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': 'FloodPolygonBuildingFunction',
'name': tr('Polygon flood on buildings'),
'impact': tr('Be flooded'),
'title': tr('Be flooded'),
'function_type': 'qgis2.0',
'author': 'Dmitry Kolesov',
'date_implemented': 'N/A',
'overview': tr('N/A'),
'detailed_description': tr('N/A'),
'hazard_input': '',
'exposure_input': '',
'output': '',
'actions': '',
'limitations': [],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': [hazard_flood],
'continuous_hazard_units': [],
'vector_hazard_classifications': [
flood_vector_hazard_classes],
'raster_hazard_classifications': [],
'additional_keywords': []
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('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': 'FloodPolygonBuildingFunction',
'name': tr('Polygon flood on buildings'),
'impact': tr('Be flooded'),
'title': tr('Be flooded'),
'function_type': 'qgis2.0',
'author': 'Dmitry Kolesov',
'date_implemented': 'N/A',
'overview': tr('N/A'),
'detailed_description': tr('N/A'),
'hazard_input': '',
'exposure_input': '',
'output': '',
'actions': '',
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': [hazard_flood, hazard_tsunami],
'units': [unit_wetdry],
'layer_constraints': [layer_vector_polygon]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [unit_building_type_type],
'layer_constraints': [layer_vector_polygon]
}
},
'parameters': OrderedDict([
# This field of the exposure layer contains
# information about building types
('building_type_field', 'TYPE'),
# This field of the hazard layer contains information
# about inundated areas
('affected_field', 'FLOODPRONE'),
# This value in 'affected_field' of the hazard layer
# marks the areas as inundated
('affected_value', 'YES'),
('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':
'VolcanoPointBuildingFunction',
'name':
tr('Point volcano on buildings'),
'impact':
tr('Be affected'),
'title':
tr('Be affected'),
'function_type':
'old-style',
'author':
'AIFDR',
'date_implemented':
'N/A',
'overview':
tr('To assess the impacts of volcano points on buildings.'),
'detailed_description':
'',
'hazard_input':
tr('The hazard layer must be a point layer. '
'This point will be buffered with the radii specified in '
'the parameters as the hazard zone. If you want to see '
'the name of the volcano in the result, you need to '
'specify the volcano name attribute in the Impact Function '
'option.'),
'exposure_input':
tr('Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output':
tr('Vector layer contains Map of building exposed to '
'volcanic hazard zones for each radius.'),
'actions':
tr('Provide details about how many building would likely be '
'affected by each hazard zones.'),
'limitations': [],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode':
layer_mode_classified,
'layer_geometries': [layer_geometry_point],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': [hazard_volcano],
'continuous_hazard_units': [],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [],
'additional_keywords': [volcano_name_field]
},
'exposure': {
'layer_mode':
layer_mode_classified,
'layer_geometries':
[layer_geometry_polygon, layer_geometry_point],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters':
OrderedDict([
# The list of radii in km for volcano point hazard
('distances', distance()),
('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': 'VolcanoPointBuildingFunction',
'name': tr('Point volcano on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'AIFDR',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of volcano points on buildings.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a point layer. '
'This point will be buffered with the radii specified in '
'the parameters as the hazard zone. If you want to see '
'the name of the volcano in the result, you need to '
'specify the volcano name attribute in the Impact Function '
'option.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output': tr(
'Vector layer contains Map of building exposed to '
'volcanic hazard zones for each radius.'),
'actions': tr(
'Provide details about how many building would likely be '
'affected by each hazard zones.'),
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': [hazard_volcano],
'units': [unit_volcano_categorical],
'layer_constraints': [
layer_vector_point
]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [
unit_building_type_type,
unit_building_generic],
'layer_constraints': [
layer_vector_polygon,
layer_vector_point]
}
},
'parameters': OrderedDict([
# The list of radii in km for volcano point hazard
('distances [km]', [3, 5, 10]),
# The attribute for name of the volcano in hazard layer
('volcano name attribute', 'NAME'),
('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':
'ClassifiedPolygonHazardBuildingFunction',
'name':
tr('Classified polygon hazard on buildings'),
'impact':
tr('Be affected'),
'title':
tr('Be affected'),
'function_type':
'qgis2.0',
'author':
'Akbar Gumbira ([email protected])',
'date_implemented':
'17/04/2015',
'overview':
tr('To assess the impact of each hazard zone on buildings.'),
'detailed_description':
'',
'hazard_input':
