The separation between the countryside and the city, from rural and urban areas, has been one of the central themes of the literature on urban and territorial studies. The seminal work of Kingsley Davis  in the 1950s introduced a wide and fruitful debate which, however, has not yet concluded in a rigorous definition that allows for comparative studies at the national and subnational levels of a scientific nature. In particular, the United Nations (UN) definition of urban and rural population is overly linked to political and administrative factors that make it difficult to use data adequately to understand the human settlement structure of different countries. The present paper seeks to define a more rigorous methodology for the identification of rural and urban areas. For this purpose it uses the night lights supplied by the SNPP satellite, and more specifically by the VIIRS sensor for the determination of the urbanization gradient, and by means of the same construct a more realistic indicator than the statistics provided by the UN. The arrival of electrification to nearly every corner of the planet is certainly the first and most meaningful indicator of artificialization of land. In this sense, this paper proposes a new methodology designed to identify highly impacted (urbanized) landscapes worldwide based on the analysis of satellite imagery of night-time lights. The application of this methodology on a global scale identifies the land highly impacted by light, the urbanization process, and allows an index to be drawn up of Land Impacted by Light per capita (LILpc) as an indicator of the level of urbanization. The methodology used in this paper can be summarized in the following steps: a) a logistic regression between US Urban Areas (UA), as a dependent variable, and night-time light intensity, as an explanatory variable, allows us to establish a nightlight intensity level for the determination of Areas Highly Impacted by Light (AHIL); b) the delimitation of the centers and peripheries is made by setting a threshold of night-time light intensity that allows the inclusion of most of the centers and sub-centers; c) once identified urbanized areas, or AHIL, it is necessary to delimit the rural areas, or Areas Little Impacted by Light (ALIL), which are characterized by low intensity night light; d) finally, rurban landscapes are those with nightlight intensities between ALIL and AHIL. The developed methodology allows comparing the degree of urbanization of the different countries and regions, surpassing the dual approach that has traditionally been used. This paper enables us to identify the different typologies of urbanized areas (villages, cities and metropolitan areas), as well as “rural”, “rurban”, “periurban” and “central” landscapes. The study identifies 186,134 illuminated contours (urbanized areas). 404 of these contours have more than 1,000,000 inhabitants and can be considered real “metropolitan areas”; on the other hand there are 161,821 contours with less than 5,000 inhabitants, which we identified as “villages”. Finally, the paper shows that 40.26% live in rural areas, 15.53% in rurban spaces, 26.04% in suburban areas and only 18.16% in central areas.
Blanca Arellano and Josep Roca, "Defining urban and rural areas: a new approach," Proc. SPIE 10431, Remote Sensing Technologies and Applications in Urban Environments II, 104310E (Presented at SPIE Remote Sensing: September 12, 2017; Published: 4 October 2017); https://doi.org/10.1117/12.2277902.
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