This paper evaluates the use of various place-based and people-based measures of accessibility in the context of public service delivery. While place-based measures examine the spatial separation between service locations and in a single reference location, people-based measures are based on detailed observations of an individual's activity schedule and space–time constraints. The aim of this paper is to contribute to previous methodological studies of accessibility by investigating the extent to which utility-based measures relying on the Burns–Miller framework relate to place- based and other people-based measures of individual accessibility. In total, four place-based and six people-based measures that are frequently used to evaluate urban service delivery are analyzed. The relationships between these measures are examined and their implications for the assessment of equity of urban service distribution are evaluated. We have found substantial differences between place-based and people-based measures, supporting previous findings in the relevant literature and extending them to utility-based space–time measures of accessibility. We also observed substantial differences within the group of people-based measures. It appears that measures which express the cardinality of a feasible opportunity choice set are quite different from measures which express the desirability of such a set. The salience of this difference is also borne out by the measurement of statistical dispersion of accessibility values, indicating that different measures provide markedly different insights into how equally service delivery is distributed among the population.

In light of the renewed attention for time geography in the transport modelling field in recent years, this paper provides a timely state‐of‐the‐art review of the contributions of the time‐geographic approach to the closely related research areas of transport planning and accessibility analysis. Specific attention will be devoted to the ways in which recent advances in time geography have deepened the understanding of human activities and travel possibilities in space and time. From this literature review, a detailed research agenda is derived and the latest research attempts to deal with lingering time‐geographic issues are discussed.

Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments. In this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach). The mean exposure to NO2 increases with 1.27 μg/m3 (4.3 %) during the week and with 0.12 μg/m3 (0.4 %) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations. It is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones).

In many countries, financial assistance is awarded to physicians who settle in an area that is designated as a shortage area to prevent unequal accessibility to primary health care. Today, however, policy makers use fairly simple methods to define health care accessibility, with physician-to-population ratios (PPRs) within predefined administrative boundaries being overwhelmingly favoured. Our purpose is to verify whether these simple methods are accurate enough for adequately designating medical shortage areas and explore how these perform relative to more advanced GIS-based methods.