json","https://stac-extensions.github.io/item-assets/v1.0.0/schema.json","https://stac-extensions.github.io/alternate-assets/v1.1.0/schema.json","https://stac-extensions.github.io/eo/v1.0.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json"],"stac_version":"1.0.0","title":"Sentinel-1 SAR L1 GRD","description":"Sentinel-1 Level-1 Ground Range Detected (GRD) products consist of focused SAR data that has been detected, multi-looked and projected to ground range using the Earth ellipsoid model WGS84. The ellipsoid projection of the GRD products is corrected using the terrain height specified in the product general annotation. The terrain height used varies in azimuth but is constant in range (but can be different for each IW/EW sub-swath). Ground range coordinates are the slant range coordinates projected onto the ellipsoid of the Earth. Pixel values represent detected amplitude. Phase information is lost. The resulting product has approximately square resolution pixels and square pixel spacing with reduced speckle at a cost of reduced spatial resolution. For the IW and EW GRD products, multi-looking is performed on each burst individually. All bursts in all sub-swaths are then seamlessly merged to form a single, contiguous, ground range, detected image per polarisation.","keywords":["sentinel","copernicus","esa","sar","radar"],"license":"proprietary","providers":[{"url":"https://earth.esa.int/web/guest/home","name":"ESA","roles":["producer","processor","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host"]}],"summaries":{"eo:bands":[{"name":"VH","description":"VH band: vertical transmit and horizontal receive"},{"name":"HH","description":"HH band: horizontal transmit and horizontal receive"},{"name":"HV","description":"HV band: horizontal transmit and vertical receive"},{"name":"VV","description":"VV band: vertical transmit and vertical receive"}],"platform":["sentinel-1a","sentinel-1b"],"published":["2023-06-19T13:16:22Z"],"constellation":["sentinel-1"],"sar:looks_range":[2,3,5,6],"sat:orbit_state":["ascending","descending"],"sar:product_type":["GRD"],"sar:looks_azimuth":[1,2,6],"sar:polarizations":["HH","VV","HV","VH",["HH","HV"],["VV","VH"]],"sar:frequency_band":["C"],"sar:instrument_mode":["IW","EW","SM"],"sar:center_frequency":[5.405],"sar:resolution_range":[9,20,23,50,93],"sar:resolution_azimuth":[9,22,23,50,87],"sar:pixel_spacing_range":[3.5,10,25,40],"sar:observation_direction":["right"],"sar:pixel_spacing_azimuth":[3.5,10,25,40],"sar:looks_equivalent_number":[3.7,29.7,398.4,4.4,81.8,2.8,10.7,123.7]},"extent":{"spatial":{"bbox":[[-180,-90,180,90]]},"temporal":{"interval":[["2014-10-03T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GRD"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GRD/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"license","href":"https://scihub.copernicus.eu/twiki/do/view/SciHubWebPortal/TermsConditions","title":"Sentinel License"},{"rel":"about","href":"https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-1-sar/products-algorithms/level-1-algorithms/ground-range-detected","title":"Sentinel-1 Ground Range Detected (GRD) Technical Guide"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_GRD/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_GRD_COVERAGE","stac_extensions":["https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/eo/v1.1.0/schema.json"],"stac_version":"1.0.0","title":"Sentinel-1 Coverage Maps","description":"Global archive of Sentinel-1 Coverage-Maps processed at EODC.","keywords":[],"license":"proprietary","providers":[{"url":"https://eodc.eu/","name":"EODC","roles":["processor","licensor","host"]}],"summaries":{"platform":["sentinel-1a","sentinel-1b"],"constellation":["sentinel-1"]},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2014-10-03T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GRD_COVERAGE"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_GRD_COVERAGE/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_GRD_COVERAGE/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_HPAR","stac_extensions":["https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.0.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL1 Harmonic Parameters","description":"The Harmonic model describes the typical seasonal Sentinel-1 backscatter variation on a 20 m pixel level. It was designed as a smoothed time-series approximation, removing short-term perturbations, such as speckle and transient events (like floods for instance). Hence, the model is suited to discern the seasonal changes brought about by varying water content, e.g., inundation or soil moisture, and progression of vegetation structure.\nThe complete Sentinel-1 time-series dataset is challenging to analyse, primarily due to its sheer data volume of at the (global) scale of Petabytes. As a user-friendly alternative, this dataset provides a Harmonic (Fourier) series model that reduces the SAR backscatter seasonality to a relative small number of harmonic coefficient values. Seven coefficients computed using (harmonic) least squares regression, along with the standard deviation of residuals and number of observations, comprise the harmonic parametner set. The parameters are being operationally used to determine the expected SAR backscatter signal for any day of the year as part of the TU Wien's method contributing to GFM's ensemble flood monitoring effort (Bauer-Marschallinger et. al, 2022 https://www.mdpi.com/2072-4292/14/15/3673). The Global Harmonic Parameters (HPARs) were derived from the whole Sentinel-1 VV temporal stack for the period 2019-2020 by least squares regression with a harmonic model formulation, running three sinusoidal iterations (k=3).