This page has only limited features, please log in for full access.
Between 1970 and 2015 urban population almost doubled worldwide with the fastest growth taking place in developing regions. To aid the understanding of how urbanisation has influenced anthropogenic CO2 and air pollutant emissions across all world regions, we make use of the latest developments of the Emissions Database for Global Atmospheric Research. In this study, we systematically analyse over 5 decades of emissions from different types of human settlements (from urban centres to rural areas) for different sectors in all countries. Our analysis shows that by 2015, urban centres were the source of a third of global anthropogenic greenhouse gases and most of the air pollutant emissions. The high levels of both population and emissions in urban centres therefore call for focused urban mitigation efforts. Moreover, despite the overall increase in urban emissions, megacities with more than 10 million inhabitants in high-income countries have been reducing their emissions, while emissions in developing regions are still growing. We further discuss per capita emissions to compare different types of urban centres at the global level.
Monica Crippa; Diego Guizzardi; Enrico Pisoni; Efisio Solazzo; Antoine Guion; Marilena Muntean; Aneta Florczyk; Marcello Schiavina; Michele Melchiorri; Andres Fuentes Hutfilter. Global anthropogenic emissions in urban areas: patterns, trends, and challenges. Environmental Research Letters 2021, 16, 074033 .
AMA StyleMonica Crippa, Diego Guizzardi, Enrico Pisoni, Efisio Solazzo, Antoine Guion, Marilena Muntean, Aneta Florczyk, Marcello Schiavina, Michele Melchiorri, Andres Fuentes Hutfilter. Global anthropogenic emissions in urban areas: patterns, trends, and challenges. Environmental Research Letters. 2021; 16 (7):074033.
Chicago/Turabian StyleMonica Crippa; Diego Guizzardi; Enrico Pisoni; Efisio Solazzo; Antoine Guion; Marilena Muntean; Aneta Florczyk; Marcello Schiavina; Michele Melchiorri; Andres Fuentes Hutfilter. 2021. "Global anthropogenic emissions in urban areas: patterns, trends, and challenges." Environmental Research Letters 16, no. 7: 074033.
The Degree of Urbanisation is a new definition of cities, towns and semi-dense areas, and rural areas endorsed by the UN Statistical Commission. The urban population share according to the Degree of Urbanisation is similar to the one based on national definitions in the Americas, Europe and Oceania, but considerably higher in Africa and Asia. An empirical analysis and a comparison of concepts suggest that towns are likely to be classified as rural areas in Africa and Asia and as urban areas in other parts of the world. The paper shows that cities cover only a small share of land, but this share doubled over the past forty years, as has the number of cities. Although cities have expanded rapidly, their population grew even faster leading to higher densities. The paper tests two classic urban facts: 1) the cities and towns as defined by the Degree of Urbanisation closely follow Zipf's law 2) the population shares in urban areas, cities and especially metropolitan areas are positively and significantly correlated with the level of economic development. Lastly, the sensitivity of the classification of population and land are tested by varying the population size and density thresholds as well using a different global population grid.
Lewis Dijkstra; Aneta J. Florczyk; Sergio Freire; Thomas Kemper; Michele Melchiorri; Martino Pesaresi; Marcello Schiavina. Applying the Degree of Urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation. Journal of Urban Economics 2020, 103312 .
AMA StyleLewis Dijkstra, Aneta J. Florczyk, Sergio Freire, Thomas Kemper, Michele Melchiorri, Martino Pesaresi, Marcello Schiavina. Applying the Degree of Urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation. Journal of Urban Economics. 2020; ():103312.
Chicago/Turabian StyleLewis Dijkstra; Aneta J. Florczyk; Sergio Freire; Thomas Kemper; Michele Melchiorri; Martino Pesaresi; Marcello Schiavina. 2020. "Applying the Degree of Urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation." Journal of Urban Economics , no. : 103312.
The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus ignoring the changing population densities resulting from human mobility. Existing assessments of spatio-temporal population are limited in their detail and geographical coverage, and the promising mobile-phone records are hindered by issues concerning availability and consistency. Here, we present a multi-layered dasymetric approach that combines official statistics with geospatial data from emerging sources to produce and validate a European Union-wide dataset of population grids taking into account intraday and monthly population variations at 1 km2resolution. The results reproduce and systematically quantify known insights concerning the spatio-temporal population density structure of large European cities, whose daytime population we estimate to be, on average, 1.9 times higher than night time in city centers.
