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This paper analyzes the factors that enable or hinder the use of sustainable modes of travel for work or study in a low-income area in southern Bogotá. The results, based on quantitative and qualitative material, show that the residents of this area mostly travel using sustainable modes and reveal how informal transportation facilitates daily bicycle use. In contrast, insecurity, invasion of public space, inadequate infrastructure, cost of travel, and rules regulating the use of public transport appear to be barriers. This suggests that urban mobility policies and projects in Bogotá overlook some realities faced by the inhabitants of the city's margins, thus hampering the further development of sustainable mobility practices. [ABSTRACT FROM AUTHOR]

This paper describes a new kind of dynamic map showing the differing location of 'day' and 'night' populations and how they balance out over 24 h. To this end, we created a smoothed animated cartogram, with visual effectiveness as the main criterion. The area of study is the Bogotá metropolitan area in Colombia, where an urban mobility survey (EODH) was carried out in 2019. This paper emphasizes the method developed and the discussions which arose over the course of our work. We used R language to process the data and create the animations in order to make them reproducible, following an open-science approach. We mainly used the cartogramR and spatstat packages. The R script is appended. [ABSTRACT FROM AUTHOR]

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Copyright of Territorios: Revista de Estudios Regionales y Urbanos is the property of Universidad de los Andes and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article examines macro‐level contextual parameters and individual‐based factors deemed in the literature to directly influence individuals' daily mobility practices. It considers the urban structure, place of residence, situation in the social hierarchy, and position in the life course. Taking its inspiration from approaches highlighting segregation at destination place and studies focusing on mobility biographies, it enquires whether systematic discrepancies may be detected between the places frequented for work or study on a daily basis by the groups of individuals residing in the same neighborhood. It also looks at whether home location (in a central area, inner suburb, or outskirt) influences how action spaces are configured. The analysis relies on a three‐phase integrated method. First, a typology of individuals is assembled to put together homogenous socio‐demographic groups. Second, the action spaces of these groups are calculated and mapped. Third, the significance of spatial differences in action spaces is assessed using a bivariate colocation test, hitherto used primarily in spatial epidemiology. This three‐phase method is applied to data collected in Santiago de Chile during a survey of 1,000 households, designed to capture spatial mobility from a biographical perspective. [ABSTRACT FROM AUTHOR]

The article presents research which analyzes unequal access to urban resources in the city of São Paulo, Brazil, through the examination of its population's daily mobility. The research was conducted within the framework of the research program Métropoles d'Amérique latine dans la globalisation: reconfigurations territorial, mobility spatiale, action publique (METAL). Some of the questions considered include how daily frequented spaces differ from one's home or sociodemographic characteristics, activity spaces associated with an individual's various life cycle stages, and an adequate spatial level between one's home and work location.

In a point set in dimension superior to 1, the statistical distribution of the number of pairs of points as a function of distance between the points of the pair is not uniform. This distribution is not considered in a large number of classic methods based on spatially weighted means used in spatial analysis, such as spatial autocorrelation indices, kernel interpolation methods, or spatial modeling methods (autoregressive, or geographically weighted). It has a direct impact on the calculations and the results of indices and estimations, and by not taking into account this distribution of the distances, spatial analysis calculations can be biased. In this article, we introduce a "spatial standardization", which corrects and adjusts the calculations with respect to the distribution of point pairs distances. As an example, we apply this correction to the calculation of spatial autocorrelation indices (Moran and Geary indices) and to trend surface calculation (by spatial kernel interpolation) on the results of the 2017 French presidential election. [ABSTRACT FROM AUTHOR]