Effects of the Modifiable Areal Unit Problem on the Delineation of Traffic Analysis Zones

Transportation analysis is typically thought of as one kind of spatial analysis. A major point of departure in understanding problems in transportation analysis is the recognition that spatial analysis has some limitations associated with the discretization of space. Among them, modifiable areal units and boundary problems are directly or indirectly related to transportation planning and analysis through the design of traffic analysis zones (TAZs). The modifiable boundary and the scale issues should all be given specific attention during the specification of a TAZ because of the effects these factors exert on statistical and mathematical properties of spatial patterns (ie the modifiable areal unit problem—MAUP). The results obtained from the study of spatial data are not independent of the scale, and the aggregation effects are implicit in the choice of zonal boundaries. The delineation of zonal boundaries of TAZs has a direct impact on the reality and accuracy of the results obtained from transportation forecasting models. In this paper the MAUP effects on the TAZ definition and the transportation demand models are measured and analyzed using different grids (in size and in origin location). This analysis was developed by building an application integrated in commercial GIS software and by using a case study (Lisbon Metropolitan Area) to test its implementabiity and performance. The results reveal the conflict between statistical and geographic precision, and their relationship with the loss of information in the traffic assignment step of the transportation planning models.

[1]  Fred L. Mannering,et al.  Occurence, frequency, and duration of commuters' work-to-home departure delay , 1990 .

[2]  Alan T. Murray,et al.  Excess Commuting and the Modifiable Areal Unit Problem , 2002 .

[3]  David Wong,et al.  Research on the MAUP: old wine in a new bottle or real breakthrough? , 1996 .

[4]  Stan Openshaw,et al.  Designing zoning systems for flow data , 2000 .

[5]  C Ding.  The GIS-Based Human-Interactive TAZ Design Algorithm: Examining the Impacts of Data Aggregation on Transportation-Planning Analysis , 1998 .

[6]  M Batty,et al.  Spatial Aggregation in Gravity Models: 2. One-Dimensional Population Density Models , 1982, Environment & planning A.

[7]  F. Escobar,et al.  Hierarchical Spatial Reasoning theory and GIS technology applied to the automated delineation of administrative boundaries , 2002 .

[8]  Chengri Ding.  IMPACT ANALYSIS OF SPATIAL DATA AGGREGATION ON TRANSPORTATION FORECASTED DEMAND : A GIS APPROACH , 1994 .

[9]  M Batty,et al.  Spatial Aggregation in Gravity Models: 3. Two-Dimensional Trip Distribution and Location Models , 1982, Environment & planning A.

[10]  M Batty,et al.  Spatial Aggregation in Gravity Models: 4. Generalisations and Large-Scale Applications , 1982, Environment & planning A.

[11]  Yichun Xie.  The overlaid network algorithms for areal interpolation problem , 1995 .

[12]  Stan Openshaw,et al.  Modifiable Areal Unit Problem , 2008, Encyclopedia of GIS.

[13]  Ola Hall,et al.  A method for landscape regionalization based on fuzzy membership signatures , 2002 .

[14]  Chandra R. Bhat,et al.  Modifiable Areal Units: A Problem or a Matter of Perception in the Context of Residential Location Choice Modeling? , 2004 .

[15]  Stan Openshaw,et al.  Applying Geocomputation to the Analysis of Spatial Distributions , 1999 .

[16]  Kang-Tsung Chang,et al.  Impacts of Analysis Zone Structures on Modeled Statewide Traffic , 2001 .

[17]  Ming Zhang,et al.  Metrics of Urban Form and the Modifiable Areal Unit Problem , 2005 .

[18]  Michael Batty,et al.  Entropy in Spatial Aggregation , 2010 .

[19]  Stan Openshaw,et al.  A geographical solution to scale and aggregation problems in region-building, partitioning and spatial modelling , 1977 .

[20]  S. Openshaw.  A million or so correlation coefficients : three experiments on the modifiable areal unit problem , 1979 .

[21]  M Batty,et al.  Spatial Aggregation in Gravity Models. 1. An Information-Theoretic Framework , 1982, Environment & planning A.

[22]  Chandra R. Bhat,et al.  Modifiable Areal Units: Problem or Perception in Modeling of Residential Location Choice? , 2004 .

[23]  Y. Chou,et al.  Map Resolution and Spatial Autocorrelation , 2010 .

[24]  S Openshaw,et al.  Algorithms for Reengineering 1991 Census Geography , 1995, Environment & planning A.

[25]  I. Thomas.  Spatial data aggregation: exploratory analysis of road accidents. , 1996, Accident; analysis and prevention.

[26]  M. Worboys,et al.  A formal approach to imperfection in geographic information , 2001 .

[27]  Kang-Tsung Chang,et al.  Effects of Zoning Structure and Network Detail on Traffic Demand Modeling , 2002 .