Damage assessment tool for natural disasters

pip install damagescanner==0.4.5


Build Status Documentation Status PyPI version DOI PyPI - Downloads


Python toolkit for direct damage assessments for natural disasters.

Please refer to the ReadTheDocs of this project for the full documentation of all functions.

Requirements: NumPy, pandas, geopandas, matplotlib, rasterio, tqdm

Please note: This package is still in development phase. In case of any problems, or if you have any suggestions for improvements, please raise an issue.


This package is (loosely) based on the original DamageScanner, which calculated potential flood damages based on inundation depth and land use using depth-damage curves in the Netherlands. The DamageScanner was originally developed for the 'Netherlands Later' project (Klijn et al., 2007). The original land-use classes were based on the Land-Use Scanner in order to evaluate the effect of future land-use change on flood damages.

This package aims to make this method widely available and for everyone to use. Next to a (generalized) function for estimating damages based on raster data, it also includes a damage assessment function using vector land-use data.

Even though the method is initially developed for flood damage assessments, it can calculate damages for any hazard for which you just require a fragility curve (i.e. a one-dimensional relation).


  1. Open the python environment in your command prompt or bash in which you want to install this package.
  2. Type pip install damagescanner and it should install itself into your python environment.
  3. Now you can import the package like any other package!


  1. Clone the repository or download the package on your computer and extract the folder.
  2. Go to the DamageScanner folder in your command prompt or bash.
  3. Type python setup.py install and it should install itself into your python environment.
  4. Now you can import the package like any other package!


  • Make inputs for both the RasterScanner and VectorScanner more flexible. Catch common errors.
  • Make plotting functions more flexible.
  • Develop automated damage assessments using OpenStreetMap data.

How to cite:

If you use the DamageScanner in your work, please cite the package directly:

Here's an example BibTeX entry:

          author       = {Koks, E.E.},
          title        = {DamageScanner: Python tool for disaster damage assessments},
          year         = 2019,
          doi          = {10.5281/zenodo.2551015},
          url          = {http://doi.org/10.5281/zenodo.2551015}


Copyright (C) 2019 Elco Koks. All versions released under the MIT license.