Application of TELUM by the Pikes Peak, Colorado, Area Council of Governments

Abstract

For U.S. metropolitan planning organizations (MPOs), obtaining, preparing, and validating socioeconomic forecasts are fundamental tasks to ensure that logical, consistent, and approved population and employment data are provided to the travel demand models. This process is enhanced if the MPO includes both transportation and land use inputs into the forecast process. To fulfill these desires, the Pikes Peak Area Council of Governments (the MPO in Colorado Springs, Colorado) decided to use TELUM–-transportation, economic, and land use model software–-to conduct the land use forecasting task. TELUM was developed by Stephen Putman and the New Jersey Institute of Technology (NJIT) as part of the transportation, economic, and land use system sponsored by FHWA. With assistance from NJIT, MPO staff serving this 500,000-plus person region calibrated the land use model for the 2000 to 2005 period and then used TELUM to produce land use forecasts for six 5-year increments between 2005 and 2035. The Colorado Springs region has a unique character, including a workforce that is 11% active military personnel, a diverse employment profile including high-tech manufacturing and a large recreation-based workforce, and a growing retiree population. Additionally, the MPO area includes a dense urban area, large exurban developments, rugged mountain areas, and frontier grasslands, all of which challenged the technical staff that worked on model development. The technical and policy insights and lessons learned from the TELUM application in Colorado Springs have transferable value for all sizes of MPOs faced with forecasting development and transportation.

An iterative approach to an integrated land use and transportation planning tool for small urban areas

“…ITLUP and TELUM are gravity-based integrated urban models that have been deployed in many urban areas [1][2][3][4]. It assumes that the subject area is a closed system, i.e., most jobs in the study area are held by residents of the area; and most workers from local house-holds work in the same area.…”

Accuracy of Zonal Socioeconomic Forecasts for Travel Demand Modeling: Retrospective Case Study

“…Historical data, control totals, and local knowledge are used by all regions. More complex approaches include a multizonal socioeconomic simulation model (1), spatially oriented land use models that predict disaggregated employment and population as a function of transportation and economic conditions (2), and rule-based models that can test land use policies (3). Ensuring that socioeconomic forecasts are reasonable is an essential step for travel demand modeling (4).…”