\nThis dataset was generated by the Remote Sensing Group of the TU Wien Department of Geodesy and Geoinformation,  within Framework Contract (No. 939866-IPR-2020) as part of the provision of an automated, global, satellite-based flood monitoring product for the Copernicus Emergency Management Service (CEMS) managed by the European Commission. The Global Flood Monitoring (GFM) product is integrated within the user interface of the Global Flood Awareness System (GloFAS) of the CEMS. ","keywords":[],"license":"proprietary","providers":[{"url":"https://www.tuwien.at/mg/geo","name":"TU Wien","roles":["processor","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["processor","host"]}],"summaries":{"eo:bands":[{"name":"C1","description":"Cosine component coefficient of iteration 1"},{"name":"C2","description":"Cosine component coefficient of iteration 2"},{"name":"C3","description":"Cosine component coefficient of iteration 3"},{"name":"M0","description":"Effective mean of the time series stacks, also called the harmonic residual in other literature."},{"name":"S1","description":"Sine component coefficient of iteration 1"},{"name":"S2","description":"Sine component coefficient of iteration 2"},{"name":"S3","description":"Sine component coefficient of iteration 3"},{"name":"STD","description":"Standard deviation of residuals, a proxy for model goodness of fit."},{"name":"NOBS","description":"Number of valid observations used for the least squares regression, also an indicator of solution quality."}],"platform":["sentinel-1a","sentinel-1b"],"constellation":["s","e","n","t","i","n","e","l","-","1"]},"extent":{"spatial":{"bbox":[[-180,-90,180,90]]},"temporal":{"interval":[["2019-01-01T00:00:00Z","2021-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_HPAR"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_HPAR/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"license","href":"https://creativecommons.org/licenses/by/4.0/legalcode","type":"text/html","title":"TUWien Harmonic Parameter Data License"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_HPAR/queryables"}]},{"type":"Collection","id":"EODC|Sentinel-1_Lacken_Extent","stac_extensions":["https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL-1 Lacken Extent","description":"Sentinel-1 Wetland Data: Lacken Extent ","keywords":[],"license":"proprietary","providers":[{"url":"https://eodc.eu/","name":"EODC","roles":["host"]},{"url":"https://www.tuwien.at/mg/geo","name":"TU WIEN","roles":["processor","licensor"]}],"summaries":{"platform":["sentinel-1a"],"constellation":["sentinel-1"]},"extent":{"spatial":{"bbox":[[15.4557,47.0861,18.2263,48.155]]},"temporal":{"interval":[["2016-01-01T00:00:00Z","2021-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|Sentinel-1_Lacken_Extent"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|Sentinel-1_Lacken_Extent/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/Sentinel-1_Lacken_Extent/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_MPLIA","stac_extensions":["https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.0.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL1 Mean PLIA","description":"The projected local incidence angle (PLIA) is the angle between the surface normal and the looking direction of the satellite (local incidence angle - LIA) which is further projected into the range plane. It can be computed for each individual Sentinel-1 acquisition during the terrain correction using SNAP Sentinel-1 Toolbox. The PLIA for all Sentinel-1 GRDH scenes in the year 2020 have been proudced. Due to high accuracy and stability of Sentinel-1 orbit, the difference between PLIAs from different passes of the same relative orbit are neglectable, in particular for non-interferometry application. The PLIA are further aggregated to the mean PLIA per each relative orbit. \nThis colleciton includes global mean PLIA per relative orbit at 20 m sampling in Eqiu7 tiling system. The original data has been encoded by multiplying 100 and are stored in integer 16-bits data type in order to minimize file size.","keywords":[],"license":"proprietary","providers":[{"url":"https://www.tuwien.at/mg/geo","name":"TU Wien","roles":["processor","licensor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["processor","host"]}],"summaries":{"eo:bands":[{"name":"MPLIA","description":"The mean MPLIA of this orbit"},{"name":"NOBS","description":"Number of valid observations used Mean PLIA calculation."}],"platform":["sentinel-1a","sentinel-1b"],"constellation":["s","e","n","t","i","n","e","l","-","1"]},"extent":{"spatial":{"bbox":[[-180,-90,180,90]]},"temporal":{"interval":[["2020-01-01T00:00:00Z","2020-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_MPLIA"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_MPLIA/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_MPLIA/queryables"}]},{"type":"Collection","id":"EODC|Sentinel-1_Reed_Extent","stac_extensions":["https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL-1 Reed Extent","description":"Sentinel-1 Wetland Data: Reed Extent ","keywords":[],"license":"proprietary","providers":[{"url":"https://eodc.eu/","name":"EODC","roles":["host"]},{"url":"https://www.tuwien.at/mg/geo","name":"TU WIEN","roles":["processor","licensor"]}],"summaries":{"platform":["sentinel-1a"],"constellation":["sentinel-1"]},"extent":{"spatial":{"bbox":[[15.4557,47.0861,18.2263,48.155]]},"temporal":{"interval":[["2016-01-01T00:00:00Z","2021-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|Sentinel-1_Reed_Extent"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|Sentinel-1_Reed_Extent/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/Sentinel-1_Reed_Extent/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_SCENE_GMR0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/item-assets/v1.0.0/schema.json","https://stac-extensions.github.io/raster/v1.1.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.0.0/schema.json","https://stac-extensions.github.io/raster/v1.1.