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erexer committed Sep 24, 2024
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8 changes: 4 additions & 4 deletions docs/source/index.rst
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**Useful links**:
`Source Repository <https://github.com/immm-sfa/naturf>`_ |
`Issues & Ideas <https://github.com/immm-sfa/naturf/issues>`_ |
`Interactive Quickstarter <quickstarter.rst>`_
`Interactive Quickstarter <https://naturf.msdlive.org/>`_

**naturf** 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). **naturf** was created to:
**naturf** 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). **naturf** was created to:

1) Calculate 132 urban parameters based on building footprints and height,

Expand All @@ -34,9 +34,9 @@ The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (**naturf**)
:img-top: _static/index_quickstarter.svg
:text-align: center

New to **naturf**? Follow the quickstarter for a quick start.
New to **naturf**? Run the quickstarter in your browser.

.. button-ref:: quickstarter
.. button-link:: https://naturf.msdlive.org/
:click-parent:
:color: primary
:expand:
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7 changes: 5 additions & 2 deletions docs/source/quickstarter.rst
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Quickstarter
============

.. note::
`Run the interactive Quickstarter in browser! <https://naturf.msdlive.org/>`_


Continue below to run `naturf` using a python file.

Input data
----------

The only input data required for `naturf` is a shapefile with building footprints and height data. There should be a field with a unique ID for each building the shapefile, and it should be in a projected coordinate system such as Alber Equal Area Conic. For input to the Weather Research and Forecasting model (WRF), the computed parameters for each building will be projected into WGS 84.

Either run the ipynb `quickstarter <https://github.com/IMMM-SFA/naturf/blob/main/notebooks/quickstarter.ipynb>`_, or continue below to run `naturf` using a python file.

.. note::
Users need to `download graphviz <https://graphviz.org/download/>`_ to visualize the Directed Acyclic Graph (DAG).

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6 changes: 4 additions & 2 deletions notebooks/quickstarter.ipynb
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"source": [
"# `naturf` Quickstarter\n",
"\n",
"The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (`naturf`) is a Python workflow that generates files readable by the Weather Research and Forecasting (WRF) model. `naturf` uses *geopandas* and *hamilton* to calculate 132 building parameters from shapefiles with building footprint and height information. These parameters can be collected and used in many formats, and the primary output is a binary file configured for input to WRF. This workflow is a flexible adaptation of the National/World Urban Database and Access Portal Tool (NUDAPT/WUDAPT) that can be used with any study area at any spatial resolution. The climate modeling community and urban planners can identify the effects of building/neighborhood morphology on the microclimate using the urban parameters and WRF-readable files produced by `naturf`. The source code for `naturf` can be found on [GitHub](https://github.com/IMMM-SFA/naturf/tree/main), and more information on the urban parameters calculated can be found in the [documentation](https://immm-sfa.github.io/naturf/). Cases 1 and 2 below illustrate using *hamilton* to pull different outputs from `naturf` using example data. Case 3 shows how to use `naturf` with user data."
"The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (`naturf`) is a Python workflow that generates files readable by the Weather Research and Forecasting (WRF) model. `naturf` uses *geopandas* and *hamilton* to calculate 132 building parameters from shapefiles with building footprint and height information. These parameters can be collected and used in many formats, and the primary output is a binary file configured for input to WRF. This workflow is a flexible adaptation of the National/World Urban Database and Access Portal Tool (NUDAPT/WUDAPT) that can be used with any study area at any spatial resolution. The climate modeling community and urban planners can identify the effects of building/neighborhood morphology on the microclimate using the urban parameters and WRF-readable files produced by `naturf`. The source code for `naturf` can be found on [GitHub](https://github.com/IMMM-SFA/naturf/tree/main), and more information on the urban parameters calculated can be found in the [documentation](https://immm-sfa.github.io/naturf/). Cases 1 and 2 below illustrate using *hamilton* to pull different outputs from `naturf` using example data. Case 3 shows how to use `naturf` with user data.\n",
"\n",
"> **_NOTE:_** [Run this quickstarter interactively in browser!](https://naturf.msdlive.org)"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.19"
"version": "3.12.2"
}
},
"nbformat": 4,
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