Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006
Introduction
Beginning with the classic work of Hansen (1959), the concept of accessibility has been widely applied to studies of the impacts of various transportation infrastructure and modes on socioeconomic activities and land-use/land-cover change. As a concept reflecting the weighted moving average of access to targets or “opportunities,” accessibility not only emphasises the transportation system, but also accounts for land-use patterns (Bhat et al., 2000, Harris, 2001). The introduction of High-Speed Rail (HSR) in Europe after the late 1970s created a new European time–space map, inherently associated with accessibility and socioeconomic benefits (Bonnafous, 1987, Campos and de Rus, 2009, Chen and Hall, 2011a, Givoni, 2006, Haynes, 1997, Pol, 2003, Spiekermann and Wegener, 1994, Vickerman, 1995). In urban areas, the attractiveness of HSR depends on the quality and level of accessibility to its stations (Brons et al., 2009). The presence of an HSR station may entail the development of new commercial, leisure, and residential areas in its catchment area (Ureña et al., 2009). With good levels of accessibility to an HSR station, new internationally-oriented, service-based, and knowledge-intensive companies tend to relocate in its proximity (Chen and Hall, 2011b, Hood, 2010, Moulaert et al., 2001, Preston and Wall, 2008, Ureña et al., 2009, Willigers et al., 2007, Willigers and van Wee, 2011). In contrast, the absence of an HSR station may even become a barrier to economic development due to spatial marginalisation (Vickerman and Ulied, 2009). Besides HSR, the improvement of accessibility at the local level due to the implementation of intra-city public transit infrastructure has also been proven to impact urban structures (Ahlfeldt and Wendland, 2011, Calvo et al., 2013, Cervero, 1995, Donaldson, 2006, Israel and Cohen-Blankshtain, 2010, Mejia-Dorantes et al., 2012).
To model the interaction between transportation and land use, one argument is commonly recognised by modellers: transport investment shapes land use patterns (Knowles, 2006). Due to the complexity of land use, changes in accessibility that partially reflect transport investment are not the only factor in modelling land-use/land-cover changes. An early work by Knight and Trygg (1977) listed several land-use influence factors, in addition to accessibility: i.e., the attractiveness of the station per se, neighbourhood impacts or constraints, socioeconomic demands, land-use policies, etc. Based on this research, two major types of methods have been widely adopted to analyse the land use-transportation system: individual-based models and spatial discrete-choice models. The former approach mainly simulates the transition of each individual among various stages, involving cellular automata (Basse, 2013, Batty, 1998, Batty et al., 1999, de Noronha Vaz et al., 2012, Li and Yeh, 2000, Li and Yeh, 2002, White and Engelen, 1993, White and Engelen, 2000), microsimulation (Ballas et al., 2005, Waddell et al., 2003), and agent-based modelling (Barros, 2012, Brown and Robinson, 2006, Matthews et al., 2007, Parker, 2005, Wu et al., 2007). The latter implementation focuses more on the sophisticated choice problems, including spatial interactions, with panel and longitudinal data analysis (Nijkamp, 1987). To model the spatial interdependencies, one implementation places the neighbourhood impacts into a set of explanatory variables to affect individual utility (Mohammadian et al., 2005, Mohammadian and Kanaroglou, 2003, Páez and Scott, 2007, Páez et al., 2008), in which the preferences of neighbours are unknown to individuals. Thus, the choice probability in such models depends on individual-specific variables and the neighbour’s choice rather than utility, with purely probabilistic interdependencies (Smirnov, 2010a). Another spatial modelling structure also recognises spatial correlation based on the definition of a neighbourhood, translating to spatially correlated error terms; e.g., the mixed spatially correlated logit (SCL) model (Bhat and Guo, 2004), the generalised spatial correlated logit (GSCL) model (Sener et al., 2011), the dynamic spatial multinomial probit (DSMNP) model (Wang et al., 2012), and spatial random utility models (Smirnov, 2010a, Smirnov, 2010b, Smirnov and Egan, 2012), etc.
