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One of the goals of constructing and operating an extensive rail transit system in the Denver metro region since 1994 has been growth and development of land use along the rail transit system. This paper analyzes the trend of land use growth and development around the rail transit system mostly from 2000 to 2010. Primarily land parcel data collected from the assessor's office of several counties in the metro region have been used to determine change in the amount of different types of land use namely commercial, mixed, industrial, multi-family residential and single-family residential near and far from the rail transit system. Change has been analyzed in terms of total square footage of the building areas as well as land use density. Statistical significance tests (Wilcoxon/Kruskal–Wallis test) have been conducted to understand if the amount of change taking place near the rail transit system is greater than away from the system. The growth of commercial land use was significantly higher near the rail transit system. More growth in multi-family residential land use has also occurred near the rail transit system, but was not significantly greater than areas away from the system. Single-family residential land use has noticeably increased in places away from the rail transit system. The other types of land use have not shown any consistent pattern in their growth either near or away from the system. Overall, a noticeable amount of land use change, especially commercial land use, has taken place around the rail transit system from 2000 to 2010. However, this change in land use cannot necessarily be attributed to the construction and operation of the rail transit system. Other factors may have influenced the growth of land use around the rail transit system more than the presence of the rail transit system itself. [ABSTRACT FROM AUTHOR]

Abstract: Among the reasons the light rail system in Denver has been built is to reduce traffic congestion. A temporal and spatial analysis of Vehicle Miles Traveled (VMT) data from 1992 to 2008 on the highways in Denver has been conducted to determine if that objective has been fulfilled after the initial light rail service began in 1994. Temporal analysis provides an insight into the changes in the level of highway traffic before and after the opening of three segments (Central, Southwest, and Southeast Corridors) of the light rail system. This part of the analysis also compares the traffic levels of highways affected by light rail with those not affected by light rail. Spatial analysis examines whether the changes have taken place uniformly throughout all the highways, or whether they have been concentrated on particular highways. Results indicate that light rail has reduced level of traffic along some of the adjacent highways for a short period of time. Overall, the three light rail corridors in operation have succeeded in lowering the rate of increase in the level of traffic on highways within the rail transit influence zone as compared to highways outside the influence zone. [Copyright &y& Elsevier]

Since the 1980s, significant investments have been made in urban rail transit across the United States, particularly using light rail technology. Most of these light rail systems have been built in Sunbelt cities which no longer had legacy rail systems. As a result, they were constructed using a building blocks approach, being funded corridor by corridor. Most research, however, on urban rail performance has taken place at the system-wide level, leaving a significant gap at the level of the transit corridor. This research examined nineteen urban rail corridors in Denver, Salt Lake City, and Portland. A performance score was constructed for each corridor based upon ridership per mile, ridership growth, capital costs, and the cost of ongoing operations. These scores were then compared with the geographic profile of each corridor studied. Corridors in each city ranked high and low, with no city emerging as a clear frontrunner. More centrally-located corridors in each city registered the highest performance scores, while longer corridors in more peripheral locations had lower performance scores. Headways, population density, job density, walkability, and percentage renter occupied housing units were found to have a statistically significant relationship with high corridor performance, largely in line with previous studies, though median income, bus connections, and park and ride spaces were not found to increase performance in this study. [ABSTRACT FROM AUTHOR]

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship. [ABSTRACT FROM AUTHOR]