Procedure Composite Process List
Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations where used.
These may have a number of 2 or more components made up of combinations of Computation and Acquisition records.
The details of the underlying records have been serialised.
GET /api/v3/composites/?format=api&offset=700
{ "count": 708, "next": null, "previous": "https://catalogue.ceda.ac.uk/api/v3/composites/?format=api&limit=100&offset=600", "results": [ { "ob_id": 46327, "uuid": "59a231d640c44181bb224d48981731e8", "title": "Composite process for ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): daily L3 HCHO from OMI, version 2.0", "abstract": "Composite process for ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): daily L3 HCHO from OMI, version 2.0", "computationComponent": [ { "ob_id": 46328, "uuid": "9b7d492796334b9cba6f51d9d1623c3c", "short_code": "comp", "title": "Computation for ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): daily L3 HCHO from OMI, version 2.0", "abstract": "This dataset provides gridded HCHO tropospherical column densities of daily 0.25°x0.25° resolution grids from October 2004 to December 2024.\r\n\r\nThe L3 product is based on the Level 2 HCHO product created for the Precursors_cci project.\r\n\r\nCompared to the operational TROPOMI product, the air mass factors have been reprocessed using an update albedo climatology, and the CAMS Reanalysis Model for the a priori vertical profiles. The background correction and the quality values have also been updated." } ], "acquisitionComponent": [ { "ob_id": 46329, "uuid": "d0f248d4759440bca4d6886606be0983", "short_code": "acq", "title": "Acquisition for ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): daily L3 HCHO from OMI, version 2.0", "abstract": "Acquisition for ESA Precursors for Aerosols and Ozone Climate Change Initiative (Precursors_cci): daily L3 HCHO from OMI, version 2.0" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221332 ] }, { "ob_id": 46333, "uuid": "9d6a746edec743a395f77ca9ed7508ea", "title": "Composite process for: ESA SATACI Climate Change Initiative (SATACI_cci): CISAR combined hourly AOD/COD products from MSG / SEVIRI, version 1.0.0", "abstract": "The data have been derived using the Combined Inversion of Surface and Aerosols (CISAR) algorithm applied to observations from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) onboard the MSG1 and MSG4 satellites.", "computationComponent": [ { "ob_id": 46335, "uuid": "c58661a8eda64ed69188a1f51352f77e", "short_code": "comp", "title": "Derivation of the ESA SATACI Climate Change Initiative (SATACI_cci): CISAR combined hourly AOD/COD products from MSG / SEVIRI, version 1.0.0", "abstract": "The data have been derived using the Combined Inversion of Surface and Aerosols (CISAR) algorithm applied to observations from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) onboard the MSG1 and MSG4 satellites.\r\n\r\nFor further information please see the project documentation" } ], "acquisitionComponent": [ { "ob_id": 46334, "uuid": "552fcf7967524d46a5d9862b3b2d6f9e", "short_code": "acq", "title": "Acquisition for: ESA SATACI Climate Change Initiative (SATACI_cci): CISAR combined hourly AOD/COD products from MSG / SEVIRI, version 1.0.0", "abstract": "Data have been derived from observations from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) onboard the MSG1 and MSG4 satellites." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221341 ] }, { "ob_id": 46343, "uuid": "6255e61b45eb4d3099792c383fe23936", "title": "Composite process for the ESA Antarctic Ice Sheets CCI: Grounding line location for key glaciers, v3.1", "abstract": "-", "computationComponent": [ { "ob_id": 32677, "uuid": "c763ca9f2a874b8ca75d9576efe6673b", "short_code": "comp", "title": "Derivation of Grounding Line Location data from the ESA Antarctic Ice Sheet Climate Change Initiative project", "abstract": "For information on the derivation of the Grounding Line location dataset see the documentation in https://climate.esa.int/projects/ice-sheets-antarctic/key-documents/" } ], "acquisitionComponent": [ { "ob_id": 46340, "uuid": "6c02e2d9c2fc4c4b91fc18d340ba6599", "short_code": "acq", "title": "Acquisition for: ESA Antarctic Ice Sheets CCI ground line location for key glaciers v3.1", "abstract": "Data have been derived from satellite observations from the ERS-1/2, TerraSAR-X and Copernicus Sentinel-1 satellites, acquired between 1994 and 2026." