New version of UrbanSim, a tool for modeling metropolitan real estate markets
Detailed documentation for UrbanSim is now available.
Click here for installation instructions.
Let us know what you are working on or if you think you have a great use case
by tweeting us at @urbansim or post on the UrbanSim forum.
UrbanSim (http://www.urbansim.com) is a model system for analyzing urban development. It is an open source platform that has been continuously refined and distributed for planning applications around the world for over 15 years. Part of the evolution of the platform is the necessary process of re-engineering the code to take advantage of new developments in computational libraries and infrastructure. We implemented UrbanSim initially in Java in the late 1990's, and by 2005 determined that it was time to re-implement it in Python, and created the Open Platform for Urban Simulation (OPUS) software implementation at that time. Now, almost a decade later, it is time again to revisit the implementation to take advantage of an amazing amount of innovation in the scientific computing community. The new implementation is hosted on this GitHub site, and maintained by UrbanSim Inc. and a growing community of contributors.
This new code base is a streamlined complete re-implementation of the longstanding UrbanSim project aimed at reducing the complexity of using the UrbanSim methodology. Redesigned from the ground up, the new library is trivial to install, the development process is made transparent via this GitHub site, and exhaustive documentation has been created in the hopes of making modeling much more widely accessible to planners and new modelers.
We lean heavily on the PyData community to make our work easier - Pandas, IPython, and statsmodels are ubiquitous in this work. These Python libraries essentially replace the UrbanSim Dataset class, tools to read and write from other storage, and some of the statistical estimation previously implemented by UrbanSim.
This makes our task easier as we can focus on urban modeling and leave the infrastructure to the wider Python community. The Pandas library is the core of the new UrbanSim, which is an extremely popular data manipulation library with a large community providing support and a very helpful book.
We have now converted a full set of UrbanSim models to the new framework, and have running applications for the Paris, Albuquerque, Denver, Bay Area, and Detroit regions. We have implemented a complete set of hedonic price models, location choice models, relocation and transition models, as well as a new real estate development model using proforma analysis.
We do strongly recommend that you contact the team at www.urbansim.com about your project to make sure you can get support when you need it, and know what you are getting into. For major applied projects, professional support is highly recommended.
Please report any bugs you encounter via GitHub Issues.
If you have improvements or new features you would like to see in UrbanSim:
- Open a feature request via GitHub Issues.
- See our code contribution instructions here.
- Contribute your code from a fork or branch by using a Pull Request and request a review so it can be considered as an addition to the codebase.
A selection of academic literature on UrbanSim can be found here.