In a wider understanding, shared mobility can be defined as trip alternatives that aim to maximize the utilization of the mobility resources that a society can pragmatically afford, disconnecting their usage from ownership. Then, shared mobility is the short-term access to shared vehicles according to the user’s needs and convenience. The contributions and added value of this paper are to provide an up-to-date and well-structured review on the area of shared mobility to researchers and practitioners of the transport sector. Hence, this paper presents a bibliographical review of shared mobility and its diverse modalities, as an alternative to individual transportation, especially in cases of individual automobiles or short trips restricted to an urban city. The present literature review on shared modes of transportation has discovered that the introduction of these modes alone will not solve transportation problems in large cities, with elevated and growing motorization rates. However, it can among the strategies employed to help alleviate the problems caused by traffic jams and pollution by reducing the number of vehicles in circulation, congestions, and the urban emission of polluting gases. Thus, the implementation of shared mobility schemes offers the potential to enhance the efficiency, competitiveness, social equity, and quality of life in cities. This paper covers the fundamental aspects of vehicle and/or ride sharing in urban centers, and provides an overview of current shared mobility systems.

This article analyses DMSP/OLS night‐time imagery as an information source to detect human settlements and to estimate the urban population in the Amazon region. DMSP/OLS single orbits were used to generate a DMSP stable light mosaic for 2002, in which most of the urban settlements with a population higher than 5000 inhabitants were precisely identified. DMSP/OLS night‐time mosaic images from 1995, 1999 and 2002 were integrated with the IBGE census data and the correlation between DMSP/OLS night‐time light area and the urban population was compared. Coefficients of determination higher than 0.8 were obtained from the linear regression between DMSP/OLS night‐time lights and urban population census data. Although the fieldwork showed that DMSP image data could only record urbanized settlements with more than 2.5 km² of well‐lit surface areas, the initial and final extension of the night‐time light foci were actually precisely registered. Therefore, this paper identifies the potential of DMSP night‐time light images for estimating urban population as well as the technical limitations of using such images as a means to monitor urban population dynamics annually in a region where data are scarce and the demographic dynamics are unique, as in the Brazilian Amazon.

This paper discusses the use of spatial data for risk and natural disaster management. The importance of remote-sensing (RS), Geographic Information System (GIS) and Global Navigation Satellite System (GNSS) data is stressed by comparing studies of the use of these technologies for natural disaster management. Spatial data sharing is discussed in the context of the establishment of Spatial Data Infrastructures (SDIs) for natural disasters. Some examples of SDI application in disaster management are analyzed, and the need for participation from organizations and governments to facilitate the exchange of information and to improve preventive and emergency plans is reinforced. Additionally, the potential involvement of citizens in the risk and disaster management process by providing voluntary data collected from volunteered geographic information (VGI) applications is explored. A model relating all of the spatial data-sharing aspects discussed in the article was suggested to elucidate the importance of the issues raised.