Procedure Composite Process Instance – Django REST framework

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.

### Available end points:

- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

None
### How to use filters:

None

GET /api/v2/composites/44837/?format=api

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

{
    "ob_id": 44837,
    "computationComponent": [
        {
            "ob_id": 44836,
            "uuid": "0b9ad9b988ad419fb2fab93ebc4f38c6",
            "title": "ESA Snow Climate Change Initiative (snow_cci): SWE, v4",
            "abstract": "The snow_cci SWE product has been based on the ESA GlobSnow SWE retrieval approach (Takala et al. 2011). The retrieval is based on passive microwave radiometer (PMR) data considering the change of brightness temperature due to different snow depth, snow density, grain size and more. The retrieval algorithm handles data from the sensors SMMR, SSM/I, SSMIS, AMSR-E and AMSR-2. The retrieval methodology combines the satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme. The GlobSnow algorithm implemented for snow_cci version 4 includes the utilisation of an advanced emission model with an improved forest transmissivity module and treatment of sub-grid lake ice. Because of the importance of the weather station snow-depth observations on the SWE retrieval, there is improved screening for consistency through the time series. Passive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data/) The retrieval algorithm has been modified relative to snow_cci v3.1 to prioritize morning overpass (descending) data over evening (ascending) data. This change affects the SWE retrieval for all years except 1988–1991. Data from those years is from the F08 satellite, which has a reversed orbit, and evening (descending) data is prioritized, as in earlier versions of the SWE retrieval. Snow masking in post-production now uses CryoClim SCE data for 35–40° latitude and −30–3° longitude. Elsewhere, the baseline snow mask and CryoClim are combined so that any pixel flagged by either is marked snow-covered, as in v3.1. The pixel-wise uncertainty model has been updated for North America using extensive snow course data. The time series has been extended from version 3.1 by one year, to 2023. SWE products are based on SMMR, SSM/I and SSMIS passive microwave radiometer data for non-alpine regions of the Northern Hemisphere.",
            "keywords": "",
            "inputDescription": null,
            "outputDescription": null,
            "softwareReference": null,
            "identifier_set": []
        }
    ],
    "acquisitionComponent": [
        {
            "ob_id": 44838,
            "independentInstrument": [],
            "instrumentplatformpair_set": [
                {
                    "ob_id": 14362,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2629/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2630/?format=api",
                    "relatedTo": {
                        "ob_id": 44838,
                        "uuid": "c58d0219d8564f8db93a088001a47c8a",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 14363,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/458/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2636/?format=api",
                    "relatedTo": {
                        "ob_id": 44838,
                        "uuid": "c58d0219d8564f8db93a088001a47c8a",
                        "short_code": "acq"
                    }
                },
                {
                    "ob_id": 14364,
                    "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2629/?format=api",
                    "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14771/?format=api",
                    "relatedTo": {
                        "ob_id": 44838,
                        "uuid": "c58d0219d8564f8db93a088001a47c8a",
                        "short_code": "acq"
                    }
                }
            ]
        }
    ],
    "identifier_set": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/214740/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/214741/?format=api"
    ]
}