The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (NATURF) is a Python workflow that generates data readable by the Weather Research and Forecasting (WRF) model. The NATURF Python modules use shapefiles containing building footprint and height data as input to calculate 132 building parameters at any resolution and converts the parameters into a binary file format.
Project description
naturf
naturf
(Neighborhood Adaptive Tissues for Urban Resilience Futures) is an open-source geospatial Python package for calculating urban building parameters to be compiled and input to the Weather Research and Forecasting model (WRF).
Purpose
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.
Install naturf
pip install naturf
Check out a quickstart tutorial to run naturf
Run naturf
using the quickstart tutorial: naturf
Quickstarter
Getting started
New to naturf
? Get familiar with what naturf
is all about in our Getting Started
User guide
Our user guide provides in-depth information on the key concepts of naturf
with useful background information and explanation. See our User Guide
Contributing to naturf
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
API reference
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
Developer Setup
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
Code citation
Allen-Dumas, Melissa Ree, Sweet-Breu, Levi, Seals, Matthew, Berres, Andy, Vernon, Chris R., Rexer, Emily, and USDOE Office of Science. NATURF. Computer software. https://www.osti.gov//servlets/purl/1879628. Vers. 0. USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division. 31 Aug. 2022. Web. doi:10.11578/dc.20220803.4.
Sample data citation
OpenDataDC (2021) Open Data DC. URL https://opendata.dc.gov/datasets
Project details
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