tr('The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the hazard '
'zone that can be specified in the impact function options.'),
'exposure_input':
tr('Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output':
tr('A vector layer of buildings with each tagged according to '
'the hazard zone in which it falls.'),
'actions':
tr('Provide details about how many buildings fall within '
'each hazard zone.'),
'limitations': [],
'citations': [{
'text': None,
'link': None
}],
'legend_title':
tr('Building count'),
'legend_units':
tr('(building)'),
'legend_notes':
tr('Thousand separator is represented by %s' %
get_thousand_separator()),
'layer_requirements': {
'hazard': {
'layer_mode':
layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types':
hazard_all,
'continuous_hazard_units': [],
'vector_hazard_classifications':
[generic_vector_hazard_classes],
'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([('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': 'ClassifiedRasterHazardBuildingFunction',
'name': tr('Classified raster hazard on buildings'),
'impact': tr('Be impacted'),
'title': tr('Be impacted in each hazard class'),
'function_type': 'old-style',
'author': 'Dianne Bencito',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of a classified hazard in raster '
'format on a buildings vector layer.'),
'detailed_description': tr(
'This function will treat the values in the hazard raster '
'layer as classes representing low, medium and high '
'impact. You need to ensure that the keywords for the hazard '
'layer have been set appropriately to define these classes.'
'The number of buildings that will be impacted will be '
'calculated for each class. The report will show the total '
'number of buildings that will be affected for each '
'hazard class.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents the '
'class of the hazard. There should be 3 classes: e.g. '
'1, 2, and 3.'),
'exposure_input': tr(
'A vector polygon layer which can be extracted from OSM '
'where each polygon represents the footprint of a '
'building.'),
'output': tr(
'The impact layer will contain all structures that were '
'exposed to the highest class (3) and a summary table '
'containing the number of structures in each class.'),
'actions': tr(
'Provide details about the number of buildings that are '
'within each hazard class.'),
'limitations': [tr('The number of classes is three.')],
'citations': [],
'legend_notes': '',
'map_title': tr('Buildings affected'),
'legend_units': tr('(Low, Medium, High)'),
'legend_title': tr('Structure inundated status'),
'layer_name': tr('Estimated buildings affected'),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_raster],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': hazard_all,
'continuous_hazard_units': [],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [
generic_raster_hazard_classes
],
'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
'parameters': OrderedDict([
('Categorical hazards', categorical_hazards()),
('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': 'VolcanoPolygonBuildingFunction',
'name': tr('Polygon volcano on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'AIFDR',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of volcano eruption on building.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the volcano hazard '
'zone that can be specified in the impact function option.'
'The valid values for the volcano hazard zone are "Kawasan '
'Rawan Bencana I", "Kawasan Rawan Bencana II", '
'or "Kawasan Rawan Bencana III." If you want to see the '
'name of the volcano in the result, you need to specify '
'the volcano name attribute in the Impact Function '
'options.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output': tr(
'Vector layer contains Map of building exposed to '
'volcanic hazard zones for each Kawasan Rawan Bencana.'),
'actions': tr(
'Provide details about the number of buildings that are '
'within each hazard zone.'),
'limitations': [],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': [hazard_volcano],
'continuous_hazard_units': [],
'vector_hazard_classifications': [
volcano_vector_hazard_classes],
'raster_hazard_classifications': [],
'additional_keywords': [
volcano_name_field]
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_polygon,
layer_geometry_point
],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('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': 'VolcanoPolygonBuildingFunction',
'name': tr('Polygon volcano on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'AIFDR',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of volcano eruption on building.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the volcano hazard '
'zone that can be specified in the impact function option. '
'There are three classes low, medium, and high. The default '
'values are "Kawasan Rawan Bencana I" for low, "Kawasan Rawan '
'Bencana II" for medium, and "Kawasan Rawan Bencana III for '
'high." If you want to see the name of the volcano in the '
'result, you need to specify the volcano name attribute in '
