Although a wide variety of transportation data sets involve discrete values scattered across space and time, there are currently few techniques for properly analyzing such data. This paper describes a new dynamic spatial ordered probit (DSOP) model and demonstrates the model's use in a case of ozone concentration categories. With outputs of photochemical models for the Austin, Texas, region from a 24-h period, model parameters are estimated with Bayesian techniques. The results illuminate key relationships, many intuitive but generally obscured by complex upstream model systems. Through the use of 132 4- x 4-km surface grid cells as observational units, values that exhibit strong patterns of temporal autocorrelation but appear strikingly random in a spatial context (after controlling for local land cover, transportation, and temperature conditions) are found. Although transportation and land cover conditions appear to influence ozone levels, their effects are neither as instantaneous nor as practically significant as the influence of temperature. The DSOP model proposed in this paper is able to accommodate the unusual dynamics and spatial evolution of the ordered response categories that are inherent in ozone concentration data.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Application of Dynamic Spatial Ordered Probit Model


    Subtitle :

    Patterns of Ozone Concentration in Austin, Texas


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2009-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Accident Severity Analysis Using Ordered Probit Model

    Rifaat, S.M. | Online Contents | 2007


    Analyze Bus Delay Severity Using Ordered Probit Model

    Liu, X. / Chen, M. / Bachman, E. et al. | British Library Conference Proceedings | 2007


    Analyze Bus Delay Severity Using Ordered Probit Model

    Liu, Xiaobo / Chen, Mei / Bachman, Erin | ASCE | 2007


    Driver injury severity: an application of ordered probit models

    Kockelman, Kara Maria | Online Contents | 2002