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL1 Scene-based Radiometric Terrain Corrected Gamma Nought","description":"Sentinel-1 Gamma Nought (GMR0) Product is radiometric terrain calibrated (RTC) and georeferenced backscatter data generated from Sentinel-1 level-1 Interferometric Wide (IW) Swath Ground Range Detected (GRD) High resolution products using wizsard software. The preprocessing workflow includes following steps: applying precise orbit file, thermal noise removal, radiometric calibration, radiometric terrain correction, and geometric terrain correction. In the end, Gamma Nought backscatter are reprojected into Equi7 Projection at 10m pixels spacing.","keywords":["Sentinel-1","Backscatter","Gamma0","Radiometric Terrain Corrected","RTC","wizsard","Scene-based"],"license":"proprietary","providers":[{"url":"https://www.tuwien.at/mg/geo","name":"TU Wien","roles":["processor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["processor","host"]}],"summaries":{"eo:bands":[{"name":"VV","common_name":"Gamma0_VV","description":"Gamma0 Nought in VV polarization","center_wavelength":55465.76},{"name":"VH","common_name":"Gamma0_VH","description":"Gamma0 Nought in VH polarization","center_wavelength":55465.76},{"name":"HH","common_name":"Gamma0_HH","description":"Gamma0 Nought in HH polarization","center_wavelength":55465.76},{"name":"HV","common_name":"Gamma0_HV","description":"Gamma0 Nought in HV polarization","center_wavelength":55465.76},{"name":"LIA","common_name":"Local Incidence Angle","description":"Local incidence angle image for backscatter image"},{"name":"Mask","common_name":"Mask","description":"Mask image for backscatter image"}],"platform":["sentinel-1a","sentinel-1b","sentinel-1c"],"constellation":["sentinel-1"]},"extent":{"spatial":{"bbox":[[9,46,24,50]]},"temporal":{"interval":[["2014-10-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_SCENE_GMR0"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|SENTINEL1_SCENE_GMR0/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/SENTINEL1_SCENE_GMR0/queryables"}]},{"type":"Collection","id":"EODC|SENTINEL1_SIG0_20M","stac_extensions":["https://stac-extensions.github.io/sat/v1.0.0/schema.json","https://stac-extensions.github.io/sar/v1.0.0/schema.json","https://stac-extensions.github.io/eo/v1.0.0/schema.json","https://stac-extensions.github.io/projection/v1.1.0/schema.json","https://stac-extensions.github.io/datacube/v2.2.0/schema.json"],"stac_version":"1.0.0","title":"SENTINEL1 Sigma Nought (SIG0) Backscatter in 20 meter resolution","description":"Sentinel-1 Sigma Nought (SIG0) Products are radiometric calibrated and georeferenced backscatter data generated from Sentinel-1 level-1 Interferometric Wide (IW) Swath Ground Range Detected (GRD) High resolution products using TUWien Sentinel-1 preprocesssing workflow. 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The data is designed to be modified and adapted by users interested in thematic areas such as:\n - spatial planning\n - agro-environmental monitoring\n - water monitoring\n - forest and vegetation monitoring\n - land carbon,\n - natural resource monitoring\n - global crop monitoring.\n\n[https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/overview](https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/overview)\n\nThe Level-1C product is composed of 100x100 km2 tiles (ortho-images in UTM/WGS84 projection). The Level-1C product results from using a Digital Elevation Model (DEM) to project the image in cartographic geometry. Per-pixel radiometric measurements are provided in Top Of Atmosphere (TOA) reflectances along with the parameters to transform them into radiances. Level-1C products are resampled with a constant Ground Sampling Distance (GSD) of 10, 20 and 60 m depending on the native resolution of the different spectral bands. 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The mission definition is driven by the need for continuity in provision of ERS, ENVISAT and SPOT vegetation data, with improvements in instrument performance and coverage.\n\nThe Sentinel-3 mission is jointly operated by ESA and EUMETSAT to deliver operational ocean and land observation services.\n\nThe spacecraft carries four main instruments:\n\n    OLCI: Ocean and Land Colour Instrument\n    SLSTR: Sea and Land Surface Temperature Instrument\n    SRAL: SAR Radar Altimeter\n    MWR: Microwave Radiometer.\n\nThese are complemented by three instruments for Precise Orbit Determination (POD):\n\n    DORIS: a Doppler Orbit Radio positioning system\n    GNSS: a GPS receiver, providing precise orbit determination and tracking multiple satellites simultaneously\n    LRR: to accurately locate the satellite in orbit using a Laser Retro-Reflector system.\n\n\n[https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-3/overview](https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-3/overview)\n\nThe main application of the Sentinel-3 topography mission is the study of ocean topography including mean sea level, wave height, wind speed over the surface, sea-ice, ocean currents, Kelvin and Rossby waves, eddies and tides.\n\nThe geophysical parameters to be measured by the Sentinel-3 topography mission are:\n    Surface Height (SSH)\n    Significant Wave Height (SWH)\n    Wind Speed over ocean surface.\n\nThe goal of the Sentinel-3 mission is to provide operational measurements for 20 years using robust and stable altimetry technology already proven in previous ESA missions. The minimum baseline altimeter performance required shall be the same as Envisat and CRYOSAT altimeters.\n\nThe Sentinel-3 orbit (altitude, inclination and coverage) is almost the same as Envisat, allowing continuation of the ERS/Envisat time series.\n\nIn the Sentinel-3 SRAL mission, there are two main modes of operation:\n    High Resolution Mode commonly called Synthetic Aperture Radar (SAR) or delay Doppler altimetry (DDA)\n    Low Resolution Mode (LRM)\n\nThe default (or principal) mode for operation of SRAL is at High Resolution Mode, but LRM provides a backup and enables for consistency with earlier missions.