NASA FIRMS - Active Fire module

class pyro_risks.datasets.nasa_wildfires.NASAFIRMS(source_path: Optional[str] = None, fmt: Optional[str] = None, use_cols: Optional[List[str]] = None)[source]

Bases: pandas.core.frame.DataFrame

Wildfire history dataset on French territory, using data from NASA satellites. Accessible by completing the form at https://effis.jrc.ec.europa.eu/applications/data-request-form/

Careful when completing the form, you can either choose to get the dataset in json format or xlsx format. However if your source data is in a csv format, you can still use this class to clean it using the parameter fmt.

By default, the format is considered to be json.

Parameters

  • source_path – str Path or URL to your version of the source data

  • fmt – str Format of the source data, can either be “csv”, “xlsx” or “json”. Default is “json”.

  • use_cols – List[str] List of columns to read from the source

fmt = 'json'
kept_cols = ['latitude', 'longitude', 'acq_date', 'acq_time', 'confidence', 'bright_t31', 'frp']
class pyro_risks.datasets.nasa_wildfires.NASAFIRMS_VIIRS(source_path: Optional[str] = None, fmt: Optional[str] = None, use_cols: Optional[List[str]] = None)[source]

Bases: pandas.core.frame.DataFrame

Wildfire history dataset on French territory, using data from VIIRS.

Parameters

  • source_path – str Path or URL to your version of the source data

  • fmt – str Format of the source data, can either be “csv”, “xlsx” or “json”. Default is “json”.

  • use_cols – List[str] List of columns to read from the source

fmt = 'csv'
kept_cols = ['latitude', 'longitude', 'acq_date', 'acq_time', 'confidence', 'bright_ti4', 'bright_ti5', 'frp', 'type']