Data

Tools

Indexes

Applications

Experiments

Open Sustainable Technology

DamageScanner

A Python toolkit for direct damage assessments for natural hazards.
https://github.com/vu-ivm/damagescanner

Category: Climate Change
Sub Category: Natural Hazard and Storms

Keywords from Contributors

hydrology

Last synced: about 2 hours ago
JSON representation

Repository metadata

Python toolkit to do direct damage assessments for natural hazards

README.md

DamageScanner: direct damage assessments for natural hazards

fair-software badge
github license badge
Tests
DOI
Documentation
PyPI version
PyPI - Downloads

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:

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.

Owner metadata

GitHub Events

Total
Last Year

Committers metadata

Last synced: 2 days ago

Total Commits: 328
Total Committers: 7
Avg Commits per committer: 46.857
Development Distribution Score (DDS): 0.22

Commits in past year: 89
Committers in past year: 2
Avg Commits per committer in past year: 44.5
Development Distribution Score (DDS) in past year: 0.494

Name Email Commits
Elco Koks 3****K 256
Jens de Bruijn 2****n 56
dependabot[bot] 4****] 5
Takuya Iwanaga t****i@g****m 4
Couasnon a****n@v****l 3
Anais Couasnon c****s@g****m 2
BenDickens b****s@z****m 2

Committer domains:

Issue and Pull Request metadata

Last synced: 14 days ago

Total issues: 11
Total pull requests: 18
Average time to close issues: 8 months
Average time to close pull requests: 3 months
Total issue authors: 3
Total pull request authors: 2
Average comments per issue: 0.64
Average comments per pull request: 0.22
Merged pull request: 9
Bot issues: 0
Bot pull requests: 9

Past year issues: 2
Past year pull requests: 3
Past year average time to close issues: N/A
Past year average time to close pull requests: about 2 months
Past year issue authors: 2
Past year pull request authors: 1
Past year average comments per issue: 0.0
Past year average comments per pull request: 0.0
Past year merged pull request: 2
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/vu-ivm/damagescanner

Top Issue Authors

  • ElcoK (9)
  • snirandjan (1)
  • jensdebruijn (1)

Top Pull Request Authors

  • jensdebruijn (9)
  • dependabot[bot] (9)

Top Issue Labels

  • enhancement (1)

Top Pull Request Labels

  • dependencies (9)

Package metadata

proxy.golang.org: github.com/VU-IVM/DamageScanner

proxy.golang.org: github.com/vu-ivm/damagescanner

pypi.org: damagescanner

Direct damage assessments for natural hazards

  • Homepage: https://github.com/VU-IVM/DamageScanner
  • Documentation: https://vu-ivm.github.io/DamageScanner/
  • Licenses: MIT License
  • Latest release: 1.0.1 (published 21 days ago)
  • Last Synced: 2026-03-24T00:01:07.371Z (2 days ago)
  • Versions: 34
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Downloads: 2,169 Last month
  • Rankings:
    • Dependent packages count: 10.082%
    • Dependent repos count: 11.564%
    • Forks count: 11.932%
    • Stargazers count: 13.909%
    • Average: 14.247%
    • Downloads: 23.747%
  • Maintainers (2)

Dependencies

.github/workflows/ci.yml actions
  • actions/checkout v3 composite
  • mamba-org/setup-micromamba v1 composite
.github/workflows/release.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
doc/environment.yml pypi
doc/requirements.in pypi
  • Sphinx >=5,<6
  • sphinx_rtd_theme *
doc/requirements.txt pypi
  • alabaster ==0.7.12
  • babel ==2.10.3
  • certifi ==2023.7.22
  • charset-normalizer ==2.1.0
  • docutils ==0.17.1
  • idna ==3.3
  • imagesize ==1.4.1
  • jinja2 ==3.1.2
  • markupsafe ==2.1.1
  • packaging ==21.3
  • pygments ==2.15.0
  • pyparsing ==3.0.9
  • pytz ==2022.1
  • requests ==2.31.0
  • snowballstemmer ==2.2.0
  • sphinx ==5.0.2
  • sphinx-rtd-theme ==1.0.0
  • sphinxcontrib-applehelp ==1.0.2
  • sphinxcontrib-devhelp ==1.0.2
  • sphinxcontrib-htmlhelp ==2.0.0
  • sphinxcontrib-jsmath ==1.0.1
  • sphinxcontrib-qthelp ==1.0.3
  • sphinxcontrib-serializinghtml ==1.1.5
  • urllib3 ==1.26.18
environment.yml pypi
  • osm-flex *
pyproject.toml pypi
  • geopandas *
  • matplotlib *
  • numpy *
  • osm-flex *
  • packaging *
  • pandas *
  • pyproj *
  • rasterio *
  • rioxarray *
  • shapely >= 2.0
  • tqdm *
  • xarray *

Score: 12.997069959298218