'the Impact Function options.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output': tr(
'Vector layer contains Map of building exposed to '
'volcanic hazard zones for each Kawasan Rawan Bencana.'),
'actions': tr(
'Provide details about the number of buildings that are '
'within each hazard zone.'),
'limitations': [],
'citations': [
{
'text': None,
'link': None
}
],
'legend_title': tr('Building count'),
'legend_units': tr('(building)'),
'legend_notes': tr(
'Thousand separator is represented by %s' %
get_thousand_separator()),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': [hazard_volcano],
'continuous_hazard_units': [],
'vector_hazard_classifications': [
volcano_vector_hazard_classes],
'raster_hazard_classifications': [],
'additional_keywords': [
volcano_name_field]
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_polygon,
layer_geometry_point
],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('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': 'ClassifiedPolygonHazardBuildingFunction',
'name': tr('Classified polygon hazard on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'qgis2.0',
'author': 'Akbar Gumbira ([email protected])',
'date_implemented': '17/04/2015',
'overview': tr(
'To assess the impact of each hazard zone on buildings.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the hazard '
'zone that can be specified in the impact function options.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output': tr(
'A vector layer of buildings with each tagged according to '
'the hazard zone in which it falls.'),
'actions': tr(
'Provide details about how many buildings fall within '
'each hazard zone.'),
'limitations': [],
'citations': [
{
'text': None,
'link': None
}
],
'map_title': tr('Buildings affected'),
'legend_title': tr('Building count'),
'legend_units': tr('(building)'),
'legend_notes': tr(
'Thousand separator is represented by %s' %
get_thousand_separator()),
'layer_name': tr('Buildings affected'),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': hazard_all,
'continuous_hazard_units': [],
'vector_hazard_classifications': [
generic_vector_hazard_classes],
'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([
('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': 'ClassifiedPolygonHazardBuildingFunction',
'name': tr('Classified polygon hazard on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'Akbar Gumbira ([email protected])',
'date_implemented': '17/04/2015',
'overview': tr(
'To assess the impact of each hazard zone on buildings.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the hazard '
'zone that can be specified in the impact function options.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output': tr(
'A vector layer of buildings with each tagged according to '
'the hazard zone in which it falls.'),
'actions': tr(
'Provide details about how many buildings fall within '
'each hazard zone.'),
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': hazard_all,
'units': [unit_classified],
'layer_constraints': [layer_vector_polygon]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [
unit_building_type_type,
unit_building_generic],
'layer_constraints': [
layer_vector_polygon,
layer_vector_point]
}
},
'parameters': OrderedDict([
# The attribute of hazard zone in hazard layer
('hazard zone attribute', 'KRB'),
('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':
'ClassifiedPolygonHazardBuildingFunction',
'name':
tr('Classified polygon hazard on buildings'),
'impact':
tr('Be affected'),
'title':
tr('Be affected'),
'function_type':
'old-style',
'author':
'Akbar Gumbira ([email protected])',
'date_implemented':
'17/04/2015',
'overview':
tr('To assess the impact of each hazard zone on buildings.'),
'detailed_description':
'',
'hazard_input':
tr('The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the hazard '
'zone that can be specified in the impact function options.'),
'exposure_input':
tr('Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output':
tr('A vector layer of buildings with each tagged according to '
'the hazard zone in which it falls.'),
'actions':
tr('Provide details about how many buildings fall within '
'each hazard zone.'),
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': hazard_all,
'units': [unit_classified],
'layer_constraints': [layer_vector_polygon]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [unit_building_type_type, unit_building_generic],
'layer_constraints':
[layer_vector_polygon, layer_vector_point]
}
},
'parameters':
OrderedDict([
# The attribute of hazard zone in hazard layer
('hazard zone attribute', 'KRB'),
('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':
'VolcanoPolygonBuildingFunction',
'name':
tr('Polygon volcano on buildings'),
'impact':
tr('Be affected'),
'title':
tr('Be affected'),
'function_type':
'old-style',
'author':
'AIFDR',
'date_implemented':
'N/A',
'overview':
tr('To assess the impacts of volcano eruption on building.'),
'detailed_description':
'',
'hazard_input':
tr('The hazard layer must be a polygon layer. This layer '
'must have an attribute representing the volcano hazard '
'zone that can be specified in the impact function option.'
