Configuration files¶

The use of a bdc-in-a-box is done with a script and two auxiliary files. In this section, we will briefly present the characteristics and possibilities with each of these files.

bdc-in-a-box.sh¶

bdc-in-a-box.sh is the script that reads the auxiliary files and uses the information in each one to download the data and register in the ODC. Essentially this script automates the operations of stac2odc, which brings the user the ease of not working directly with the parameters of stac2odc.

collections.list¶

collections.list is a CSV file created to facilitate the definition of which data should be considered in indexing. This section presents its structure.

The file is composed of 6 columns (in order), being them:

Collection Name (This name must be the same as the one made available in BDC-STAC)
- e.g. CB4_64_16D_STK_v1
Platform (Sensor platform that generated the data. User-defined name pattern)
- e.g. CBERS4
Sensor (Sensor that collected the data. User-defined name pattern)
- e.g. AWFI
ODC metadata type (Check ODC-Dataset documentation)
- e.g. eo
Number of images to be indexed
- e.g. 5000
File with parameters for filtering the data to be downloaded in bdc-in-a-box. The parameters are the same as those offered in the stac.py. The file may be blank, but must be declared in the lines of the collections.list file
- e.g. advanced_filter.json

advanced_filter.json¶

The file advanced_filter.json allows the filter functionalities implemented in stac.py to be used by bdc-in-a-box users. This way, the same parameters that stac.py accepts can be inserted in this JSON file. Internally, the content of advanced_filter.json is passed to the search method of stac.py.

For example, consider the file advanced_filter.json presented below.

Code snippet 6 - An example filter file used by bdc-in-a-box.¶

{
    "datetime": "2016-09-13/2017-12-31",
    "intersects": {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -44.78027343749999,
              -14.434680215297268
            ],
            [
              -41.9677734375,
              -14.434680215297268
            ],
            [
              -41.9677734375,
              -11.480024648555816
            ],
            [
              -44.78027343749999,
              -11.480024648555816
            ],
            [
              -44.78027343749999,
              -14.434680215297268
            ]
          ]
        ]
    }
}

Internally, the contents of this file will be passed as follows to stac.py:

items = stac.search({
    "datetime": "2016-09-13/2017-12-31",
    "intersects": {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -44.78027343749999,
              -14.434680215297268
            ],
            [
              -41.9677734375,
              -14.434680215297268
            ],
            [
              -41.9677734375,
              -11.480024648555816
            ],
            [
              -44.78027343749999,
              -11.480024648555816
            ],
            [
              -44.78027343749999,
              -14.434680215297268
            ]
          ]
        ]
    }
})