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UrbanSim is a platform for building statistical models of cities and regions. These models help forecast long-range patterns in real estate development, demographics, and related outcomes, under various policy scenarios.
This urbansim Python library is a core component. It contains tools for statistical estimation and simulation; domain-specific logic about housing markets, household relocation, and other processes; and frameworks and utilities for assembling a model.
Operational UrbanSim models begin with detailed data about a particular region, and then estimate and validate a system of interconnected model components. Full models draw on a number of libraries: not just urbansim, but also Orca <https://github.com/UDST/orca> for task orchestration, Synthpop <https://github.com/UDST/synthpop> for population synthesis, Pandana <https://github.com/UDST/pandana> for network analysis, and so on. Collectively, these make up the Urban Data Science Toolkit <https://github.com/UDST> (UDST).
UrbanSim models are used by public agencies, consultancies, and researchers in dozens of cities around the U.S. and world. The core platform is open source, but many operational models make use of additional cloud-hosted model building and visualization tools provided by UrbanSim Inc. <https://urbansim.com>__
An Introduction to UrbanSim <https://udst.github.io/urbansim/gettingstarted.html#a-gentle-introduction-to-urbansim>__
UrbanSim for San Francisco: An example implementation <https://github.com/UDST/sanfran_urbansim>__
UrbanSim Inc. <https://urbansim.com>__
pip install urbansim
conda install urbansim --channel conda-forge
Getting started <https://udst.github.io/urbansim/gettingstarted.html>__
Full documentation <https://udst.github.io/urbansim/>__
Other UDST <https://docs.udst.org>__ libraries
Documentation for UrbanCanvas <https://cloud.urbansim.com/docs/>__, the UrbanSim cloud platform