Case Study: New Mexico Mid-Region Council of Governments (MRCOG)

What was the organization using before UrbanSim?

Before New Mexico’s Mid-Region Council of Governments (MRCOG) began working with UrbanSim in 2011, they were using a homegrown land use model called LAM which they built alongside Maricopa Association of Governments in Phoenix. LAM was an incremental land use tool which employed the velocity curve concept to distribute growth across the region, assuming growth follows a certain velocity. It fell short, however, due to its design as an incremental model, which did not allow existing households and jobs to relocate, a key aspect of the active change in neighborhoods and employment centers, that have dynamic movement into and out of the community over time, leading to cycles of growth, decline, and redevelopment. In effect, the LAM model was keeping populations in every zone constant except those which were expected to grow, showing heightened growth in the hinterland as opposed to densification and infill development in existing centers. Due to this limitation, MRCOG’s team began searching for a tool which could better simulate reality. They were searching for a tool which could simulate, for example, the dynamic movement of households and jobs and the processes of neighborhood change and redevelopment.

How did your work change after you started using UrbanSim?

When MRCOG adopted the open source UrbanSim model, they used the modeling software for their metropolitan transportation plan (MTP). It is primarily used to forecast urban development patterns, which are used as inputs to their travel demand model. This approach allows MRCOG to understand future priorities for transportation investments. This modeling framework is “respected and touted by our member governments. It’s really nice to have this modeling environment to substantiate where we put our money.”

A  highlight of MRCOG’s use of UrbanSim is a climate change scenario planning project which arose out of MRCOG’s 2040 Futures MTP, adopted in April 2015. From their work on the 2040 Futures MTP, they were awarded a grant by the US Department of Transportation’s Volpe Center which was funded by numerous national environmental agencies including the National Parks Service and the Bureau of Land Management. This award gave MRCOG additional access to technical services to use the scenarios employed in their 2040 Futures MTP and evaluate them in the context of climate change. The goal was to develop strategies to reduce transportation-related greenhouse gas emissions through changes to land use plans and policies as well as transportation system investments.

A set of three scenarios were developed using UrbanSim: a ‘trend scenario’ which represents current land use policies and historical development patterns; an ‘emerging lifestyles’ scenario which promoted infill, transit-oriented development, and mixed development; and a ‘jobs/housing balance’ scenario which focused on developing housing near employment centers and vice versa.

The organization’s preliminary evaluation of these scenarios found that the two alternative scenarios (‘emerging lifestyles’ and ‘jobs/housing balance’ scenarios) performed better than the trend scenario, but the differences between the scenarios were small. Through a series of community workshops and scenario planning iterations, MRCOG developed a final set of scenarios which responded to the community’s desire for even more reductions in travel and emissions and more concentrated infill and mixed-use development in priority centers than previous iterations had utilized. The ‘emerging lifestyles’ and ‘jobs/housing balance’ scenarios were combined into one ‘target’ scenario and compared to the baseline ‘trend’ scenario (Figures 1 & 2). A few clear distinctions between the trend scenario and this final alternative scenario may be drawn. The alternative scenario generated by UrbanSim was projected to achieve several key outcomes:

         Consume 30% less new land,

         Result in water savings,

         Place less development in environmentally sensitive areas

(i.e. floodplains and wildfire risk areas),

         Reduce driving, congestion, and GHG emissions,

         Increase transit access above the trend scenario’s outputs.

In this climate change scenario planning project, zoning and developer incentive indicators from the UrbanSim model were used to forecast the type and intensity of development on each parcel of the metropolitan area, along with changes in population and employment over time. The UrbanSim output was then used as inputs to the regional travel demand model for each scenario. Tying transportation, climate change, and land use planning together, this project sought to identify how patterns of development would lead to differences in  vehicle miles traveled, the primary environmental performance metric of interest. UrbanSim was “central to the scope of trying to simulate different mitigation measures,” and MRCOG was excited by the heightened stakeholder interest and support which came from the effort. Lastly, this more realistic approach to modeling allowed MRCOG and local municipalities to more adequately plan for utility infrastructure based on the region’s distributed demand. UrbanSim forecasts were customized for member governments, so they could anticipate the number of future residents in their municipalities and adjust utility rates accordingly.

Why did your Team Transition to UrbanSim Scenario Modeling?

MRCOG is currently in the process of adopting the scenario modeling solution for their region, and its continuous use will be able to provide additional assistance to the member governments. The MRCOG team transitioned for numerous reasons, including the following:

Built-In Visualizations: The pre-made indicator charts and visuals allow them to quickly evaluate and compare scenario results.
Manage Runs: Their team can start multiple runs at once, better track runs, and view how each run differentiates from another.

Ease of Use: UrbanCanvas is easier to use than the open source UrbanSim model because a staff member without Python experience can build and run scenarios.

Speed of Computation: The cloud platform performs tasks much more quickly than running the open source model locally on their machines.
Avoid Manual Processing: By skipping the time intensive process of exporting outputs to CSV, joining datasets,
and importing it into ArcGIS, the MRCOG has found that UrbanCanvas’ ESRI backed platform allows them to save a significant amount of manual processing time at the end of each run.

How Does UrbanSim Integrate with Other Tools?

In addition to UrbanSim’s UrbanCanvas cloud platform, MRCOG uses ESRI ArcGIS, Cube’s four-step travel model, and a Trans-sight REMI macroeconomic model. Together these platforms create a complete land use, transportation, and economic development modeling toolkit.