'The valid values for the volcano hazard zone are "Kawasan '
'Rawan Bencana I", "Kawasan Rawan Bencana II", '
'or "Kawasan Rawan Bencana III." If you want to see the '
'name of the volcano in the result, you need to specify '
'the volcano name attribute in the Impact Function '
'options.'),
'exposure_input':
tr('Vector polygon layer extracted from OSM where each '
'polygon represents the footprint of a building.'),
'output':
tr('Vector layer contains Map of building exposed to '
'volcanic hazard zones for each Kawasan Rawan Bencana.'),
'actions':
tr('Provide details about the number of buildings that are '
'within each hazard zone.'),
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': [hazard_volcano],
'units': [unit_volcano_categorical],
'layer_constraints': [layer_vector_polygon]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [unit_building_type_type, unit_building_generic],
'layer_constraints':
[layer_vector_polygon, layer_vector_point]
}
},
'parameters':
OrderedDict([
# The attribute of hazard zone in hazard layer
('hazard zone attribute', 'KRB'),
# The attribute for name of the volcano in hazard layer
('volcano name attribute', 'NAME'),
('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": [],
"categories": {
"hazard": {
"definition": hazard_definition,
"subcategories": [hazard_flood, hazard_tsunami],
"units": [unit_metres_depth, unit_feet_depth],
"layer_constraints": [layer_raster_continuous],
},
"exposure": {
"definition": exposure_definition,
"subcategories": [exposure_structure],
"units": [unit_building_type_type, unit_building_generic],
"layer_constraints": [layer_vector_polygon, layer_vector_point],
},
},
"parameters": OrderedDict(
[
("threshold [m]", 1.0),
("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': 'FloodPolygonBuildingFunction',
'name': tr('Polygon flood on buildings'),
'impact': tr('Be flooded'),
'title': tr('Be flooded'),
'function_type': 'qgis2.0',
'author': 'Dmitry Kolesov',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of (flood or tsunami) inundation '
'on building footprints with hazard in vector format.'),
'detailed_description': tr(
'The inundation status is calculated for each building '
'(using the centroid if it is a polygon) based on the value '
'of hazard attribute. The attribute and the values that are '
'considered as flooded can be configured in impact function '
'options.'),
'hazard_input': tr(
'A hazard vector layer whose attribute that can be used to '
'mark whether a polygon is flood or not.'),
'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': '',
'limitations': [],
'citations': [],
'legend_units': '',
'legend_notes': '',
'map_title': tr('Buildings inundated'),
'legend_title': tr('Structure inundated status'),
'layer_name': tr('Flooded buildings'),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': [hazard_flood],
'continuous_hazard_units': [],
'vector_hazard_classifications': [
flood_vector_hazard_classes],
'raster_hazard_classifications': [],
'additional_keywords': []
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_polygon,
layer_geometry_point],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
('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':
'FloodPolygonBuildingFunction',
'name':
tr('Polygon flood on buildings'),
'impact':
tr('Be flooded'),
'title':
tr('Be flooded'),
'function_type':
'qgis2.0',
'author':
'Dmitry Kolesov',
'date_implemented':
'N/A',
'overview':
tr('N/A'),
'detailed_description':
tr('N/A'),
'hazard_input':
'',
'exposure_input':
'',
'output':
'',
'actions':
'',
'limitations': [],
'citations': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': [hazard_flood, hazard_tsunami],
'units': [unit_wetdry],
'layer_constraints': [layer_vector_polygon]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [unit_building_type_type],
'layer_constraints': [layer_vector_polygon]
}
},
'parameters':
OrderedDict([
# This field of the exposure layer contains
# information about building types
('building_type_field', 'TYPE'),
# This field of the hazard layer contains information
# about inundated areas
('affected_field', 'FLOODPRONE'),
# This value in 'affected_field' of the hazard layer
# marks the areas as inundated
('affected_value', 'YES'),
('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': 'VolcanoPointBuildingFunction',
'name': tr('Point volcano on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'AIFDR',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of volcano points on buildings.'),
'detailed_description': '',
'hazard_input': tr(
'The hazard layer must be a point layer. This point will be '
'buffered with the radii (in kilometer) specified in the '
'parameters as the hazard zone. If you want to see the name '
'of the volcano in the result, you need to specify the '
'volcano name attribute in the Impact Function option.'),
'exposure_input': tr(
'Vector polygon layer extracted from OSM where each polygon '