Filipe Batista E Silva; Sérgio Freire; Marcello Schiavina; Konštantín Rosina; Mario Alberto Marín-Herrera; Lukasz Ziemba; Massimo Craglia; Eric Koomen; Carlo Lavalle. Uncovering temporal changes in Europe’s population density patterns using a data fusion approach. Nature Communications 2020, 11, 1 -11.
AMA StyleFilipe Batista E Silva, Sérgio Freire, Marcello Schiavina, Konštantín Rosina, Mario Alberto Marín-Herrera, Lukasz Ziemba, Massimo Craglia, Eric Koomen, Carlo Lavalle. Uncovering temporal changes in Europe’s population density patterns using a data fusion approach. Nature Communications. 2020; 11 (1):1-11.
Chicago/Turabian StyleFilipe Batista E Silva; Sérgio Freire; Marcello Schiavina; Konštantín Rosina; Mario Alberto Marín-Herrera; Lukasz Ziemba; Massimo Craglia; Eric Koomen; Carlo Lavalle. 2020. "Uncovering temporal changes in Europe’s population density patterns using a data fusion approach." Nature Communications 11, no. 1: 1-11.
This paper presents a novel method to delineate metropolitan areas – or functional urban areas (FUAs) – in the entire world and assesses their population trends. According to the definition developed by the OECD and the European Uunion, FUAs are composed of high-density urban centres with at least 50 thousand people plus their surrounding commuting zones. The latter represent the urban centres’ areas of influence in terms of labour market flows. The proposed method combines a functional and a morphological approach to overcome the dependency on travel-to-work data to define commuting zones and allow a global delineation. It relies on a probabilistic approach and the use of population and travel impedance gridded data across the globe. Results show that around 3.9 billion people, making up 53% of the world population, live in 8,790 FUAs, out of which 17% live in their commuting zones. Between 2000 and 2015, population growth was higher in larger FUAs, highlighting a general trend toward higher concentration of the metropolitan population. Commuting zones grew faster than urban centres, though with heterogeneous patterns across world regions, income levels and metropolitan size.
Ana I. Moreno-Monroy; Marcello Schiavina; Paolo Veneri. Metropolitan areas in the world. Delineation and population trends. Journal of Urban Economics 2020, 103242 .
AMA StyleAna I. Moreno-Monroy, Marcello Schiavina, Paolo Veneri. Metropolitan areas in the world. Delineation and population trends. Journal of Urban Economics. 2020; ():103242.
Chicago/Turabian StyleAna I. Moreno-Monroy; Marcello Schiavina; Paolo Veneri. 2020. "Metropolitan areas in the world. Delineation and population trends." Journal of Urban Economics , no. : 103242.
Sustainable Development Goal (SDG) 11 aspires to “Make cities and human settlements inclusive, safe, resilient and sustainable”, and the introduction of an explicit urban goal testifies to the importance of urbanisation. The understanding of the process of urbanisation and the capacity to monitor the SDGs require a wealth of open, reliable, locally yet globally comparable data, and a fully-fledged data revolution. In this framework, the European Commission–Joint Research Centre has developed a suite of (open and free) data and tools named Global Human Settlement Layer (GHSL) which maps the human presence on Earth (built-up areas, population distribution and settlement typologies) between 1975 and 2015. The GHSL supplies information on the progressive expansion of built-up areas on Earth and population dynamics in human settlements, with both sources of information serving as baseline data to quantify land use efficiency (LUE), listed as a Tier II indicator for SDG 11 (11.3.1). In this paper, we present the profile of the LUE across several territorial scales between 1990 and 2015, highlighting diverse development trajectories and the land take efficiency of different human settlements. Our results show that (i) the GHSL framework allows us to estimate LUE for the entire planet at several territorial scales, opening the opportunity of lifting the LUE indicator from its Tier II classification; (ii) the current formulation of the LUE is substantially subject to path dependency; and (iii) it requires additional spatially-explicit metrics for its interpretation. We propose the Achieved Population Density in Expansion Areas and the Marginal Land Consumption per New Inhabitant metrics for this purpose. The study is planetary and multi-temporal in coverage, demonstrating the value of well-designed, open and free, fine-scale geospatial information on human settlements in supporting policy and monitoring progress made towards meeting the SDGs.
Marcello Schiavina; Michele Melchiorri; Christina Corbane; Aneta Florczyk; Sergio Freire; Martino Pesaresi; Thomas Kemper. Multi-Scale Estimation of Land Use Efficiency (SDG 11.3.1) across 25 Years Using Global Open and Free Data. Sustainability 2019, 11, 5674 .
