Assessing and integrating uncertainty into land-use forecasting

Hana Sevcikova; Mark Simonson; Michael Jensen

doi:10.5198/jtlu.2015.614

PDF

Published

2015-03-16

Issue

Vol. 8 No. 3 (2015)

Section

Articles

License

Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution-Noncommercial License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. 3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

How to Cite

Sevcikova, H., Simonson, M., & Jensen, M. (2015). Assessing and integrating uncertainty into land-use forecasting. Journal of Transport and Land Use, 8(3). https://doi.org/10.5198/jtlu.2015.614

Assessing and integrating uncertainty into land-use forecasting

Hana Sevcikova

Puget Sound Regional Council University of Washington

Mark Simonson

Puget Sound Regional Council

Michael Jensen

Puget Sound Regional Council

DOI: https://doi.org/10.5198/jtlu.2015.614

Keywords: Uncertainty, Land Use Forecast, Bayesian Melding, UrbanSim, Agent-based Models, PSRC

Abstract

Uncertainty in land use and transportation modeling has received increasing attention in the past few years. However, methods for quantifying uncertainty in such models are usually developed in an academic environment and in most cases do not reach users of official forecasts, such as planners and policymakers. In this paper, we describe the practical application of a methodology called Bayesian melding and its integration into the land-use forecast published by the Puget Sound Regional Council, a metropolitan planning organization. The method allows practitioners to assess uncertainty about forecasted quantities, such as households, population, and jobs, for each geographic unit. Users are provided with probability intervals around forecasts, which add value to model validation, scenario comparison, and external review and comment procedures. Practical issues such as how many runs to use or assessing uncertainty for aggregated regions are also discussed.

Journal of Transport and Land Use

Published

Issue

Section

License

How to Cite

Assessing and integrating uncertainty into land-use forecasting

Abstract

Current Issue