Observation Instance

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 37676,
    "uuid": "0d88dc06fd514e8199cdd653f00a7be0",
    "title": "ACRUISE: deep-learning inferred shiptrack clouds from AQUA MODIS daylight satellite data for 2002-2021",
    "abstract": "Large dataset of emission induced \"shiptrack\" clouds, detected using deep-learning, from satellite based remote sensing data with global coverage, from 2002 to 2021 for the Atmospheric Composition and Radiative forcing changes due to UN International Ship Emissions regulations (ACRUISE) project. Shiptracks were inferred from every daylight granule captured by the MODerate Imaging Spectroradiometer (MODIS) instrument, onboard the NOAA-AQUA satellite from 2002-2021 inclusive and stored in a compressed netcdf file.  In addition, polygons corresponding to contours of level 0.5 and 0.8 from the inference images are provided as a light-weight alternative. These are stored in annual geopackages in the geographic projection.\r\n\r\nThe model is a standard neural-network based segmentation model with a UNet architecture, a resnet-152 backbone and sigmoid activation on the final layer that was pre-trained on the 2012 ImageNet Large Scale Visual Recognition Challenge 2012 (ILSVRC2012) ImageNet dataset. This model was trained to segment clouds formed by ship exhausts, known as shiptracks, from MODIS level 1b, day microphysics composite granules enhanced through histogram stretching.\r\n\r\nThe purpose of these data is to measure the effect that shipping fuel regulation has on climate change and to reduce the uncertainty in the relationship between aerosols and cloud formation and properties. This allows the determination of where tracks are more likely to form and the sensitivity of clouds to such perturbations.The data indicate a sharp reduction in tracks due to the more stringent ship emission regulations since 2020.\r\n\r\nA small minority of granules (<0.5%) are missing  due to a combination of missing or corrupt files and/or unexpected computational processing failures. These remained unresolved as they were judged insignificant compared to model uncertainties and and of negligible additional benefit to warrant the overheads to resolve each missing granule.",
    "keywords": "Ship tracks, MODIS",
    "publicationState": "citable",
    "dataPublishedTime": "2022-09-09T10:34:19",
    "doiPublishedTime": "2022-09-16T13:14:45",
    "updateFrequency": "notPlanned",
    "status": "completed",
    "result_field": {
        "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/37677/?format=api",
        "dataPath": "/badc/acruise/data/NERC_ACRUISE_MODIS_shiptracks",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 9771844028217,
        "numberOfFiles": 1132857,
        "fileFormat": "Data are NetCDF (.nc) formatted with additional geopackages files (.gpkg)"
    },
    "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/10398/?format=api",
    "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/3541/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/7026/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/7028/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/49998/?format=api"
    ],
    "dataLineage": "NASA supplied AQUA MODIS level 1a data, archived at Plymouth Marine Laboratory, was processed to level 1b using NASA SeaDAS modis_L1B.py script. Satpy was used to process level 1b data into ‘day microphysics’ composites from channels 1, 20 and 32 (corresponding to wavelengths of 645nm, 3.75µm and 12.5µm respectively). Histogram equalisation was then used to enhance the image prior to training and inference by the model.\r\n\r\nModel output was written to a variable, \"shiptracks\", within a netcdf file that inherits the coordinates and metadata from the original day micro-physics granule. Contours at 0.5 and 0.8 were computed and stored in annual .gpkg files in the geographic projection.\r\n\r\nFor archiving, lossy compression was applied to inference granules: Variable \"shiptracks\" from float32 to unint16, with appropriate scaling factor. Latitude and Longitude coordinates from float64 to float32. Contours files were not compressed.\r\n\r\nDuncan Watson-Paris (DWP), Matthew Christensen (MC) and Philip Stier (PS) designed the research, DWP carried it out. Angus Laurenson and Daniel Clewley supported analysis. MC and Ed Gryspeerdt provided label data.  Data were prepared by the project team and uploaded to CEDA for archival",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12197/?format=api"
    ],
    "projects": [
        "https://api.catalogue.ceda.ac.uk/api/v2/projects/27736/?format=api"
    ],
    "observationcollection_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179692/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179693/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179694/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179695/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179696/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179697/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179698/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179699/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179700/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179701/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179702/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179703/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/179704/?format=api"
    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/37680/?format=api",
    "procedureComputation": null,
    "permissions": [
        {
            "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2543/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "registered",
            "accessRoles": null,
            "label": "registered: None group",
            "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf",
            "licenceClassifications": "unstated"
        }
    ],
    "discoveryKeywords": []
}