damagescanner.risk
Created on Thu Jan 31 11:54:09 2019
@author: cenv0574
Module Contents
Functions
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Calculates the monetary risk based on the return periods and the losses. |
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Raster-based implementation of a risk assessment. |
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Vector based implementation of a direct damage assessment |
- damagescanner.risk.monetary_risk(RPS, loss_list)[source]
Calculates the monetary risk based on the return periods and the losses.
- Arguments:
RPS : List of return periods (in years) for which the losses are calculated. loss_list : List of losses (in euro) for each return period.
- Returns:
total_risk : Returns the total risk for the area
- damagescanner.risk.RasterBased(landuse_ras, inundation_path, curve_path, maxdam_path, per_landuse=False)[source]
Raster-based implementation of a risk assessment.
- Arguments:
landuse_map : GeoTiff with land-use information per grid cell. Make sure the land-use categories correspond with the curves and maximum damages (see below). Furthermore, the resolution and extend of the land-use map has to be exactly the same as the inundation map.
inun_map : GeoTiff with inundation depth per grid cell. Make sure that the unit of the inundation map corresponds with the unit of the first column of the curves file.
curve_path : File with the stage-damage curves of the different land-use classes. Can also be a pandas DataFrame or numpy Array.
maxdam_path : File with the maximum damages per land-use class (in euro/m2). Can also be a pandas DataFrame or numpy Array.
- Optional Arguments:
per_landuse : Set to True if you would like the output er land-use class.
- Returns:
total_risk : Returns the total risk for the area
- damagescanner.risk.VectorBased(landuse_vec, inundation_path, curve_path, maxdam_path, per_landuse=False)[source]
Vector based implementation of a direct damage assessment
- Arguments:
landuse_map : Shapefile, Pandas DataFrame or Geopandas GeoDataFrame with land-use information of the area.
inun_map : GeoTiff with inundation depth per grid cell. Make sure that the unit of the inundation map corresponds with the unit of the first column of the curves file.
curve_path : File with the stage-damage curves of the different land-use classes. Can also be a pandas DataFrame (but not a numpy Array).
maxdam_path : File with the maximum damages per land-use class (in euro/m2). Can also be a pandas DataFrame (but not a numpy Array).
- Optional Arguments:
per_landuse : Set to True if you would like the output er land-use class.
landuse_col : Specify the column name of the unique landuse id’s. Default is set to landuse.
- Returns:
total_risk : Returns the total risk for the area