A NITC research project from Portland State University introduces a method of cleaning up land use data, for use in improved transportation models.

Transportation and land use are closely interdependent. Considerable work is underway, in Oregon and elsewhere, to develop models that integrate the two.

Planners creating these models often spend the bulk of their time preparing data on the various land uses. Many times the data, gathered from diverse sources, is incomplete and requires the planner to find missing information to fill in the gaps.

In fields outside of transportation, there have been considerable advances in techniques to do this. Data-mining and machine-learning techniques have been developed, for example, to systematically detect fraud in credit data, reconcile medical records and clean up information on the web.

In the transportation modeling community, by contrast, most efforts to tackle the problem are tied to a specific model system and a chosen study area. Few have produced reusable tools for processing land use data.

Liming Wang, lead investigator of the project Continuous Data Integration for Land Use and Transportation Planning and Modeling, offers such reusable tools.

Wang brought interdisciplinary methods to the development of land use datasets, in coordination with a similar project funded by the University of California Transportation Center.

Wang and his research team applied their methods to the Portland, Oregon metro area for a case study. They worked to develop a harmonized and coherent land use database, compiled from various public and private sources. The data structure, tools for data processing and quality monitoring, and documentation are available to the public on the project website.

Using this continuous approach, land use data can be managed and a public database can be maintained for use by cities, counties, metropolitan planning agencies, state agencies, universities or anyone else needing to develop a usable database for use in integrated planning and modeling.

For more details about the project and the statistical methods used, download the final report.