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Point

The stac_generator uses the csv and txt extensions to describe point data. In addition to the minimum required fields, the STAC generator requires a few additional parameters to properly parse the asset.

Given the flexibility of the csv format, we require point dataset to be structured in a particular way. Each row of the csv file describes a point, with columns being the attributes. At the minimum, there must be two columns describing the coordinates of the points, with the common options being lat/lon, y/x, northings/eastings, etc. The required config fields include:

  • X: the column in the csv asset to describe the longitude.
  • Y: the column in the csv asset to describe the latitude.
  • epsg: the crs of the X, Y columns.

There can also be optional columns:

  • T: the column in the csv asset that describes the date of collection of a point record.
  • date_format: how the date string is interpreted - by default, dates are assumed to be ISO8640 compliant.
  • Z: the column in the csv asset that describes the altitude.
  • column_info: describe the relevant names and descriptions of relavant attributes.

Generic Point Data

In this tutorial, we will describe the asset soil_data.csv contained in the zip folder.

Longitude Latitude mid_depth Ca_Soln
150.547 -24.3399 0.05 85.25
150.547 -24.3399 0.2 361.1
150.547 -24.3399 0.4 295.8
150.551 -24.3403 0.05 230.2
150.551 -24.3403 0.2 222.85
150.551 -24.3403 0.4 157.5
150.555 -24.3409 0.05 42.58
150.555 -24.3409 0.2 34.97
150.555 -24.3409 0.4 47.815
150.551 -24.3395 0.05 222.35
150.551 -24.3395 0.2 214.85
150.551 -24.3395 0.4 158.15
150.549 -24.3383 0.05 78.4
150.549 -24.3383 0.2 196.05
150.549 -24.3383 0.4 249.25
150.552 -24.3388 0.05 191.15
150.552 -24.3388 0.2 203.4
150.552 -24.3388 0.4 156.75
150.554 -24.339 0.05 53.05
150.554 -24.339 0.2 36.675
150.554 -24.339 0.4 62.1
150.553 -24.3376 0.05 88.55
150.553 -24.3376 0.2 69.65
150.553 -24.3376 0.4 29.245
150.556 -24.338 0.05 43.945
150.556 -24.338 0.2 29.185
150.556 -24.338 0.4 33.32
150.552 -24.3367 0.05 58.85
150.552 -24.3367 0.2 57.85
150.552 -24.3367 0.4 30.12
150.554 -24.3364 0.05 171.7
150.554 -24.3364 0.2 60.05
150.554 -24.3364 0.4 45.795
150.556 -24.336 0.05 83.55
150.556 -24.336 0.2 37.535
150.556 -24.336 0.4 43.605

Config

The config - point_simple_config.json is described below:

point_simple_config.json
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[
  {
    "id": "soil_data",
    "location": "soil_data.csv",
    "collection_date": "2020-01-01",
    "collection_time": "10:00:00",
    "X": "Longitude",
    "Y": "Latitude",
    "epsg": 4326,
    "column_info": [
      {
        "name": "Ca_Soln",
        "description": "Calcium solution in ppm"
      }
    ]
  }
]
point_simple_config.yaml
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- id: soil_data
  location: soil_data.csv
  epsg: 4326
  X: Longitude
  Y: Latitude
  collection_date: '2020-01-01'
  collection_time: '10:00:00'
  column_info:
  - description: Calcium solution in ppm
    name: Ca_Soln

Field Explanations

  • X: the x coordinate of the data is Longitude.
  • Y: the y coordinate of the data is Latitude.
  • epsg: we assume the data is recorded in WGS84 or epsg 4326.
  • column_info: similar to the same field in vector assets. This is a list of column objects with fields name and description. In this example, we describe the attribute ca_soln.

Command and Output

Save the config file as point_simple_config.json and run the follow serialisation command:

stac_generator serialise point_simple_config.json

Timeseries Point Data

In this tutorial, we describe the asset adelaide_airport.csv which contains weather station collected by a BOM station in the area:

