Get a list of Project objects. Projects have a 1:1 mapping with Observations.

### Available end points:

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

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `uuid`
- `status`
- `title`
- `keywords`

### How to use filters:

- `/projects/?uuid=ab4ca8d019d148f78afba1cd20872bdd`

- `/projects/?title__icontains!=Project details`

- `/projects.json?status=ongoing`

GET /api/v2/projects/10763/?format=api
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 10763,
    "uuid": "547e5293aa1e0e5c583257005f1ed6c6",
    "title": "ARSF - Flight GB08/03: Peak District, Burbage Moor",
    "abstract": "ARSF project GB08/03: Spatial and temporal changes in fuel moisture content (FMC) in upland vegetation: A case study in the Peak District. Led by: Dr. Richard Armitage, Centre for Environmental Systems Research, School of Environment and Life Sciences, University of Salford, Salford, M5 4WT. Location: Peak District, SE of Manchester, UK.A\r\n\r\nFuel  moisture  content  (FMC) , a  key  variable  in  fire  risk  modelling, is controlled by the  interaction of plant physiology and soil moisture conditions. Remote sensing has been used for mapping the spatial and temporal dynamics of vegetation FMC, but virtually all of this work has focused on Mediterranean ecosystems. In England and Wales fire risk is assessed using the Meteorological Office Fire Severity Index which uses meteorological data  to determine  fuel moisture and  soil water balance and map  fire  risk  in 10x10km cells on a daily basis. The model  does not currently account for spatial variations in fuel type and has to be tuned locally to account  for variations  in vegetation cover. This proposal  for  the acquisition of ARSF data was to test whether the relationships between reflectance and FMC, determined  in previous studies, can be used to improve fire severity risk assessment for fire-prone upland vegetation in northern England.",
    "keywords": "",
    "status": "completed",
    "publicationState": "published",
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7142/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7143/?format=api"
    ],
    "observationCollection": [
        "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/8604/?format=api"
    ],
    "parentProject": null,
    "subProject": [],
    "responsiblepartyinfo_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/38831/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/144632/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145249/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145250/?format=api"
    ]
}