Characterizing the location of tourist images in cities. Differences in user-generated images (Instagram), official tourist brochures and travel guides. Paül i Agustí, Daniel Highlights-We compare spatial distribution of user-generated images and projected images.-A partial overlap between the locations captured in these sources was identified.-User-generated images are clearly wider than that from official sources.-To obtain a consistent representation of the city we need to analyse various sources.

Social networks have facilitated access to the spatial location of usergenerated images and this has permitted studies of the spatial distribution of tourist images. To date, however, most studies have tended to focus on European or North American cities. The current research focuses on an analysis of the behaviour of tourists in cities with other social, economic and cultural contexts. To be more precise, we analyse the cities of Los Cabos, Acapulco, Tijuana and La Paz (Mexico), and Natal and Fortaleza (Brazil). These cities share the condition of being both tourist hot spots and some of the cities with the highest murder rates in the world. The main objective of this work is to analyse the spatial concentration of images taken by tourists in contexts that have hitherto received little analysis in academic literature. The results show a clear spatial concentration of user-generated images, especially around the spaces that offer the highest levels of safety.

One of the primary strategies of slowing down the COVID-19 pandemic has been the establishment of social distancing rules that recommend keeping a buffer distance between individuals, and this has proven effective in helping in reducing the basic reproduction number [R 0] . However, social distancing rules have put the use of public spaces in densely populated places under strain, and this is especially important as some of the most virulent outbreaks of the COVID-19 pandemic have been in compact cities. It is therefore fundamental to take into account each neighbourhood's morphological characteristics and the potential population densities each street, square or park can accommodate under such new regulations in order to effectively enforce social distancing rules. Otherwise, certain areas may be rapidly overwhelmed by crowds with citizens unable to maintain the minimum safe distance between individuals. In this paper, we develop a method to identify the potential public space accessibility if social distancing rules are followed and we apply it to three global and highly affected by COVID-19 cities. Our research finds that, at micro level there are important inequalities between neighbourhoods, so people will struggle to comply with social distancing rules and consequently it will make controlling infection rates more difficult.

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