Three Methods for Synthesizing Base-Year Built Form for Integrated Land Use-Transport Models

Abraham, John; Weidner, Tara; Gliebe, John; Willison, C.; Hunt, John Douglas

doi:10.3141/1902-14

Cited by 12 publications

(13 citation statements)

References 5 publications

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“…Very limited research has been done to improve the state-of-the-art estimation of baseyear floorspace inputs for planning models. In a study by Abraham et al (2005), three methods of synthesizing base-year floorspace data are developed and tested. Their general algorithm consists of two main sections which develop a floorspace inventory and then assign the floorspace to parcels of land.…”

Section: Review Of Related Studiesmentioning

confidence: 99%

“…However, data, such as employment, household, and floorspace quantity by category and by zone, are necessary inputs for every ILUTM. Floorspace quantity is a type of information that is not readily available as census data (Abraham et al, 2005;Pflum, 2004). Obtaining floorspace data is simplified in most ILUTM applications by transforming household and employment census data into floorspace via conversion factors (Walker et al, 1994).…”

Section: Introductionmentioning

confidence: 99%

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An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach

Shiravi

Zhong

Beykaei

et al. 2015

Environ Plann B Plann Des

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A literature review indicates that most integrated land-use transport models (ILUTMs) estimate base-year floorspace data according to limited population and employment data provided by the census and, in general, the accuracy is unknown. This paper assesses the utility of airborne Light Detection And Ranging (LiDAR) technology as a valuable tool for extracting base-year floorspace using the following three datasets: a geographic vector building footprint layer, a LiDAR dataset, and field survey data for the south side of the City of Fredericton, Canada. It is found through a statistical comparison with the results from the field survey that LiDAR data can be used to extract buildings and estimate floorspace with a good degree of accuracy. Further, two base-year floorspace estimation methods, one based on the LiDAR data and the other on census data, are compared. In general, our results show that the traditional census-based approach may not be reliable for estimating base-year floorspace. Using the extracted floorspace from the LiDAR data as the basis, for residential floorspace estimation the average absolute percentage errors (APE) of the census-based approach is 16% and the 95th percentile APE is 34%. On the other hand, for employment floorspace estimation, the accuracy of the census-based approach is even lower, with average errors of 50% or higher and the 95th percentile APEs as high as 163% up to 400% for several land-use categories. All the above statistics indicate that the traditional census-based approach is unreliable and inaccurate for modelers and planners to prepare their base-year floorspace, and therefore suggest a better way be explored. Study results clearly show the utility of LiDAR data and imply that it can be used as a powerful add-on for ILUTMs in general.

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Section: Review Of Related Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach

Shiravi

Zhong

Beykaei

et al. 2015

Environ Plann B Plann Des

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show abstract

“…Abraham et al (2005) provide examples of rule-based data imputation, in which the authors assign floor space to geography to meet pre-determined demand. IPF is the underlying algorithm for population synthesizers that are commonly used in transportation demand modeling (See Müller and Axhausen, 2011 for a recent review of popular population synthesizers).…”

Section: Data Imputation and Synthesismentioning

confidence: 99%

“…These domains are as varied as cleaning of web data, detecting fraud in credit data, reconciling medical records, mining the vast streams of email and web content for targeted advertising, and many others (See, for example, Hu et al, 2012). To date, most attempts to tackle the problem in the modeling communities (Abraham et al, 2009(Abraham et al, , 2005; for example, Waddell et al, 2005) are tied to a specific model system and a chosen study area. Few systematic efforts have applied these technological advances to produce re-usable tools in the problem domain of land use and transportation data.…”

Section: Introductionmentioning

confidence: 99%

“…The data development for the UrbanSim application for the Puget Sound region (Waddell et al, 2005) exemplifies such an approach, in which data from original sources are processed into data tables for UrbanSim. Abraham et al (2005) tested three rule-based approaches to synthesize realestate inventory data for modeling applications according to data available in three different regions. Each approach is tied to the specific model requirements and geographical resolution (TAZ, parcel, or gridcell) specified for one of the regions.…”

Section: Introductionmentioning

confidence: 99%

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Continuous Data Integration for Land Use and Transportation Planning and Modeling

Wang

Kim²

2014

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There is an urgent need for improved models that address the interdependencies between land use and transportation, and considerable new work is underway to develop such models in Oregon and elsewhere. These models and planning practices to integrate land use into the process, however, require the integration of massive amounts of land use data that is messy and incomplete. There have been considerable advances in the treatment of such data problems in other domains, drawing on data mining and machine-learning techniques to address issues in various domains. To date, however, little systematic effort has applied these technological advances to the problem domain of land use and transportation data. Experience suggests that as much as 70% of the total effort in developing integrated land use and transportation models is directly or indirectly associated with data development, integration and cleaning, yet there is remarkably little systematic research focused on the development of reusable methods and tools to support this problem domain.In coordination with an ongoing project of similar theme funded by University of California Transportation Center (UCTC), this project will focus on bringing interdisciplinary methods to develop land use datasets for integrated land use and transportation planning and modeling, with special attention on preserving temporal dimension of the data and monitoring data quality through indicators. Utilizing statistics and machinelearning techniques, we will develop reusable tools that will create a harmonized and coherent land use database from various public and private sources. These tools will be made available to the public and can be used 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. All of the resulting data, with the exception of proprietary or confidential input data where there is no viable alternative, would be public and reusable for planning and research.17.

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Household Behaviour in the Oregon2 Model

Hunt

Abraham²,

Weidner

2010

Residential Location Choice

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Three Methods for Synthesizing Base-Year Built Form for Integrated Land Use-Transport Models

Cited by 12 publications

References 5 publications

An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach

An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach

Continuous Data Integration for Land Use and Transportation Planning and Modeling

Household Behaviour in the Oregon2 Model

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