User:Bubblehead607/sandbox

In the paper Effects of the modifiable areal unit problem on the delineation of traffic analysis zones published in Environment and Planning B: Planning and Design 2009, volume 36, the authors put forth transportation analysis is typically thought of as one kind of spatial analysis; however, spatial analysis has some limitations, the discretization of space, to address the issues in transportation analysis. The design of traffic analysis zones (TAZs) can be affected by the modifiable areal unit problem (MAUP) which happens during the geographic data aggregation or analysis. The MAUP effect has two components including scale effects and zoning effects that the focus of this research is the earlier one. There is no way to completely solve the MAUP effects; however it can be effectively minimized. To reduce the MAUP effects, there are three recommendations including starting from the smallest division, aggregating the divisions, and evaluating different combinations of the aggregations. To address the MAUP’s effect, some research have been developed since 1970’s starting with automated zone design program (AZP) and its developed versions to give the users more flexibility in terms of re-aggregating data. The next research were based on finding the relation between MAUP and transportation planning models, the TAZ structure and the level of transportation network, and changing the zoning system and returning analysis.

The authors developed a new methodology and GIS-based application to measure the effects of MAUP on the TAZ delineation by analyzing grids in different dimensions on Lisbon Metropolitan Area (AML) as a case study. There are different options for grids’ justification including defining valid and reliable zones, cell-based analysis, object-based analysis, and matrix-based analysis. This paper analyzes the square cells with 200 m as lower bound and 2000 m as upper bound. The dimension of the gird and the location of the gird origin are two factors evaluated by eight indicators in the origin – destination (O-D) matrix including maximum cell value, average cell value, percentage of cells without any trips, percentage of intrazonal trips, maximum number of origins or destination per cell, average number of origins or destinations per cell, percentages of cells with no trip origins or destinations, and percentage of trips in non-statistically significant cells. An important basic concept is ‘Intrazonal trips cannot be assigned to the network, as they now have the same origin and destination `point'. Therefore, these trips constitute lost information for the traffic demand modeling, and their number should be minimized.’ The most significant indicators are the percentage of intrazonal trips in the O-D matrix, the percentage of trips in non-statistically-significant O-D matrix cells, and the percentage of zones with no trips. In addition, a sensitivity analysis has been done to find the effect of the grid origin location in the indicator. The outputs of this research show that the cell size has a significant impact on the percentage of intrazonal trips and cells with no trips. The cell origin position has a small impact on the percentage of intrazonal trips and very significant impact on percentage of cells with no trips and percentage of trips in non-statistically-significant O-D matrix.