simcenter-pyncoda-fork 3.0.0.post2

A Python package for generating probabilistic household and population data for community resilience analysis

Repository Title: Intersect Community Data (pyncoda)

Description

People are the most important part of community resilience planning. However, models for community resilience planning tend to focus on buildings and infrastructure. This repository provides a solution that connects people to buildings for community resilience models. The housing unit inventory method transforms aggregated population data into disaggregated housing unit data that includes occupied and vacant housing unit characteristics. Detailed household characteristics include size, race, ethnicity, income, group quarters type, vacancy type and census block. Applications use the housing unit allocation method to assign the housing unit inventory to structures within each census block through a reproducible and randomized process. The benefits of the housing unit inventory include community resilience statistics that intersect detailed population characteristics with hazard impacts on infrastructure; uncertainty propagation; and a means to identify gaps in infrastructure data such as limited building data. This repository includes all of the python code files. Python is an open source programming language and the code files provide future users with the tools to generate a 2010 housing unit inventory for any county in the United States. Applications of the method are reproducible in IN-CORE (Interdependent Networked Community Resilience Modeling Environment).

License

Output Data License: Open Data Commons Attribution License (https://opendatacommons.org/licenses/by/summary/)

Program Code: Mozilla Public License Version 2.0 (https://www.mozilla.org/en-US/MPL/2.0/)

Setup Environment

1. Install Anaconda
2. Install VS Code
3. Download Repository
4. See environment.yml file for dependencies
5. Run the primary Jupyter Notebook in the main folder

More Details

For more details on the following refer to the Admin Folder

• Acknowledgements
• Census Data Terms of Use
• Directory Design
• File Name Plan
• Funding Sources
• Related Works