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221399 ] }, { "ob_id": 46350, "uuid": "170503f50ef5466cb5460c341f84a75e", "title": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v5.2)", "abstract": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v5.2)", "computationComponent": [ { "ob_id": 46351, "uuid": "0ed19ce77d4146b08aa950fb8877f8f1", "short_code": "comp", "title": "Derivation of Gravimetric Mass Balance products from the Antarctic Ice Sheet CCI (v5.2)", "abstract": "TU Dresden has generated a Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended to December 2025 by means of GRACE-FO data starting from June 2018, thus including 240 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden.\r\n\r\nThe methodology is described in: Groh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736" } ], "acquisitionComponent": [ { "ob_id": 46352, "uuid": "cd05fd01dd5e425a80e2a91499ffc467", "short_code": "acq", "title": "Acquisition for ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance Product, v5.2", "abstract": "The Antarctic Ice Sheet Gravimetric Mass Balance (GMB) v5.2 product is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through December 2025." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221410 ] }, { "ob_id": 46354, "uuid": "df9bc44916f34ee1b504795e43f908fc", "title": "Composite process for Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI project", "abstract": "Composite process for Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic project", "computationComponent": [ { "ob_id": 46353, "uuid": "ef1232ad1cd14840ac787ef7a51bbcd8", "short_code": "comp", "title": "Derivation of Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI project", "abstract": "Surface elevation change products are derived from radar altimetry data acquired by ERS-1 (1991–1996), ERS-2 (1995–2003), ENVISAT (2002–2012), CryoSat-2 (2010–present), Sentinel-3A (2016–present), and Sentinel-3B (2018–present), and from laser altimetry data acquired by ICESat-2 (2018–present). Cross-calibration of radar altimetry missions was performed to produce consistent multi-mission records. Processing was carried out by CPOM. Products are provided on a 5 km south polar stereographic grid (EPSG:3031). Single-mission SEC products represent the full operational period of each mission. Multi-mission products combine all available radar altimetry missions." } ], "acquisitionComponent": [ { "ob_id": 46085, "uuid": "fd7062df62004998a4e1476834e6d2e9", "short_code": "acq", "title": "Acquisition for: Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI project", "abstract": "Acquisition for: Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI project" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221416, 221417 ] }, { "ob_id": 46379, "uuid": "c8178dfabaa94803b0dda3f04ae042c6", "title": "Composite process for: ESA SATACI Climate Change Initiative (SATACI_cci): ORAC/BUGSRad cloud, aerosol and flux products from MSG / SEVIRI, version 3.0.0", "abstract": "This dataset has been derived using the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm applied to observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the MSG4 satellite, as well as fluxes derived using the BUGSRad algorithm.", "computationComponent": [ { "ob_id": 46378, "uuid": "2537abe9508349b2b21397a46c2b449a", "short_code": "comp", "title": "Derivation of the ESA SATACI Climate Change Initiative (SATACI_cci): ORAC/BUGSRad cloud, aerosol and flux products from MSG / SEVIRI, version 3.0.0", "abstract": "This dataset has been derived using the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm applied to observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the MSG4 satellite, as well as fluxes derived using the BUGSRad algorithm.\r\n\r\nFor further information please see the project documentation" } ], "acquisitionComponent": [ { "ob_id": 46380, "uuid": "f46853ae42724c9b9bca77388c3c508f", "short_code": "acq", "title": "Acquisition for: ESA SATACI Climate Change Initiative (SATACI_cci): ORAC/BUGSRad cloud, aerosol and flux products from MSG / SEVIRI, version 3.0.0", "abstract": "Data have been derived from observations from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) onboard the MSG1 and MSG4 satellites." