Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.

In the last few decades the magnitude and impacts of planetary urban transformations have become increasingly evident to scientists and policymakers. The ability to understand these processes remained limited in terms of territorial scope and comparative capacity for a long time: data availability and harmonization were among the main constraints. Contemporary technological assets, such as remote sensing and machine learning, allow for analyzing global changes in the settlement process with unprecedented detail. The Global Human Settlement Layer (GHSL) project set out to produce detailed datasets to analyze and monitor the spatial footprint of human settlements and their population, which are key indicators for the global policy commitments of the 2030 Development Agenda. In the GHSL, Earth Observation plays a key role in the detection of built-up areas from the Landsat imagery upon which population distribution is modelled. The combination of remote sensing imagery and population modelling allows for generating globally consistent and detailed information about the spatial distribution of built-up areas and population. The GHSL data facilitate a multi-temporal analysis of human settlements with global coverage. The results presented in this article focus on the patterns of development of built-up areas, population and settlements. The article reports about the present status of global urbanization (2015) and its evolution since 1990 by applying to the GHSL the Degree of Urbanisation definition of the European Commission Directorate General for Regional and Urban Policy (DG-Regio) and the Statistical Office of the European Communities (EUROSTAT). The analysis portrays urbanization dynamics at a regional level and per country income classes to show disparities and inequalities. This study analyzes how the 6.1 billion urban dwellers are distributed worldwide. Results show the degree of global urbanization (which reached 85% in 2015), the more than 100 countries in which urbanization has increased between 1990 and 2015, and the tens of countries in which urbanization is today above the global average and where urbanization grows the fastest. The paper sheds light on the key role of urban areas for development, on the patterns of urban development across the regions of the world and on the role of a new generation of data to advance urbanization theory and reporting.

Better and more detailed analyses of global human exposure to hazards and associated disaster risk require improved geoinformation on population distribution and densities. In particular, issues of temporal and spatial resolution are important for determining the capacity for assessing changes in these distributions. We combine the best-available global population grids with latest data on volcanoes, to assess and characterize the worldwide distribution of population from 1975–2015 in relation to recent volcanism. Both Holocene volcanoes and those where there is evidence of significant eruptions are considered. A comparative analysis is conducted for the volcanic hot spots of Southeast Asia and Central America. Results indicate that more than 8% of the world’s 2015 population lived within 100 km of a volcano with at least one significant eruption, and more than 1 billion people (14.3%) lived within 100 km of a Holocene volcano, with human concentrations in this zone increasing since 1975 above the global population growth rate. While overall spatial patterns of population density have been relatively stable in time, their variation with distance is not monotonic, with a higher concentration of people between 10 and 20 km from volcanoes. We find that in last 40 years in Southeast Asia the highest population growth rates have occurred in close proximity to volcanoes (within 10 km), whereas in Central America these are observed farther away (beyond 50 km), especially after 1990 and for Holocene volcanoes.

The application of last-generation spatial data modelling, integrating Earth Observation, population, economic and other spatially explicit data, enables insights into the sustainability of the global urbanisation processes with unprecedented detail, consistency, and international comparability. In this study, the land use efficiency indicator, as developed in the Sustainable Development Goals, is assessed globally for the first time at the level of Functional Urban Areas (FUAs). Each FUA includes the city and its commuting zone as inferred from statistical modelling of available spatial data. FUAs represent the economic area of influence of each urban centre. Hence, the analysis of land consumption within their boundary has significance in the fields of spatial planning and policy analyses as well as many other research areas. We utilize the boundaries of more than 9,000 FUAs to estimate the land use efficiency between 1990 and 2015, by using population and built-up area data extracted from the Global Human Settlement Layer. This analysis shows how, in the observed period, FUAs in low-income countries of the Global South evolved with rates of population growth surpassing the ones of land consumption. However, in almost all regions of the globe, more than half of the FUAs improved their land use efficiency in recent years (2000–2015) with respect to the previous decade (1990–2000). Our study concludes that the spatial expansion of urban areas within FUA boundaries is reducing compactness of settlements, and that settlements located within FUAs do not display higher land use efficiency than those outside FUAs.