Master Transportation Plan Task 4: Gap Analysis and Needs Network
• Trip Density : NCTCOG OD data by TAZ for trips made during the 2023 morning peak travel period was analyzed to better understand travel patterns in the study area. This trip data was then aggregated to count the total number of trips generated and received in each analysis district. A total district trip density was then calculated by dividing the total number of trips by the district land area. • Land Use : This layer provides an understanding of the existing built and planned market areas. This involved classifying the potential of areas by synthesizing data regarding current and future land use, existing zoning, and form-based code areas. The zoning and land use datasets were classified by type for their prescribed density allowances. The change in development density, projected through changes from zoning to the future land use, indicates areas pre-determined by the city to be supportive of higher-density development, ultimately showing a desire for greater transportation networks in support of the growing activity. Further encapsulating the city’s target for urban growth are the growth centers and urban villages, which were incorporated into land use classifications. • Infrastructure Proximity : The extraterritorial jurisdiction (ETJ) is a legally defined area of land outside Fort Worth’s limits, over which the city can regulate some activities through agreement with adjacent counties. The TSI includes the ETJ as a factor of infrastructure capacity and thus, is an indication for the need of future transportation development. The proximity of the ETJs is accounted for in the scoring of this layer. The analysis district scores are delineated by the adjacency to municipal city boundaries. The extent at which an ETJ is adjacent to a city boundary indicates their overall proximity to city infrastructure and future transference to city- based infrastructure through annexation. Districts with more coincidence to the city boundaries score higher for their proximity to infrastructure tie-ins. • Transportation Network : As an index targeting to understand transportation, the transportation step is the most intensive. It is crucial to understand the capacity for the existing transportation network in different areas and the level of connectivity for the given modes. The TSI focuses separately on three modes of travel for the study area, including transit, active transportation, and private vehicles. Transit effectiveness was measured by the existing ridership numbers from both Trinity Metro and Texas Rail. Active transportation is assessed based on a city’s primary urban development pattern as understood by its intersection density, as shorter block length typically means more blocks, which in turn lead to smaller parcels and higher population density. These compounding factors are strong predictors of active transportation activity. Private vehicles were accounted for in two sub-metrics: street connectivity based on the link (roads) to nodes (intersection) ratios and the V/C ratio as a sub-metric to show how intense the use of the network is in a particular segment of roadway. These variables are represented equally in this category of analysis and are combined into an aggregate score of one to five, based on the prevalence and future growth of the network. • Environmental : Environmental barriers can be significant determinant for development and transportation connectivity in a specific area or community. While natural environments provide
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