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221526 ] }, { "ob_id": 46386, "uuid": "0db40e6ef053438ba4bfd990af506d73", "title": "Composite process for ESA River Discharge Climate Change Initiative (RD_cci): Water Level product, v2.1", "abstract": "The data has been derived from nadir viewing satellite radar altimeter missions (ERS-2, Envisat, Saral, Topex-Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A/B and Sentinel 6).", "computationComponent": [ { "ob_id": 46385, "uuid": "d3a1711a7c5f410ea9a7e20180ff3330", "short_code": "comp", "title": "Derivation of the ESA Climate Change Initiative River Discharge Water Level product, v2.1", "abstract": "For information on the derivation of the Water Level dataset see the project documentation \r\n(https://climate.esa.int/projects/river-discharge)" } ], "acquisitionComponent": [ { "ob_id": 46384, "uuid": "5ee1c6a324ba4b4a872b00dc4a50b5af", "short_code": "acq", "title": "Acquisition Process for the ESA River Discharge Climate Change Initiative (RD_cci): Water Level product, v2.1", "abstract": "The water level product was derived from the following nadir-viewing satellite radar altimeter missions : ERS-2, Envisat, Saral, Topex-Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A/B, and Sentinel-6" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221549, 221550 ] }, { "ob_id": 46392, "uuid": "f94e106d9dd74d13874dd12e6241ac66", "title": "Composite process for Land-cover classifications and chainage-level vegetation metrics for islands of the middle Congo River derived from Sentinel-2 imagery for 2020, 2024 and 2025", "abstract": "Land-cover mapping was performed in Google Earth Engine using ee.Classifier.smileRandomForest (500 trees) was trained on manually digitised polygons sampling four classes (vegetated, non-vegetated, water, sand) from Sentinel-2 L2A Surface Reflectance Harmonized median composites of June-August each target year. Cloud and shadow masking used the Scene Classification Layer with a 1-2 pixel buffer. Classification used bands B2, B3, B4, B8 and B11 with a 70/30 train-test split, validated using overall accuracy, Cohen's Kappa, Producer's Accuracy and User's Accuracy (Congalton, 1991). A majority filter was applied to reduce salt-and-pepper noise. Chainage-level metrics were generated in ArcGIS Pro using the Tabulate Area tool, with 10 km chainage polygons as zone features and the classified rasters / canopy-height raster as class rasters. The CHIRPS June-August 2024 cumulative rainfall raster was aggregated using Zonal Statistics (mean) over the same chainage polygons.", "computationComponent": [ { "ob_id": 46391, "uuid": "e7fe7bd4a7ca48debe132a2eca2c8b91", "short_code": "comp", "title": "Sentinel-2 dry-season compositing and Random Forest land-cover classification in Google Earth Engine, with chainage-level summary statistics generated in ArcGIS Pro using the Tabulate Area tool.", "abstract": "Land-cover mapping was performed in Google Earth Engine using ee.Classifier.smileRandomForest (500 trees) was trained on manually digitised polygons sampling four classes (vegetated, non-vegetated, water, sand) from Sentinel-2 L2A Surface Reflectance Harmonized median composites of June-August each target year. Cloud and shadow masking used the Scene Classification Layer with a 1-2 pixel buffer. Classification used bands B2, B3, B4, B8 and B11 with a 70/30 train-test split, validated using overall accuracy, Cohen's Kappa, Producer's Accuracy and User's Accuracy (Congalton, 1991). A majority filter was applied to reduce salt-and-pepper noise. Chainage-level metrics were generated in ArcGIS Pro using the Tabulate Area tool, with 10 km chainage polygons as zone features and the classified rasters / canopy-height raster as class rasters. The CHIRPS June-August 2024 cumulative rainfall raster was aggregated using Zonal Statistics (mean) over the same chainage polygons." } ], "acquisitionComponent": [ { "ob_id": 43427, "uuid": "636c6974c4034d0ca3bbe6661ac03128", "short_code": "acq", "title": "Acquisition Process for: Sentinel 2C Multispectral Instrument (MSI)", "abstract": "The acquisition process for the collection of raw imaging data from the European Space Agency (ESA) Sentinel 2C Multispectral Instrument (MSI)." }, { "ob_id": 25439, "uuid": "18f84df32d934058862f2c3990885a4c", "short_code": "acq", "title": "Acquisition Process for: Sentinel 2B Multispectral Instrument (MSI)", "abstract": "The acquisition process for the collection of raw imaging data from the European Space Agency (ESA) Sentinel 2B Multispectral Instrument (MSI)." }, { "ob_id": 13191, "uuid": "e05a470bb02a4bf5bba845b1fcc3aca6", "short_code": "acq", "title": "Acquisition Process for: Sentinel 2A Multispectral Instrument (MSI)", "abstract": "The acquisition process for the collection of raw imaging data from the European Space Agency (ESA) Sentinel 2A Multispectral Instrument (MSI)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 221587, 221588 ] } ] }