`damagescanner.risk`

Created on Thu Jan 31 11:54:09 2019

@author: cenv0574

Module Contents

Functions

`monetary_risk`(RPS, loss_list)	Calculates the monetary risk based on the return periods and the losses.
`RasterBased`(landuse_ras, inundation_path, curve_path, ...)	Raster-based implementation of a risk assessment.
`VectorBased`(landuse_vec, inundation_path, curve_path, ...)	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).