'represents the footprint of a building.'),
'output': tr(
'Vector layer contains Map of building exposed to volcanic '
'hazard zones for each radius.'),
'actions': tr(
'Provide details about how many building would likely be '
'affected by each hazard zones.'),
'limitations': [],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_point],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': [hazard_volcano],
'continuous_hazard_units': [],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [],
'additional_keywords': [volcano_name_field]
},
'exposure': {
'layer_mode': layer_mode_classified,
'layer_geometries': [
layer_geometry_polygon,
layer_geometry_point],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters': OrderedDict([
# The list of radii in km for volcano point hazard
('distances', distance()),
('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': 'EarthquakeBuildingFunction',
'name': tr('Earthquake on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'N/A',
'date_implemented': 'N/A',
'overview': tr(
'This impact function will calculate the impact of an '
'earthquake on buildings, reporting how many are expected '
'to be damaged.'),
'detailed_description': '',
'hazard_input': '',
'exposure_input': '',
'output': '',
'actions': '',
'limitations': [],
'citations': [],
'map_title': tr('Building affected by earthquake'),
'legend_notes': tr(
'The level of the impact is according to the threshold the '
'user input.'),
'legend_units': tr('(mmi)'),
'legend_title': tr('Impact level'),
'layer_name': tr('Estimated buildings affected'),
'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_earthquake],
'continuous_hazard_units': [unit_mmi],
'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(
[('low_threshold', low_threshold()),
('medium_threshold', medium_threshold()),
('high_threshold', high_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': 'EarthquakeBuildingFunction',
'name': tr('Earthquake on buildings'),
'impact': tr('Be affected'),
'title': tr('Be affected'),
'function_type': 'old-style',
'author': 'N/A',
'date_implemented': 'N/A',
'overview': tr(
'This impact function will calculate the impact of an '
'earthquake on buildings, reporting how many are expected '
'to be damaged.'),
'detailed_description': '',
'hazard_input': '',
'exposure_input': '',
'output': '',
'actions': '',
'limitations': [],
'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_earthquake],
'continuous_hazard_units': [unit_mmi],
'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(
[('low_threshold', low_threshold()),
('medium_threshold', medium_threshold()),
('high_threshold', high_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': 'ClassifiedRasterHazardBuildingFunction',
'name': tr('Classified raster hazard on buildings'),
'impact': tr('Be impacted'),
'title': tr('Be impacted in each hazard class'),
'function_type': 'old-style',
'author': 'Dianne Bencito',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of a classified hazard in raster '
'format on a buildings vector layer.'),
'detailed_description': tr(
'This function will treat the values in the hazard raster '
'layer as classes representing low, medium and high '
'impact. You need to ensure that the keywords for the hazard '
'layer have been set appropriately to define these classes.'
'The number of buildings that will be impacted will be '
'calculated for each class. The report will show the total '
'number of buildings that will be affected for each '
'hazard class.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents the '
'class of the hazard. There should be 3 classes: e.g. '
'1, 2, and 3.'),
'exposure_input': tr(
'A vector polygon layer which can be extracted from OSM '
'where each polygon represents the footprint of a '
'building.'),
'output': tr(
'The impact layer will contain all structures that were '
'exposed to the highest class (3) and a summary table '
'containing the number of structures in each class.'),
'actions': tr(
'Provide details about the number of buildings that are '
'within each hazard class.'),
'limitations': [tr('The number of classes is three.')],
'citations': [
{
'text': None,
'link': None
}
],
'legend_notes': '',
'legend_units': tr('(Low, Medium, High)'),
'legend_title': tr('Structure inundated status'),
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_classified,
'layer_geometries': [layer_geometry_raster],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': hazard_all,
'continuous_hazard_units': [],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [
generic_raster_hazard_classes
],
'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
'parameters': OrderedDict([
('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) 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':
'TsunamiRasterBuildingFunction',
'name':
tr('Raster tsunami on buildings'),
'impact':
tr('Be inundated'),
'title':
tr('Be inundated'),
'function_type':