Previous studies in terms of the impacts of HSR on Madrid mainly focus on the “exterior” regional agglomeration impacts on the creation of the Greater Metropolitan Area of Madrid due to the improvement of accessibility (Garmendia et al., 2012, Garmendia et al., 2008, Monzón et al., 2013). Yet studies on the “interior” local impacts of HSR, as an essential component of the local transportation system, on land cover change and socioeconomic growth within Madrid are limited (Shen et al., 2013). Thus this present study attempts to assess the impacts of HSR on land cover change in Madrid Atocha station’s buffer (service) area from 1990 to 2006. In order to measure the contribution of HSR among all the other factors (e.g., the growth of socioeconomic activities and the expansion of the local public transit network) on local land-cover change, a spatial mixed logit modelling approach with panel data structure is adopted, incorporating integrated regional–local accessibility as a nexus between HSR and land cover change.
The modelling approaches are described in detail in Section 2. In Section 3, the background of Madrid Atocha railway station is introduced and the selection of its buffer (service) area is also discussed. To accomplish the modelling assessment, Section 4 introduces the processing of collected data, comprehending local data in Madrid at the census tract (sección censal) level, as well as Spanish regional data at the municipal level. Based on the processed data, Section 5 presents two models: one that considers the impact of HSR and HSR facilities on regional accessibility, and the other (as a control model) that does not. Finally, conclusions are presented in Section 6 together with a discussion of the main findings.
Section snippets
Accessibility estimation
In general, accessibility serves as an input for the calculation of economic benefits of land-use/transportation changes, with four different measures: infrastructure-based, location-based, person-based, and utility-based accessibility measures (Geurs and van Wee, 2004). In the studies of HSR impacts in Europe, the location-based measurement is widely implemented with two indicators: weighted average travel time (Gutiérrez, 2001, Gutiérrez et al., 1996) and economic potential (Baptiste et al.,
Case study: Atocha station and the selection of its buffer area
Atocha station, located in the southern part of the centre of Madrid (Spain), is a railway complex that acts as an interchange for subway services, suburban trains, national regional railways and high-speed services, and international HSR services to France and Portugal (planned). The HSR services from Atocha to Seville, Zaragoza, Toledo, and Barcelona were inaugurated in 1992, 2003, 2005, and 2008, respectively. The station also connects local Cercanías commuter rail and the Madrid Metro,
Data processing
The data adopted in this study could be classified in two major categories. The first one comprises socioeconomic data, as well as land cover variables. The second category summarises transportation GIS data, including the local public transport and road transportation network in Madrid, plus the regional railway (i.e., HSR and conventional rail) and roadway network data. Each category of data is collected from three different years: 1990, 2000, and 2006. As the data gathered cannot be directly
Results and analysis
The simulation is run using BIOGEME software package (Bierlaire, 2003) with 2000 Halton random draws, which fixes the alternative specific constant of continuous urban fabric land cover at 0. The estimated parameters with and without spatial autocorrelation component, Znit in Eq. (13), are both listed in Table 5(a). For each cell n, there are at maximum 112 neighbourhood cells, as Sn, within the 3 km distance. To relieve the demanding nonlinear calculation task, for each land cell n, 30
Conclusions and discussions
This paper studied the impacts of HSR service on land cover change within a buffer of 20 km centred on Atocha station in Madrid, from 1990 to 2006. To quantify the impacts due to the construction and upgrade of regional and local transportation infrastructure (i.e., HSR, local public transit, and roadway networks), the weighted average travel time accessibility indicator is chosen as one of the explanatory variables. Both ML and SML modelling frameworks are adopted to study the impacts of
Acknowledgements
This research was developed in the framework of the EXPRESS Research Project (MIT/SET/0023/2009) sponsored by the Portuguese National Research Funds through FCT/MCTES (PIDDAC) and co-financed by the European Regional Development Fund (ERDF) under the Operational Agenda for Competitiveness Factors – COMPETE. We acknowledge the help from Marcos Correia in the data collection process. We also appreciate Prof. Andrés Monzón from Universidad Politécnica de Madrid for his help in this study.
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