latitude longitude elevation station YYYY-MM-DD daily_rain max_temp min_temp radiation mslp
-34.9524 138.52 2 23034 2023-01-01 0 32.2 17 31.8 1007.4
-34.9524 138.52 2 23034 2023-01-02 0 26.9 16.8 31.7 1007.5
-34.9524 138.52 2 23034 2023-01-03 0 24.1 16.5 29 1012.9
-34.9524 138.52 2 23034 2023-01-04 0 22.9 14.9 25.3 1014.9
-34.9524 138.52 2 23034 2023-01-05 0 24.8 14 31.6 1016.8
-34.9524 138.52 2 23034 2023-01-06 0 28.8 15.9 31.7 1014.1
-34.9524 138.52 2 23034 2023-01-07 0 35.1 18.3 31.5 1008.8
-34.9524 138.52 2 23034 2023-01-08 0 36.1 20.2 31.4 1008.2
-34.9524 138.52 2 23034 2023-01-09 0 31.1 17.5 31.1 1013.9
-34.9524 138.52 2 23034 2023-01-10 0 29.5 15.9 31.2 1014.8
-34.9524 138.52 2 23034 2023-01-11 0 27.1 15.9 31 1011.3
-34.9524 138.52 2 23034 2023-01-12 0 33.1 15.8 31.1 1013.8
-34.9524 138.52 2 23034 2023-01-13 0 34.7 17.1 31 1015.2
-34.9524 138.52 2 23034 2023-01-14 0 40.4 25.7 26.1 1009.3
-34.9524 138.52 2 23034 2023-01-15 0 25.3 16.3 25 1019.7
-34.9524 138.52 2 23034 2023-01-16 0 34.3 17.4 29.9 1016.8
-34.9524 138.52 2 23034 2023-01-17 0 38.1 22.1 14 1009.5
-34.9524 138.52 2 23034 2023-01-18 2.6 21.6 18.5 13.6 1015.4
-34.9524 138.52 2 23034 2023-01-19 0 22.8 14.8 29.2 1020.4
-34.9524 138.52 2 23034 2023-01-20 0 25.1 13.5 26.5 1017.7
-34.9524 138.52 2 23034 2023-01-21 0 27.7 15.4 30.4 1015.3
-34.9524 138.52 2 23034 2023-01-22 0 30.1 15.7 30.1 1016.3
-34.9524 138.52 2 23034 2023-01-23 0 29.9 16.1 22.8 1013.1
-34.9524 138.52 2 23034 2023-01-24 0 29.5 17 30 1011.9
-34.9524 138.52 2 23034 2023-01-25 0.2 24.4 14.4 30 1011.9
-34.9524 138.52 2 23034 2023-01-26 0 27.8 14.7 29.3 1018
-34.9524 138.52 2 23034 2023-01-27 0 37.8 13.4 29.4 1012.9
-34.9524 138.52 2 23034 2023-01-28 0 27.6 24.1 8.2 1008.2
-34.9524 138.52 2 23034 2023-01-29 14.2 23.5 19.2 10.5 1012.2
-34.9524 138.52 2 23034 2023-01-30 0 25.2 16 29 1014.9
-34.9524 138.52 2 23034 2023-01-31 0 23.5 13.8 29.4 1011.3
-34.9524 138.52 2 23034 2023-02-01 0 22.1 12.7 14.5 1010.4

Config

We prepare the point_time_series_config.json as follows:

point_time_series_config.json
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[
  {
    "id": "adelaide_airport",
    "location": "adelaide_airport.csv",
    "collection_date": "2023-01-01",
    "collection_time": "09:00:00",
    "X": "longitude",
    "Y": "latitude",
    "Z": "elevation",
    "T": "YYYY-MM-DD",
    "epsg": 7843,
    "column_info": [
      {
        "name": "daily_rain",
        "description": "Observed daily rain fall in mm"
      },
      {
        "name": "max_temp",
        "description": "Observed daily maximum temperature in degree C"
      },
      {
        "name": "min_temp",
        "description": "Observed daily minimum temperature in degree C"
      },
      {
        "name": "radiation",
        "description": "Total incoming downward shortwave radiation on a horizontal surface MJ/sqm"
      },
      {
        "name": "mslp",
        "description": "Mean sea level pressure in hPa"
      }
    ]
  }
]
point_time_series_config.yaml
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- id: adelaide_airport
  location: adelaide_airport.csv
  collection_date: '2023-01-01'
  collection_time: 09:00:00
  X: longitude
  Y: latitude
  Z: elevation
  T: YYYY-MM-DD
  epsg: 7843
  column_info:
  - description: Observed daily rain fall in mm
    name: daily_rain
  - description: Observed daily maximum temperature in degree C
    name: max_temp
  - description: Observed daily minimum temperature in degree C
    name: min_temp
  - description: Total incoming downward shortwave radiation on a horizontal surface
      MJ/sqm
    name: radiation
  - description: Mean sea level pressure in hPa
    name: mslp

Field Explanation

  • T: describe the name of the time column - i.e. YYYY-MM-DD.

In summary, the values for X, Y, Z, T are obtained from the raw csv - i.e. longitude, latitude, elevation and YYYY-MM-DD respectively.

epsg value cannot be derived from the csv and must be known by the user - i.e. reading dataset metadata on BOM/SILO website.

Command and Output

Save the config as point_time_series_config.json. Run the following command to serialise the metadata:

stac_generator serialise point_time_series_config.json