\n\nLike many recent altimeters, Sentinel 3 operates at two frequencies (Ju and C band) in order to derive an ionospheric correction. 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The layer is an RGB-colour multi-temporal representation of vegetation, where each colour represents one of three different time periods. All available Sentinel-2 images for three years (one for each colour) went into the analysis. For each year the vegetation observation was quantified (percentage of all yearly observations) using a standardized and fully automated semantic enrichment of EO images (https://color33.io), which identifies vegetation automatically based on spectral signatures. The RGB colour model is an additive colour model used to visualise the three different grayscale layers for each time period. It displays the changes from and within the three periods on the map within one layer using the different colour combinations. The interpretation of the colours can be drawn from the colour cube. The RGB colour palette and colour cube for the interpretation indicates change (increase and decrease) as well as persistence (white and very bright colours) or absence of vegetation (black/very dark). Changes in vegetation intensity and/or partly changed vegetation can be identified by the colour intensity. Service requests for other spatiotemporal extents can be made through the contact on the INTERFACE Website This layer focuses on vegetation / non-vegetation changes based on Sentinel-2 big EO data, which means at least one image every 5 days, and in higher latitudes and overlapping orbits even more. A specific service for calculating layers for custom analysis periods (e.g. years or seasons) or areas is available on request through the contact on the INTERFACE Website (https://interface.eodc.eu). Implementation by the Paris Lodron University Salzburg and Spatial Services GmbH","keywords":["sentinel","copernicus","esa","imagery","reflectance"],"license":"ODC-By-1.0","providers":[{"url":"https://www.plus.ac.at/","name":"Paris Lodron University Salzburg","roles":["producer","licensor"]},{"url":"https://www.spatial-services.com/","name":"Spatial Services GmbH","roles":["producer","processor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host"]}],"summaries":{"providers":[{"url":"https://www.plus.ac.at/","name":"Paris Lodron University Salzburg","roles":["producer","licensor"]},{"url":"https://www.spatial-services.com/","name":"Spatial Services GmbH","roles":["producer","processor"]},{"url":"https://eodc.eu/","name":"EODC","roles":["host"]}],"published":{"maximum":"None","minimum":"2024-08-27T07:31:14Z"}},"extent":{"spatial":{"bbox":[[15.953984827833802,46.77108096987509,17.176816759840396,48.1760048418813]]},"temporal":{"interval":[["2018-01-01T00:00:00Z","2022-12-31T00:00:00Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|VEGETATION_CHANGE_AUSTRIA"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/EODC|VEGETATION_CHANGE_AUSTRIA/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.eodc.eu/api/v1/collections/VEGETATION_CHANGE_AUSTRIA/queryables"}]},{"type":"Collection","id":"CREODIAS|SUOMI-NPP","stac_extensions":[],"stac_version":"1.0.0","title":"SUOMI-NPP","description":"A satellite to study long-term climate change and short-term weather conditions, Suomi NPP continues the work of NASA's Earth Observing System fleet of satellites, examining the dynamics of clouds, oceans, vegetation, ice, solid Earth, and atmosphere.The craft was named in memory of Verner E. Suomi of the University of Wisconsin, recognized widely as “the father of satellite meteorology.” [https://science.nasa.gov/mission/suomi-npp/]","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2011-10-28T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SUOMI-NPP"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SUOMI-NPP/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SUOMI-NPP/queryables"}]},{"type":"Collection","id":"CREODIAS|LANDSAT-7","stac_extensions":[],"stac_version":"1.0.0","title":"LANDSAT-7","description":"Landsat-7 continues the goal of the Landsat programme to image repetitively Earth's land and coastal areas with the aim of monitoring changes to those areas over time. The satellite continues to provide data continuity for the Thematic Mapper aboard Landsat-4 and 5, utilising an enhanced version of the instrument. The Enhanced Thematic Mapper Plus (ETM+) is the main instrument on board Landsat-7 and has been operational since 1999. It provides 30 m resolution for visible (VIS), near infrared (NIR) and shortwave infrared (SWIR) as well as 60 m resolution for thermal infrared. Moreover, it adds 15 m resolution panchromatic band (PAN).","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-19.0,36.0,51.0,72.0]]},"temporal":{"interval":[["1999-06-30T10:14:58Z","2023-11-02T07:08:42Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-7"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-7/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/LANDSAT-7/queryables"}]},{"type":"Collection","id":"CREODIAS|AQUA","stac_extensions":[],"stac_version":"1.0.0","title":"AQUA","description":"Aqua is a NASA-led international Earth science satellite launched on May 4, 2002. It carries six instruments that collect about 89 GB of daily data, mainly focused on water in all its forms—liquid, solid, and vapor—along with other variables like energy fluxes, aerosols, vegetation, ocean biology, and global temperatures.