Data integration for urban transport planning

Abstract

Urban transport planning aims at balancing conflicting challenges by promoting more efficient transport systems while reducing negative impacts. The availability of better and more reliable data has not only stimulated new planning methodologies, but also created challenges for efficient data management and data integration. The major focus of this study is to improve methodologies for representing and integrating multi-source and multi-format urban transport data. This research approaches the issue of data integration based on the classification of urban transport data both from a functional and a representational perspective. The functional perspective considers characteristics of the urban transport system and planning requirements, and categorises data into supply, demand, performance and impact. The representational perspective considers transport data in terms of their spatial and non-spatial characteristics that are important for data representation. These two perspectives correspond to institutional and methodological data integration respectively, and are the foundation of transport data integration. This research is based on the city of Wuhan in China. The methodological issues of transport data integration are based on the representational perspective. A framework for data integration has been put forward, in which spatial data are classified as point, linear and areal types, and the non-spatial data are sorted out as values and temporal attributes. This research has respectively probed the integration of point, linear and areal transport data within a GIS environment. The locations of socio-economic activities are point-type data that need to be spatially referenced. A location referencing process requires a referencing base, source address units and referencing methods. The referencing base consists of such spatial features as streets, street addresses, points of interest and publicly known zones. These referencing bases have different levels of spatial preciseness and have to be kept in a hierarchy. Source addresses in Chinese cities are usually written as one sentence, which has to be divided into address units for automatic geo-coding. As it is difficult to separate from the sentences, the address units have to be clearly identified in survey forms. Depending on the types of address units, the referencing process makes use of either semantic name matching or address matching to link source addresses to features in the referencing base. The name-based and road-based referencing schemes constitute a comprehensive location referencing framework that is applicable to Chinese cities. The relationship between two sets of linear features can be identified with spatial overlay in the case of independent representation, or with internal linkage in a dependent representation. The bus line is such a feature that runs on the street network and can be dependently referenced by streets. In the heavily bus-oriented city of Wuhan, bus lines constitute a large public transit network that is important to transport planning and management. This research has extended conventional bus line representation to a more detailed level. Each bus line has been differentiated as two directional routes that are defined separately with reference to the street network. Accordingly, individual route stops are also represented in the database. These stop sites are spatial features with geometry that are linked to street segments and bus routes by linear location referencing methods. A data model linking base street network, bus lines and routes, line and route stops, and other bus operations data has been constructed. The benefits of the detailed model have been demonstrated in several transport applications. Zonal data transitions include three types of operations, i.e. aggregation, areal interpolation and disaggregation. This study focuses on disaggregating data from larger zones to smaller zones. In the context of Wuhan, zonal data disaggregation involves the allocation of statistical data from statistical units to smaller parcels. Given the availability of land use data, a weighted approach reflecting spatial variations has been applied in the disaggregation process. Two technical processes for disaggregation have been examined. Weighted area-weighting (WAW) is an adaptation of the classic area-weighting method, and Monte Carlo simulation (MC) is a stochastic process based on a raster data model. The MC outcome is more convenient for subsequent re-aggregation, and is also directly available for micro-simulation. An important contribution arising from this zonal integration study is that two standardised disaggregation tools have been developed within a GIS environment. The research has also explored the institutional aspect of data integration. The findings of this study show that there is generally a good institutional transport structure in the city of Wuhan and that there is also a growing awareness of using information technology. Professional cooperation exists among transport organisations, but not yet at a level for data sharing. An integrated data support framework requires data sharing. In such a framework, it should be possible to know where to get data for specific transport studies, or which kind of research an institution supports