DamageScanner: direct damage assessments for natural hazards

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

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.

Background

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.

Installation

To use DamageScanner in your project:

Using uv (recommended)

uv add damagescanner

Using pip

pip install damagescanner

Development & Testing

To set up a local environment for development or to run tests:

Using uv (recommended)

uv is an extremely fast Python package manager and is the preferred way to set up the development environment.

# Clone the repository
git clone https://github.com/VU-IVM/DamageScanner.git
cd DamageScanner

# Create a virtual environment and install all optional dependencies
uv sync --all-groups

Using Miniconda

If you prefer Miniconda, use the provided environment.yml file:

# Add conda-forge channel for extra packages
conda config --add channels conda-forge

# Create environment and activate
conda env create -f environment.yml
conda activate ds-test

Documentation

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

How to cite

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

• Koks. E.E. & de Bruijn, J. (2026). DamageScanner: Python tool for natural hazard damage assessments. Zenodo. http://doi.org/10.5281/zenodo.2551015

Here's an example BibTeX entry:

@misc{damagescannerPython,
      author       = {Koks, E.E. and {de Bruijn}, J.},
      title        = {DamageScanner: Python tool for natural hazard damage assessments},
      year         = 2026,
      doi          = {10.5281/zenodo.2551015},
      url          = {http://doi.org/10.5281/zenodo.2551015}
}

License

Copyright (C) 2026 Elco Koks & Jens de Bruijn. All versions released under the MIT license.