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 Storm

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Python toolkit to do direct damage assessments for natural hazards

README.md

DamageScanner: direct damage assessments for natural hazards

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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

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

  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!

OR:

  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!

Create testing environment

Recommended option is to use a miniconda
environment to work in for this project, relying on conda to handle some of the
trickier library dependencies.


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

# Create a conda environment for the project and install packages
conda env create -f environment.yml
activate ds_env

Documentation

Documentation Status

Please refer to the ReadTheDocs 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.},
          title        = {DamageScanner: Python tool for natural hazard damage assessments},
          year         = 2022,
          doi          = {10.5281/zenodo.2551015},
          url          = {http://doi.org/10.5281/zenodo.2551015}
    }

License

Copyright (C) 2022 Elco Koks. All versions released under the MIT license.


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Committers metadata

Last synced: 9 days ago

Total Commits: 211
Total Committers: 7
Avg Commits per committer: 30.143
Development Distribution Score (DDS): 0.128

Commits in past year: 11
Committers in past year: 1
Avg Commits per committer in past year: 11.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
elco.k e****s@g****m 184
Jens de Bruijn j****n@o****m 11
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

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Issue and Pull Request metadata

Last synced: about 11 hours ago

Total issues: 26
Total pull requests: 21
Average time to close issues: about 1 year
Average time to close pull requests: about 1 month
Total issue authors: 6
Total pull request authors: 5
Average comments per issue: 0.42
Average comments per pull request: 0.29
Merged pull request: 14
Bot issues: 0
Bot pull requests: 9

Past year issues: 1
Past year pull requests: 3
Past year average time to close issues: 2 months
Past year average time to close pull requests: 6 days
Past year issue authors: 1
Past year pull request authors: 1
Past year average comments per issue: 3.0
Past year average comments per pull request: 0.0
Past year merged pull request: 1
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 (21)
  • czor847 (1)
  • jensdebruijn (1)
  • rmmilewi (1)
  • TBuskop (1)
  • couasnonanais (1)

Top Pull Request Authors

  • dependabot[bot] (9)
  • jensdebruijn (5)
  • couasnonanais (3)
  • ElcoK (3)
  • ConnectedSystems (1)

Top Issue Labels

  • enhancement (7)
  • good first issue (1)

Top Pull Request Labels

  • dependencies (9)

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: 5.37989735354046