[https://eospso.nasa.gov/sites/default/files/mission_handbooks/Aqua.pdf]","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2002-05-04T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|AQUA"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|AQUA/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/AQUA/queryables"}]},{"type":"Collection","id":"CREODIAS|COP-DEM","stac_extensions":[],"stac_version":"1.0.0","title":"COP-DEM","description":"The Copernicus DEM is a Digital Surface Model (DSM) that represents the surface of the Earth including buildings, infrastructure and vegetation. Data were acquired through the TanDEM-X mission between 2011 and 2015 [https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2010-12-12T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|COP-DEM"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|COP-DEM/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/COP-DEM/queryables"}]},{"type":"Collection","id":"CREODIAS|LANDSAT-5","stac_extensions":[],"stac_version":"1.0.0","title":"LANDSAT-5","description":"Landsat-5 was launched on 1 March 1984 and the mission ended on 5 June 2013. It launched the Thematic Mapper (TM) which was a multispectral scanning radiometer operating in the visible and Infra-Red regions of the Electromagnetic Spectrum. It was characterized by 185 km swath width and 30 m resolution for visible (VIS), near infrared (NIR) and shortwave infrared (SWIR) while 120 m resolution for thermal infrared. The acquired Landsat TM scene covers approximately 183 x 172.8 km. The objective of Landsat-5 and any other Landsat mission was to image repetitively Earth's land and coastal areas with the aim of monitoring changes to those areas over time.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-19.0,36.0,51.0,72.0]]},"temporal":{"interval":[["1984-03-19T10:05:55Z","2011-11-16T23:59:59Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-5"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-5/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/LANDSAT-5/queryables"}]},{"type":"Collection","id":"CREODIAS|TERRAAQUA","stac_extensions":[],"stac_version":"1.0.0","title":"TERRAAQUA","description":"Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands. MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra and Aqua satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon [https://modis.gsfc.nasa.gov/about/].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2000-02-16T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|TERRAAQUA"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|TERRAAQUA/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/TERRAAQUA/queryables"}]},{"type":"Collection","id":"CREODIAS|LANDSAT-9","stac_extensions":[],"stac_version":"1.0.0","title":"LANDSAT-9","description":"The Landsat 9 (L9) mission is a joint mission formulated, implemented, and operated bythe National Aeronautics and Space Administration (NASA) and the Department of theInterior (DOI) U.S. Geological Survey (USGS). L9 is a remote-sensing satellite missionproviding coverage of the Earth’s land surfaces. This mission ushers in 50 years ofglobal data collection and distribution provided by the Landsat series of satellites.Landsat images provide information that meets the broad and diverse needs ofbusiness, science, education, government, and national security. Landsat 9, launched September 27, 2021, carries nearly identical sensors as L8 — the OLI-2, and the TIRS-2. The OLI-2 data has 14-bit quantization, and improvements to the TIRS-2 increases the quality of split-window thermal data usability.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2021-10-31T01:40:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-9"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-9/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/LANDSAT-9/queryables"}]},{"type":"Collection","id":"CREODIAS|S2GLC","stac_extensions":[],"stac_version":"1.0.0","title":"S2GLC","description":"The S2GLC 2017 product represents land cover classification of a major portion of the European continent. The classification has been performed using multi-temporal Sentinel-2 data collected during the year 2017 with the methodology developed in the frame of the Sentinel-2 Global Land Cover (S2GLC) project. The Sentinel-2 Global Land Cover (S2GLC) project was founded by the European Space Agency (ESA) through its Scientific Exploitation of Operational Missions (SEOM) element [https://s2glc.cbk.waw.pl/].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-19.0,36.0,51.0,72.0]]},"temporal":{"interval":[["2017-01-01T00:00:00Z","2017-12-30T23:59:59Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|S2GLC"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|S2GLC/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/S2GLC/queryables"}]},{"type":"Collection","id":"CREODIAS|CSS","stac_extensions":[],"stac_version":"1.0.0","title":"CSS","description":"The Civil Security from Space collection delivers geospatial products supporting civil protection and emergency response by integrating Earth Observation (EO) data with high-resolution UAV imagery processed in a secure cloud environment. The collection currently focuses on UAV-derived orthophotos and their Cloud Optimized GeoTIFFs (COGs), enabling efficient access, visualization, and near–real-time situational awareness for civil services during crisis events. By consolidating satellite and drone data and evolving towards AI-driven analysis and interoperability with commercial data services, the collection supports rapid crisis response, improved data-driven decision-making, and enhanced monitoring capabilities across European civil security operations.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2020-01-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CSS"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CSS/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/CSS/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-1","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-1","description":"The Sentinel-1 mission is the European Radar Observatory for the Copernicus joint initiative of the European Commission (EC) and the European Space Agency (ESA). The Sentinel-1 mission includes C-band imaging operating in four exclusive imaging modes with different resolution (down to 5 m) and coverage (up to 400 km). It provides dual polarization capability, short revisit times and rapid product delivery. Additionally, precise measurements of spacecraft position and attitude are available for every observation [https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-1].