Journal of Transport Geography

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Previous activity-based studies have shown that behavioural outcomes are the result of complex and multidimensional processes. In this context, identifying and characterizing discrete mobility profiles through the classification of people’s behavior is particularly attractive. By facilitating the interpretation of complex, multidimensional processes, such an exercise could help to efficiently target transport policy decisions. The purpose of this paper is to identify mobility strategy profiles considering four key dimensions: time, space, money, and social interaction. Data from a seven-day activity, travel, expenditure, and social interaction diary applied to a sample of residents from the city of Concepción, Chile, is used. A two-step approach based on machine learning techniques is adopted. First, we use a Self-Organizing Map algorithm to identify seven distinct mobility strategies, each characterized by distinctive behaviors. These profiles are identified through 18 weekday and weekend daily behavior variables measuring the four key dimensions mentioned above, with an explicit focus on transport mode use. In the second step, we use a Decision Tree algorithm to profile the mobility strategies by means of personal and household sociodemographic variables. The results show interesting links among the dimensions of analysis within these profiles, such as connections between monetary expenditure on leisure and daily social interaction, and that profiles with higher private vehicle modal split tend to present higher levels of social interaction with people in their social network than public transit users.

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Journal of Glaciology

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Soil Biology and Biochemistry

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The Science of the total enviroment

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The Routledge Handbook of Urban Resilience

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Journal of Transport Geography

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Wildfires are gaining importance in the Mediterranean regions owing to climate change and landscape changes due to the increasing closeness between urban areas and forests prone to wildfires. We analysed the dry season wildfire occurrences in the Mediterranean region of Central Chile (32°S–39°30′ S) between 2000 and 2017, using satellite images to detect burned areas, their landscape metrics and the land use and covers (vegetal) pre-wildfire, in order to determine the population living in areas that may be affected by wildfires. The existing regulations in western Mediterranean countries (Portugal, Spain, France, and Italy) were used to identify and define the wildland-urban interface (WUI) areas, quantifying the people inhabiting them and estimating the population affected by burned areas from 2001 to 2017. We used the Google Earth Engine to process MODIS products and extract both burned areas and land covers. We detected that 25% of the urban population inhabits WUI areas (i.e. Biobío, Araucanía and Valparaíso regions) where the urban population exposed to burned areas exceeds 40%. Most of the land use and land covers affected by wildfires are anthropogenic land covers, classified as savannas, croplands, evergreen broadleaf forests and woody savannas, representing >70% of the burned areas. Urban areas show only 0.6% of the burned surface from 2001 to 2017. We estimate that 55,680 people are potentially affected by wildfires, and 50% of them are in just one administrative region. These results show the imperative need for public policies as a regulating force for establishing WUI areas with the purpose of identifying wildfire risk in urban areas, such as establishing prevention methods as firewalls and prescribed fires.

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Transportation Research Record

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Hydrometallurgy

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Transport Reviews

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Transport Reviews

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Transport Reviews

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