'old-style',
# should be a list, but we can do it later.
'author':
'Ole Nielsen, Kristy van Putten, and Ismail Sunni',
'date_implemented':
'N/A',
'overview':
tr('To assess the impacts of tsunami inundation on building '
'footprints in vector format 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 '
'tsunami threshold. The threshold can be configured in '
'impact function options.'),
'hazard_input':
tr('A hazard raster layer where each cell represents tsunami '
'inundation depth (in meters).'),
'exposure_input':
tr('Vector polygon or point layer where each feature represents '
'the footprint of a building.'),
'output':
tr('Vector layer contains building is estimated to be '
'inundated and the breakdown of the building by type.'),
'actions':
tr('Provide details about where critical infrastructure '
'might be inundated.'),
'limitations': [
tr('This function only flags buildings as impacted or not either '
'based on a fixed threshold')
],
'citations': [{
'text':
tr('Papadopoulos, Gerassimos A., and Fumihiko Imamura. '
'"A proposal for a new tsunami intensity scale." '
'ITS 2001 proceedings, no. 5-1, pp. 569-577. 2001.'),
'link':
None
}],
'legend_notes':
'',
'legend_title':
tr('Inundated structure status'),
'legend_units':
tr('(low, medium, high, and very high)'),
'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_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([('low_threshold', low_threshold()),
('medium_threshold', medium_threshold()),
('high_threshold', high_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':
'FloodPolygonBuildingFunction',
'name':
tr('Polygon flood on buildings'),
'impact':
tr('Be flooded'),
'title':
tr('Be flooded'),
'function_type':
'qgis2.0',
'author':
'Dmitry Kolesov',
'date_implemented':
'N/A',
'overview':
tr('To assess the impacts of (flood or tsunami) inundation '
'on building footprints with hazard in vector format.'),
'detailed_description':
tr('The inundation status is calculated for each building '
'(using the centroid if it is a polygon) based on the value '
'of hazard attribute. The attribute and the values that are '
'considered as flooded can be configured in impact function '
'options.'),
'hazard_input':
tr('A hazard vector layer whose attribute that can be used to '
'mark whether a polygon is flood or not.'),
'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':
'',
'limitations': [],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode':
layer_mode_classified,
'layer_geometries': [layer_geometry_polygon],
'hazard_categories': [
hazard_category_single_event,
hazard_category_multiple_event
],
'hazard_types': [hazard_flood],
'continuous_hazard_units': [],
'vector_hazard_classifications':
[flood_vector_hazard_classes],
'raster_hazard_classifications': [],
'additional_keywords': []
},
'exposure': {
'layer_mode':
layer_mode_classified,
'layer_geometries':
[layer_geometry_polygon, layer_geometry_point],
'exposure_types': [exposure_structure],
'exposure_units': [],
'exposure_class_fields': [structure_class_field],
'additional_keywords': []
}
},
'parameters':
OrderedDict([('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': [],
'categories': {
'hazard': {
'definition': hazard_definition,
'subcategories': [
hazard_flood,
hazard_tsunami
],
'units': [
unit_metres_depth,
unit_feet_depth],
'layer_constraints': [
layer_raster_continuous,
]
},
'exposure': {
'definition': exposure_definition,
'subcategories': [exposure_structure],
'units': [
unit_building_type_type,
unit_building_generic],
'layer_constraints': [
layer_vector_polygon,
layer_vector_point
]
}
},
'parameters': OrderedDict([
('threshold [m]', 1.0),
('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': 'TsunamiRasterBuildingFunction',
'name': tr('Raster tsunami on buildings'),
'impact': tr('Be inundated'),
'title': tr('Be inundated'),
'function_type': 'old-style',
# should be a list, but we can do it later.
'author': 'Ole Nielsen, Kristy van Putten, and Ismail Sunni',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of tsunami inundation on building '
'footprints in vector format 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 '
'tsunami threshold. The threshold can be configured in '
'impact function options.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents tsunami '
'inundation depth (in meters).'),
'exposure_input': tr(
'Vector polygon or point layer where each feature represents '
'the footprint of a building.'),
'output': tr(
'Vector layer contains building is estimated to be '
'inundated and the breakdown of the building by type.'),
'actions': tr(
'Provide details about where critical infrastructure '
'might be inundated.'),
'limitations': [tr(
'This function only flags buildings as impacted or not either '
'based on a fixed threshold')
],
'citations': [
tr('Papadopoulos, Gerassimos A., and Fumihiko Imamura. '
'"A proposal for a new tsunami intensity scale." '
'ITS 2001 proceedings, no. 5-1, pp. 569-577. 2001.')
],
'legend_notes': '',
'map_title': tr('Inundated buildings'),
'legend_title': tr('Inundated structure status'),
'legend_units': tr('(low, medium, high, and very high)'),
'layer_name': tr('Estimated buildings affected'),
'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_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(
[
('low_threshold', low_threshold()),
('medium_threshold', medium_threshold()),
('high_threshold', high_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
