def as_dict():
"""Return metadata as a dictionary.
This is a static method. You can use it to get the metadata in
dictionary format for an impact function.
:returns: A dictionary representing all the metadata for the
concrete impact function.
:rtype: dict
"""
dict_meta = {
'id': 'FloodRasterBuildingFunction',
'name': tr('Raster flood on buildings'),
'impact': tr('Be flooded'),
'title': tr('Be flooded'),
'function_type': 'old-style',
# should be a list, but we can do it later.
'author': 'Ole Nielsen and Kristy van Putten',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of (flood or tsunami) inundation '
'on building footprints originating from OpenStreetMap '
'(OSM) with hazard in raster format.'),
'detailed_description': tr(
'The inundation status is calculated for each building '
'(using the centroid if it is a polygon) based on the '
'flood threshold. The threshold can be configured in '
'impact function options.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents flood '
'depth (in meters).'),
'exposure_input': tr(
'Vector polygon or point layer extracted from OSM where '
'each feature represents the footprint of a building.'),
'output': tr(
'Vector layer contains building is estimated to be '
'flooded and the breakdown of the building by type.'),
'actions': tr(
'Provide details about where critical infrastructure '
'might be flooded.'),
'limitations': [
tr('This function only flags buildings as impacted or not '
'either based on a fixed threshold')
],
'citations': [
{
'text': None,
'link': None
}
],
'legend_notes': '',
'legend_title': tr('Flooded structure status'),
'legend_units': tr('(flooded, wet, or dry)'),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_continuous,
'layer_geometries': [layer_geometry_raster],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': [hazard_flood],
'continuous_hazard_units': [unit_feet, unit_metres],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [],
'additional_keywords': []
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_point,
layer_geometry_polygon
],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('threshold', threshold()),
('postprocessors', OrderedDict([
('BuildingType', building_type_postprocessor())
]))
])
}
return dict_meta
def as_dict():
"""Return metadata as a dictionary.
This is a static method. You can use it to get the metadata in
dictionary format for an impact function.
:returns: A dictionary representing all the metadata for the
concrete impact function.
:rtype: dict
"""
dict_meta = {
'id': 'FloodRasterBuildingFunction',
'name': tr('Raster flood on buildings'),
'impact': tr('Be flooded'),
'title': tr('Be flooded'),
'function_type': 'old-style',
# should be a list, but we can do it later.
'author': 'Ole Nielsen and Kristy van Putten',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of (flood or tsunami) inundation '
'on building footprints originating from OpenStreetMap '
'(OSM).'),
'detailed_description': tr(
'The inundation status is calculated for each building '
'(using the centroid if it is a polygon) based on the '
'hazard levels provided. if the hazard is given as a '
'raster a threshold of 1 meter is used. This is '
'configurable through the InaSAFE interface. If the '
'hazard is given as a vector polygon layer buildings are '
'considered to be impacted depending on the value of '
'hazard attributes (in order) affected" or "FLOODPRONE": '
'If a building is in a region that has attribute '
'"affected" set to True (or 1) it is impacted. If '
'attribute "affected" does not exist but "FLOODPRONE" '
'does, then the building is considered impacted if '
'"FLOODPRONE" is "yes". If neither affected" nor '
'"FLOODPRONE" is available, a building will be impacted '
'if it belongs to any polygon. The latter behaviour is '
'implemented through the attribute "inapolygon" which is '
'automatically assigned.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents flood '
'depth (in meters).'),
'exposure_input': tr(
'Vector polygon or point layer extracted from OSM where '
'each feature represents the footprint of a building.'),
'output': tr(
'Vector layer contains building is estimated to be '
'flooded and the breakdown of the building by type.'),
'actions': tr(
'Provide details about where critical infrastructure '
'might be flooded.'),
'limitations': [
tr('This function only flags buildings as impacted or not '
'either based on a fixed threshold in case of raster '
'hazard or the the attributes mentioned under input '
'in case of vector hazard.')
],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_continuous,
'layer_geometries': [layer_geometry_raster],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': [hazard_flood, hazard_tsunami],
'continuous_hazard_units': [unit_feet, unit_metres],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [],
'additional_keywords': []
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_point,
layer_geometry_polygon
],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('threshold', threshold()),
('postprocessors', OrderedDict([
('BuildingType', building_type_postprocessor())
]))
])
}
return dict_meta