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2014-10-01T02:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-1"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-1/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-1/queryables"}]},{"type":"Collection","id":"CREODIAS|GLOBAL-MOSAICS","stac_extensions":[],"stac_version":"1.0.0","title":"GLOBAL-MOSAICS","description":"This STAC Collection is part of the data federation and its description was auto-generated by the EO-MQS.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2020-01-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|GLOBAL-MOSAICS"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|GLOBAL-MOSAICS/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/GLOBAL-MOSAICS/queryables"}]},{"type":"Collection","id":"CREODIAS|LANDSAT-8","stac_extensions":[],"stac_version":"1.0.0","title":"LANDSAT-8","description":"Launched in 2013, the Landsat 8 satellite has contributed to an uninterrupted multispectral record of the Earth’s land surfaces since 1972. Landsat 8 orbits in an eight-day offset with Landsat 7, which was launched in 1999. The L8 mission objective is to provide timely, high-quality visible and infrared images of all landmass and near-coastal areas on the Earth, continually refreshing an existing Landsat database. Data input into the system are sufficiently consistent with currently archived data in terms of acquisition geometry, calibration, coverage, and spectral characteristics to allow for comparison of global and regional change detection and characterization.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2013-03-18T15:58:14Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-8"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|LANDSAT-8/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/LANDSAT-8/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-3","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-3","description":"Sentinel-3 is a constellation of two radar imaging satellites developed to support Copernicus ocean, land, atmospheric, emergency, security and cryospheric applications. Both S3A, launched in February 2016, and S3B, launched in April 2018, are part of the Copernicus Programme- the European Union’s Earth observation program, managed by the European Commission (COM) [https://www.eoportal.org/satellite-missions/copernicus-sentinel-3]. The spacecraft carries four main instruments: OLCI (Ocean and Land Colour Instrument), SLSTR (Sea and Land Surface Temperature Instrument), SRAL (SAR Radar Altimeter) and MWR (Microwave Radiometer). The SENTINEL-3 mission is jointly operated by the European Space Agency (ESA) and supported by EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) [https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-3].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2016-03-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-3"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-3/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-3/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-6","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-6","description":"The Sentinel-6 mission represents a groundbreaking advancement in Earth observation, providing invaluable insights for scientists, environmentalists, and stakeholders worldwide. At the heart of this mission is the cutting-edge radar altimeter instrument, designed to measure sea surface height and monitor key oceanographic parameters with unparalleled accuracy. The Sentinel-6 satellite collects precise data by employing advanced radar technology, allowing for a comprehensive understanding of sea level variations, ocean currents, and climate patterns [https://creodias.eu/eodata/sentinel-6/].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2021-10-09T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-6"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-6/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-6/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-5P","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-5P","description":"The Copernicus Sentinel-5 Precursor mission dedicated to monitoring our atmosphere, consists of one satellite carrying the TROPOspheric Monitoring Instrument (TROPOMI) instrument. It aims to fill in global atmospheric data gap between the retired ENVISAT and AURA missions and the upcoming Sentinel-5 mission. The primary goal of TROPOMI is to provide daily global observations of key atmospheric constituents related to monitoring and forecasting air quality, the ozone layer, and climate change [https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-5p].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2018-04-30T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-5P"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-5P/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-5P/queryables"}]},{"type":"Collection","id":"CREODIAS|SMOS","stac_extensions":[],"stac_version":"1.0.0","title":"SMOS","description":"The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2 November 2009. It is one of the European Space Agency's Earth Explorer missions, which form the science and research element of the Living Planet Programme. The payload of SMOS consists of the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument, a passive microwave 2-D interferometric radiometer, operating in L-band (1.413 GHz, 21 cm) within a protected wavelength/frequency band [https://creodias.eu/eodata/smos/].