Socio Economic And Land Use Projections By Traffic Zone PDF Download

Travel networks are the backbone of an economy. The urban structure relies heavily on transport systems to grow and interact with the environment. They play an important role in shaping the land use of a region as mobility is instrumental in the process of location choice for residential and non-residential developments. However, land use changes are also governed by economic, governmental and environmental factors besides accessibility and hence, they indirectly affect transport systems too. Therefore, the ability to predict interactions between future land use and social economy for travel demand forecasting is of tremendous significance from the planning perspective. Among widely applied land use models, UrbanSim is gaining edge over others, being an open source system that models changes in spatial characteristics of the households and jobs in accordance with changing travel accessibilities and land prices. It allows for land use change simulation at varied geographic resolutions at parcel level and zone level. While the parcel-level version has been the most widely used in planning for its capability of featuring location-based socioeconomic factors at a disaggregate level, its intense data requirements also pose a big challenge or an extreme difficulty to validation efforts in practice. The relatively less-implemented zone-version of UrbanSim simulates household and employment changes at an aggregated Traffic Analysis Zone (TAZ) level with a relatively lesser data demand. However, the zone version does not account for the land use effect into the modeling approach directly. Instead, it uses only zoning data in one of the input tables in order to calculate development capacities in zones. But such zoning plans are only regulations to preserve land use and are not exactly representative of the actual land use at a location. The aim of this study was to overcome this weakness of the zone-version of UrbanSim with lack of focus on spatial effect of land use changes on social economy of each TAZ. This was achieved by linking future land use forecast data with UrbanSim input, while a travel model is used to generate traffic feedback in evaluating the spatial allocation of forecasted jobs and households. This proof-of-concept study was performed with the target at work describing an effort of integrated land use and transportation modeling for the Hamilton County of Ohio through year 2020 using the data sets that were provided mainly from the Ohio-Kentucky-Indiana Regional Council of Governments (OKI), in the Greater Cincinnati area, Ohio. The land use forecasting analysis was carried out with IDRISI Taiga module, a GIS and image processing model that could be validated with the land use datasets available at most Metropolitan Planning Organizations (MPOs)' databases. A VISUM travel model was used for travel accessibility inputs.