Observation Instance
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/46227/?format=api
{ "ob_id": 46227, "uuid": "8f932c8964904e1ab07c1a5e2817fe12", "title": "SPLICE: Terrestrial Laser Scanning (TLS) for UK Alice Holt plot AH2", "abstract": "Terrestrial laser scanning was collected on the 18th July 2023 by Mat Disney and Meg Stretton using a Riegl VZ-400i for the SPLICE project. Scans were acquired using chain sampling at 34 locations along a 12.5 m Cartesian grid to ensure sufficient data overlap to produce a high-quality point cloud of this forest plot. Capturing a complete sample of the scene at each location requires two scans (an upright scan and a tilt scan), owing to a 100° field of view. Upright scans will be odd-numbered while tilt scans will be even-numbered. The angular resolution between sequentially fired pulses is 0.04°, resulting in approximately 22.4 million emitted pulses per scan (i.e., 5.42 billion per ha). Up to four targets can be resolved per pulse, with a nominal ranging accuracy of 5 mm. The laser itself is characterized by a beam divergence of 0.35 mrad, and the diameter of the beam at emission is 7 mm (e.g., the diameter of the beam at a range of 50 m, would be 21 mm). The pulse repetition rate is 300 kHz, therefore, each scan takes approximately 3 minutes to complete. To generate a plot-level point cloud, scans were coarse registered using GNSS enabled Auto-Registration 2 (AR2) with coarse registraion fine-tuned using Multi Station Adjustment 2 (MSA2) The Sensor's Orientation and Position (SOP) matrix for all scans was saved into the \"matrix\" project directory and the GNSS coordinates (geographical coordinate system: WGS84 Cartesian) for all scans saved as a .kmz file.", "keywords": "Alice Holt, Forest, TLS, Trees, Splice, biomass", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "updateFrequency": "", "status": "completed", "result_field": { "ob_id": "https://catalogue.ceda.ac.uk/api/v2/observations/46226/?format=api", "dataPath": "/neodc/tls/data/raw/uk/AH2/2023-07-18-AHL2.PROJ", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 206231500428, "numberOfFiles": 52270, "fileFormat": "The data is stiored as PLY files. PLY files (Polygon File Format or Stanford Triangle Format) store 3D data captured by terrestrial laser scanners (TLS), including point clouds and polygonal meshes.\r\n\r\nScan position .DAT file are text files containing data. CSV and text log files are alos within the dataset.\r\n\r\nMore information on the data structure and formats can be found in the SPLICE_example_TLS_data_directory_structure.pdf document archived with the data" }, "timePeriod": "https://catalogue.ceda.ac.uk/api/v2/times/13335/?format=api", "geographicExtent": "https://catalogue.ceda.ac.uk/api/v2/bboxes/5200/?format=api", "nonGeographicFlag": false, "phenomena": [], "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataTime": null, "removedDataReason": "", "language": "English", "identifier_set": [], "projects": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ "https://catalogue.ceda.ac.uk/api/v2/rpis/220705/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220706/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220707/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220708/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220709/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220710/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220711/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220718/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220712/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220713/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220714/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220715/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220716/?format=api", "https://catalogue.ceda.ac.uk/api/v2/rpis/220717/?format=api" ], "procedureAcquisition": null, "procedureCompositeProcess": null, "procedureComputation": null, "permissions": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ] }