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2010-01-13T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SMOS"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SMOS/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SMOS/queryables"}]},{"type":"Collection","id":"CREODIAS|CCM","stac_extensions":[],"stac_version":"1.0.0","title":"CCM","description":"Copernicus Complementary Missions Datasets CCM Core datasets. More information can be found via https://dataspace.copernicus.eu/explore-data/data-collections/copernicus-contributing-missions/ccm-collections-description.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2003-01-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CCM"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CCM/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/CCM/queryables"}]},{"type":"Collection","id":"CREODIAS|ENVISAT","stac_extensions":[],"stac_version":"1.0.0","title":"ENVISAT","description":"Envisat was ESA's successor to ERS. Launched on 1 March 2002 on an Ariane-5 rocket from Europe's spaceport in French Guiana, Envisat was the largest Earth observation spacecraft ever built with 10 instruments aboard and at eight tonnes was the largest civilian Earth observation mission ever launched. More advanced imaging radar, radar altimeter and temperature-measuring radiometer instruments extended ERS data sets. This was supplemented by new instruments including a medium-resolution spectrometer sensitive to both land features and ocean colour. Envisat also carried two atmospheric sensors monitoring trace gases. The Envisat mission ended on 8 April 2012, following the unexpected loss of contact with the satellite [https://earth.esa.int/eogateway/missions/Envisat].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2002-05-17T00:00:00Z","2012-04-08T23:59:59Z"]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|ENVISAT"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|ENVISAT/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/ENVISAT/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-1-RTC","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-1-RTC","description":"Sentinel-1 Radiometric Terrain Corrected (RTC) SAR Backscatter is a product processed from Sentinel-1 ground range detected (GRD) and is compliant with CEOS Analysis Ready Data for Land (CARD4L) specifications for Normalised Radar Backscatter (NRB) products [https://collections.eurodatacube.com/card4l/].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2018-01-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-1-RTC"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-1-RTC/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-1-RTC/queryables"}]},{"type":"Collection","id":"CREODIAS|SENTINEL-2","stac_extensions":[],"stac_version":"1.0.0","title":"SENTINEL-2","description":"The Copernicus Sentinel-2 mission consists of two polar-orbiting satellites that are positioned in the same sun-synchronous orbit, with a phase difference of 180°. It aims to monitor changes in land surface conditions. The satellites have a wide swath width (290 km) and a high revisit time. Sentinel-2 is equipped with an optical instrument payload that samples 13 spectral bands: four bands at 10 m, six bands at 20 m and three bands at 60 m spatial resolution [https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-2].","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["2015-07-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-2"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|SENTINEL-2/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/SENTINEL-2/queryables"}]},{"type":"Collection","id":"CREODIAS|CLMS","stac_extensions":[],"stac_version":"1.0.0","title":"CLMS","description":"Copernicus program priorities are to gain from Earth Observation techniques and make research, administration, agriculture, economy, environmental protection of our lands easier, cheaper and more effective. Copernicus Land Monitoring Service (CLMS) constitute rich data hub with archival and near real time environmental resources. Copernicus Data Space Ecosystem platform makes CLMS products accessible over S3 or NFS protocol . Each User can make his own contribution to expanding data land applications using Copernius Data Space Ecosystem resources.\nCLMS provides three kinds of data related to its coverage: Global, Pan-European and Local. It also provides imagery and reference data (IAR).","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["1990-01-01T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CLMS"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|CLMS/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/CLMS/queryables"}]},{"type":"Collection","id":"CREODIAS|TERRA","stac_extensions":[],"stac_version":"1.0.0","title":"TERRA","description":"The Terra (formerly called EOS AM-1) satellite is the flagship of NASA’s Earth Science Missions. Terra is the first EOS (Earth Observing System) platform and provides global data on the state of the atmosphere, land, and oceans, as well as their interactions with solar radiation and with one another.","keywords":[],"license":"proprietary","providers":[],"summaries":{},"extent":{"spatial":{"bbox":[[-180.0,-90.0,180.0,90.0]]},"temporal":{"interval":[["1999-12-18T00:00:00Z",null]]}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|TERRA"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CREODIAS|TERRA/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"queryables","type":"application/json","href":"https://datahub.creodias.eu/stac/collections/TERRA/queryables"}]},{"type":"Collection","id":"CollGS_CZ|sentinel-2-l2a-experimental","stac_extensions":[],"stac_version":"1.0.0","title":null,"description":"MSI L2a. Bottom of Atmosphere Reflectances in Cartographic