Neighborhood Adaptive Tissues for Urban Resilience Futures (naturf
) is an open-source geospatial Python package that calculates and compiles urban building parameters to be input to the Weather Research and Forecasting model (WRF).
naturf
was created to:
- Calculate 132 urban parameters based on building footprints and height,
- Compile the parameters at sub-kilometer resolutions into binary files,
- Prepare binary files to be fed into WRF to understand the effect of building morphology on the urban microclimate.
pip install naturf
Run naturf
! Check out the naturf
ipynb Quickstarter or the naturf
Python Quickstarter.
Our user guide provides in-depth information on the key concepts of naturf
with useful background information and explanation.
Whether you find a typo in the documentation, find a bug, or want to develop functionality that you think will make naturf
more robust, you are welcome to contribute! See our Contribution Guidelines
The reference guide contains a detailed description of the naturf
API. The reference describes how the methods work and which parameters can be used. It assumes that you have an understanding of the key concepts. See API Reference
To get started on development, install the pre-commit hooks to format code.
First install pre-commit
.
Then install the hooks within the repo:
$ cd /PATH/TO/NATURF
$ pre-commit install
Allen-Dumas, Melissa R., Sweet-Breu, Levi, Rexer, Emily, and Vernon, Chris. Neighborhood Adaptive Tissues for Urban Resilience Futures (NATURF) V1.0. Computer Software. https://github.com/IMMM-SFA/naturf. USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS). 03 Jun. 2024. Web. doi:10.11578/dc.20240531.1.
Sweet-Breu, L., & Allen-Dumas, M. (2024). Urban Parameters LA County 100m (Version v1) [Data set]. MSD-LIVE Data Repository. https://doi.org/10.57931/2349436
Allen-Dumas M ; Sweet-Breu L (2024): Urban Parameters Maricopa County 100m Grid Spacing. Southwest Urban Corridor Integrated Field Laboratory (SW-IFL), ESS-DIVE repository. Dataset. ess-dive-b6200929fa5b268-20240604T184443135 accessed via https://data.ess-dive.lbl.gov/datasets/ess-dive-b6200929fa5b268-20240604T184443135 on 2024-06-04.
OpenDataDC (2021) Open Data DC. URL https://opendata.dc.gov/datasets