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Freizeitverkehrsforschung aus klassischer verkehrswissenschaftlicher Sicht: Ein Blick zurück und nach vorn
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Modelling hedonic residential rents for land use and transport simulation while considering spatial effects
Get PDFJTLU vol 3, no 2, pp 39-63 (2010)The application of UrbanSim requires land or real estate price data for the study area. These can be difficult to obtain, particularly when tax assessor data and data from commercial sources are unavailable. The article discusses an alternative method of data acquisition and applies hedonic modeling techniques in order to generate the required data. Many studies have highlighted that ordinary least square (OLS) regression approaches lack the ability to consider spatial dependency and spatial heterogeneity, consequently leading to biased and inefficient estimations. Therefore, a comprehensive data set is used for modeling residential asking rents by applying and comparing OLS, spatial autoregressive, and geographically weighted regression (GWR) techniques. The latter technique performed best with regard to model fit, but the issue of correlated coefficients favored a spatial simultaneous autoregressive model. Overall, the article reveals that when housing markets are a particular concern in UrbanSim applications, significant efforts are needed for the price data generation and modeling. The study concludes with further development potentials for UrbanSim.Löchl, Michael; Axhausen, Kay. (2010). Modelling hedonic residential rents for land use and transport simulation while considering spatial effects. Retrieved from the University Digital Conservancy, 10.5198/jtlu.v3i2.117
A multiscale classification of urban morphology
Get PDFVarious studies in the field of urban planning and design have given recommendations for "good urban forms," suggesting that specific spatial characteristics inform the quality of an urban landscape and the way people perceive and behave in them. When modeling spatial behavior in the form of location choice models or hedonic prices, we should reflect these spatial characteristics through the integration of quantitative attributes such as model variables, which is currently only done in a very limited way. The increasing availability of disaggregated geodata enlarges the options to characterize urban morphology in the form of such attributes. The question for the researcher is which attributes are most useful to reflect characteristics of urban morphology and how can they be processed from the given data. In this paper, we want to address this issue and give an overview of quantitative descriptions of urban morphology. We base our work on a data model that is simple enough to allow for reproducibility in any study area. These attributes are classified in multiple scales to reflect different perceptions of urban morphology. In a case study on the canton of Zurich, we furthermore prove how these characteristics allow for the definition of urban typologies at different scales.Schirmer, Patrick M.; Axhausen, Kay W.. (2016). A multiscale classification of urban morphology. Retrieved from the University Digital Conservancy, 10.5198/jtlu.2015.667
Multi-day activity-travel pattern sampling based on single-day data
No full textAlthough it is important to consider multi-day activities in transportation planning, multi-day activity-travel data are expensive to acquire and therefore rarely available. In this study, we propose to generate multi-day activity-travel data through sampling from readily available single-day household travel survey data. A key observation we make is that the distribution of interpersonal variability in single-day travel activity datasets is similar to the distribution of intrapersonal variability in multi-day. Thus, interpersonal variability observed in cross-sectional single-day data of a group of people can be used to generate the day-to-day intrapersonal variability. The proposed sampling method is based on activity-travel pattern type clustering, travel distance and variability distribution to extract such information from single-day data. Validation and stability tests of the proposed sampling methods are presented.
Location choice for a continuous simulation of long periods under changing conditions
Get PDFJTLU vol. 7, no. 2, pp. 85-103 (2014)The authors propose a location choice procedure that is capable of handling changing conditions of aspects with different time horizons. It integrates expected travel time, current location effectiveness, prospective location effectiveness, and individual unexplained location perception into a decision heuristic that considers different planning horizons simultaneously and decides on-the-fly about future location visits. Multiple simulation runs illustrate agents' location choice behavior in various situations and confirm that the model enables agents to simultaneously consider seasonal effects, weather conditions, expected travel times, and individual unexplained location preference in their location choice.Märki, Fabian; Charypar, David; Axhausen, Kay. (2014). Location choice for a continuous simulation of long periods under changing conditions. Retrieved from the University Digital Conservancy, 10.5198/jtlu.v7i2.547
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