Geometry.","keywords":[],"license":"proprietary","providers":[],"summaries":{"collection":{"const":"sentinel-2-l2a-experimental","count":1000,"type":"string"}},"extent":{"spatial":{"bbox":[[10.382684,47.690851,21.13777,51.451182]],"crs":"http://www.opengis.net/def/crs/OGC/1.3/CRS84"},"temporal":{"interval":[["2015-07-04T00:00:00.000000Z","2025-04-29T10:00:51.025000Z"]],"trs":"http://www.opengis.net/def/uom/ISO-8601/0/Gregorian"}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|sentinel-2-l2a-experimental"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|sentinel-2-l2a-experimental/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.cesnet.cz/collections/sentinel-2-l2a-experimental/queryables"}]},{"type":"Collection","id":"CollGS_CZ|e-obs","stac_extensions":[],"stac_version":"1.0.0","title":"E-OBS","description":"E-OBS is a daily gridded land-only observational dataset over Europe. The blended time series from the station network of the European Climate Assessment & Dataset (ECA&D) project form the basis for the E-OBS gridded dataset. All station data are sourced directly from the European National Meteorological and Hydrological Services (NMHSs) or other data holding institutions. For a considerable number of countries the number of stations used is the complete national network and therefore much more dense than the station network that is routinely shared among NMHSs (which is the basis of other gridded datasets). The density of stations gradually increases through collaborations with NMHSs within European research contracts. \nInitially, in 2008, this gridded dataset was developed to provide validation for the suite of Europe-wide climate model simulations produced as part of the European Union ENSEMBLES project. While E-OBS remains an important dataset for model validation, it is also used more generally for monitoring the climate across Europe, particularly with regard to the assessment of the magnitude and frequency of daily extremes. \nThe position of E-OBS is unique in Europe because of the relatively high spatial horizontal grid spacing, the daily resolution of the dataset, the provision of multiple variables and the length of the dataset. Finally, the station data on which E-OBS is based are available through the ECA&D webpages (where the owner of the data has given permission to do so). In these respects it contrasts with other datasets. \nThe dataset is daily, meaning the observations cover 24 hours per time step. The exact 24-hour period can be different per region. The reason for this is that some data providers measure between midnight to midnight while others might measure from morning to morning. Since E-OBS is an observational dataset, no attempts have been made to adjust time series for this 24-hour offset. It is made sure, where known, that the largest part of the measured 24-hour period corresponds to the day attached to the time step in E-OBS (and ECA&D).","keywords":["era5","reanalysis-era5-land","ecmwf","cds"],"license":"proprietary","providers":[{"url":"https://cds.climate.copernicus.eu/#!/home","name":"European Union/Copernicus/ECMWF","roles":["producer","licensor"]}],"summaries":{"collection":{"const":"e-obs","count":4,"type":"string"}},"extent":{"spatial":{"bbox":[[-40,25,75,75]],"crs":"http://www.opengis.net/def/crs/OGC/1.3/CRS84"},"temporal":{"interval":[["1950-01-01T00:00:00.000000Z","2025-03-25T23:59:59.999999Z"]],"trs":"http://www.opengis.net/def/uom/ISO-8601/0/Gregorian"}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|e-obs"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|e-obs/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.cesnet.cz/collections/e-obs/queryables"},{"href":"https://object-store.os-api.cci2.ecmwf.int/cci2-prod-catalogue/licences/licence-to-use-E-OBS-products/licence-to-use-E-OBS-products_22c02baab8ecc1c91abb598affb74f18bc69724559cfbe20b4e9155774c12d78.pdf","rel":"license","title":"Data Policy for E-OBS"},{"href":"https://cds.climate.copernicus.eu/datasets/insitu-gridded-observations-europe","rel":"via"}]},{"type":"Collection","id":"CollGS_CZ|reanalysis-era5-pressure-levels","stac_extensions":[],"stac_version":"1.0.0","title":"ERA5 hourly data on pressure levels","description":"ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article (href=https://confluence.ecmwf.int/display/CKB/The+family+of+ERA5+datasets). Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). 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Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article (href=https://confluence.ecmwf.int/display/CKB/The+family+of+ERA5+datasets). Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is ERA5 hourly data on single levels from 1940 to present.","keywords":["era5","reanalysis-era5-single-levels","ecmwf","cds"],"license":"proprietary","providers":[{"url":"https://cds.climate.copernicus.eu/#!/home","name":"European Union/Copernicus/ECMWF","roles":["producer","licensor"]}],"summaries":{"collection":{"const":"reanalysis-era5-single-levels","count":9181,"type":"string"}},"extent":{"spatial":{"bbox":[[12.07,48.48,19,51.08]],"crs":"http://www.opengis.net/def/crs/OGC/1.3/CRS84"},"temporal":{"interval":[["1940-01-01T00:00:00.000000Z","2026-05-19T00:00:00.000000Z"]],"trs":"http://www.opengis.net/def/uom/ISO-8601/0/Gregorian"}},"links":[{"rel":"self","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|reanalysis-era5-single-levels"},{"rel":"parent","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"items","type":"application/geo+json","href":"https://mqs.eodc.eu/stac/v1/collections/CollGS_CZ|reanalysis-era5-single-levels/items"},{"rel":"root","type":"application/json","href":"https://mqs.eodc.eu/stac/v1/"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://stac.cesnet.cz/collections/reanalysis-era5-single-levels/queryables"},{"href":"https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf","rel":"license","title":"Licence to Use Copernicus Products"},{"href":"https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels","rel":"via"}]},{"type":"Collection","id":"CollGS_CZ|reanalysis-era5-land","stac_extensions":[],"stac_version":"1.0.0","title":"ERA5-Land hourly data","description":"ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. 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