Observation Instance – Django REST framework

Get a list of Observation objects.

### Available end points:

- `/observations/` - Will list all Results in the database
- `/observations.json` - Will return all Results in json format. This can
also be achieved by using the accept header. `application/json`
- `/observations/<object_id>/` - Returns Results object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `title`
- `uuid`
- `keywords`
- `status`
- `result_field`
- `discoveryKeywords`
- `updateFrequency`
- `nonGeographicFlag`
- `publicationState`
- `permissions`

### How to use filters:

These filters can be used like django query filters using __ for related model relationships.

- `/observations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/observations/?status=completed`
- `/observations/?results_field__dataPath__startswith=/neodc/esacci`
- `/observations/?discoveryKeywords__name=ESACCI`
- `/observations/?nonGeographicFlag=True`

Filters can be stacked to build an 'AND' relationship. E.g.

- `/observations/?publicationState__in=published,citable&nonGeographicFlag=True`
- `/observations/?publicationState__in=published,citable&discoveryKeyword__name=NDGO0003`

GET /api/v2/observations/45168/?format=api

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

{
    "ob_id": 45168,
    "uuid": "e3f42bece9364be3a5653f4c71f2905c",
    "title": "NCEO aboveground biomass maps of Africa for years 2007, 2008, 2009, 2010, 2015, 2016, and 2017 (v1.0)",
    "abstract": "This product contains maps of aboveground biomass (AGB) estimates and their uncertainty (AGB standard deviation) in the African continent at 100m spatial resolution for years 2007, 2008, 2009, 2010, 2015, 2016, 2017. The maps are in GeoTIFF format and the unit of pixel values is ton per hectare. \r\n\r\nAboveground biomass (AGB) was estimated using satellite-based canopy estimates and ground-based tree height and AGB data. Input data for modelling canopy height are HH and HV backscatter from ALOS PALSAR 1 and 2 and tree cover fraction from Landsat. Relative height 100% from spaceborne LiDAR GEDI was used for training. An empirical model, built with field and ALS data, was used for converting canopy height to aboveground biomass.\r\n\r\nDetails of the methods for data production are provided in the following paper, which is linked in the documentation section of this catalogue record: Rodríguez-Veiga, P., Carreiras, J.M.B., Quegan, S. et al. Loss of tropical moist broadleaf forest has turned Africa’s forests from a carbon sink into a source. Sci Rep 15, 41744 (2025).",
    "keywords": "Forests, Biomass, Carbon, Africa, Climate",
    "publicationState": "preview",
    "dataPublishedTime": null,
    "doiPublishedTime": null,
    "updateFrequency": "notPlanned",
    "status": "pending",
    "result_field": {
        "ob_id": "https://catalogue.ceda.ac.uk/api/v2/observations/46077/?format=api",
        "dataPath": "/neodc/nceo_biomass_maps/data/african_maps/v1.0/",
        "oldDataPath": [],
        "storageLocation": "internal",
        "storageStatus": "online",
        "volume": 19659722378,
        "numberOfFiles": 15,
        "fileFormat": "The maps are in GeoTIFF format and the unit of pixel values is ton per hectare."
    },
    "timePeriod": "https://catalogue.ceda.ac.uk/api/v2/times/12844/?format=api",
    "geographicExtent": "https://catalogue.ceda.ac.uk/api/v2/bboxes/4956/?format=api",
    "nonGeographicFlag": false,
    "phenomena": [],
    "dataLineage": "The data was supplied by Nezha Acil of the NCEO University of Leicester research team to CEDA for archival.",
    "removedDataTime": null,
    "removedDataReason": "",
    "language": "English",
    "identifier_set": [],
    "projects": [
        "https://catalogue.ceda.ac.uk/api/v2/projects/45169/?format=api"
    ],
    "observationcollection_set": [
        "https://catalogue.ceda.ac.uk/api/v2/observationcollections/30127/?format=api"
    ],
    "responsiblepartyinfo_set": [
        "https://catalogue.ceda.ac.uk/api/v2/rpis/220148/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216136/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216137/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216138/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216139/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216140/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216144/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216135/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216145/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216146/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216147/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/216148/?format=api"
    ],
    "procedureAcquisition": null,
    "procedureCompositeProcess": "https://catalogue.ceda.ac.uk/api/v2/composites/46080/?format=api",
    "procedureComputation": null,
    "permissions": [
        {
            "ob_id": "https://catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api",
            "useLimitation": null,
            "accessConstraints": null,
            "accessCategory": "public",
            "accessRoles": null,
            "label": "public: None group",
            "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
            "licenceClassifications": "any, attribution required"
        }
    ],
    "discoveryKeywords": [
        {
            "ob_id": 1138,
            "name": "NDGO0003"
        }
    ]
}