A GIS-Based Performance Measurement System for Assessing Transportation Sustainability and Community Livability

Sustainability and livability in transportation, as the concepts referring to the capability of transportation systems to maintain the well being of our society, have been widely accepted as the critical principles to improve quality of life and health of communities. The research developed a geographic information systems (GIS)-based performance measurement system for assessing the roles of transportation in achieving these goals. Using the City of Buffalo, New York as the case study, the authors collected various data and generated twenty sustainability and livability related performance measures (PMs), including the transportation attributes, land use measures, living condition indicators, and system-wide indices. The analysis on PMs derives several policy implications and suggestions. Lessons and challenges learnt from the PM development process were also summarized to help other relevant initiatives. The PMs, supporting database, case study and findings produced by the research are expected to help a wide range of audience such as policy makers, planners and transportation engineers to gain insights about the sustainability and livability oriented performance measurement. The land use information is found as an important input data for developing such a performance measurement system. However, it is often outdated and not sufficient to support sustainability and livability assessment practices. In this context, the authors also developed the methods to predict land use classes by taking advantage of frequently updated remote sensing data. The authors utilized the multinomial logistic regression, or called multinomial logit (MNL) models, for land use classification, whose great potentials have been overlooked in the field. In addition, the authors also suggest use transportation related attributes, such as the distances from a parcel of land to the nearest road or intersection, as the ancillary attributes to improve classification performance, in addition to spectral features collected by remote sensing. The MNL models were tested on the land use data collected in the City of Buffalo, New York. The best model achieves an average prediction accuracy of 83.7%. For the residential and commercial parcels, the prediction accuracy reaches up to 94.5%. In addition, the suggested transportation attributes were also found significant in discriminating land use classes.

• Record URL:
  http://www.utrc2.org/sites/default/files/Final-Report-A-GIS-Based-Performance-Measurement-System.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/32330
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  State University of New York, Buffalo

  Department of Civil, Structural and Environmental Engineering
  Buffalo, NY  United States  14260

  University Transportation Research Center

  City College of New York
  Marshak Hall, Suite 910, 160 Convent Avenue
  New York, NY  United States  10031

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Wang, Qian
  • Wang, Le
  • Tang, Shuai
  • Hu, Jinge
  • Chen, Xiao
  • Ji, Wenjie
• Publication Date: 2014-8-31

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; References; Tables;
• Pagination: 41p

Subject/Index Terms

• TRT Terms: Case studies; Communities; Evaluation and assessment; Geographic information systems; Land use; Performance measurement; Quality of life; Regression analysis; Remote sensing; Sustainable development
• Geographic Terms: Buffalo (New York)
• Subject Areas: Data and Information Technology; Environment; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01637829
• Record Type: Publication
• Contract Numbers: 49997-28-24; DTRT-12-G-UTC02
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Jun 8 2017 12:04PM