AMA StyleMarcello Schiavina, Michele Melchiorri, Christina Corbane, Aneta Florczyk, Sergio Freire, Martino Pesaresi, Thomas Kemper. Multi-Scale Estimation of Land Use Efficiency (SDG 11.3.1) across 25 Years Using Global Open and Free Data. Sustainability. 2019; 11 (20):5674.
Chicago/Turabian StyleMarcello Schiavina; Michele Melchiorri; Christina Corbane; Aneta Florczyk; Sergio Freire; Martino Pesaresi; Thomas Kemper. 2019. "Multi-Scale Estimation of Land Use Efficiency (SDG 11.3.1) across 25 Years Using Global Open and Free Data." Sustainability 11, no. 20: 5674.
Geo-information on settlements from Earth Observation offers a base for objective and scalable monitoring of the evolution of cities and settlements, including their location, extent and other attributes. In this work, we deploy the best available global knowledge on the presence of human settlements and built-up structures derived from Earth Observation to advance the understanding of the human presence on Earth. We start from a concept of Generalised Settlement Area to identify the Earth surface within which any built-up structure is present. We further characterise the resulted map by using an agreement map among the state of the art of remote sensing products mapping built-up areas or other strictly related semantic abstractions as urban areas or artificial surfaces. The agreement map is formed by a grid of 1 km2, where each cell is classified according to the number of EO-derived products reporting any positive occurrence of the abstractions related to the presence of built-up structures. The paper describes the characteristics of the Generalised Settlement Area, the differences in the agreement map across geographic regions of the world, and outlines the implications for potential users of the EO-derived products used in this study.
A. J. Florczyk; M. Melchiorri; J. Zeidler; C. Corbane; M. Schiavina; S. Freire; F. Sabo; P. Politis; T. Esch; M. Pesaresi. The Generalised Settlement Area: mapping the Earth surface in the vicinity of built-up areas. International Journal of Digital Earth 2019, 13, 45 -60.
AMA StyleA. J. Florczyk, M. Melchiorri, J. Zeidler, C. Corbane, M. Schiavina, S. Freire, F. Sabo, P. Politis, T. Esch, M. Pesaresi. The Generalised Settlement Area: mapping the Earth surface in the vicinity of built-up areas. International Journal of Digital Earth. 2019; 13 (1):45-60.
Chicago/Turabian StyleA. J. Florczyk; M. Melchiorri; J. Zeidler; C. Corbane; M. Schiavina; S. Freire; F. Sabo; P. Politis; T. Esch; M. Pesaresi. 2019. "The Generalised Settlement Area: mapping the Earth surface in the vicinity of built-up areas." International Journal of Digital Earth 13, no. 1: 45-60.
Data on global population distribution are a strategic resource currently in high demand in an age of new Development Agendas that call for universal inclusiveness of people. However, quality, detail, and age of census data varies significantly by country and suffers from shortcomings that propagate to derived population grids and their applications. In this work, the improved capabilities of recent remote sensing-derived global settlement data to detect and mitigate major discrepancies with census data is explored. Open layers mapping built-up presence were used to revise census units deemed as ‘unpopulated’ and to harmonize population distribution along coastlines. Automated procedures to detect and mitigate these anomalies, while minimizing changes to census geometry, preserving the regional distribution of population, and the overall counts were developed, tested, and applied. The two procedures employed for the detection of deficiencies in global census data obtained high rates of true positives, after verification and validation. Results also show that the targeted anomalies were significantly mitigated and are encouraging for further uses of free and open geospatial data derived from remote sensing in complementing and improving conventional sources of fundamental population statistics.
Sergio Freire; Marcello Schiavina; Aneta J. Florczyk; Kytt MacManus; Martino Pesaresi; Christina Corbane; Olena Borkovska; Jane Mills; Linda Pistolesi; John Squires; Richard Sliuzas. Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice. International Journal of Digital Earth 2018, 13, 61 -77.
AMA StyleSergio Freire, Marcello Schiavina, Aneta J. Florczyk, Kytt MacManus, Martino Pesaresi, Christina Corbane, Olena Borkovska, Jane Mills, Linda Pistolesi, John Squires, Richard Sliuzas. Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice. International Journal of Digital Earth. 2018; 13 (1):61-77.
Chicago/Turabian StyleSergio Freire; Marcello Schiavina; Aneta J. Florczyk; Kytt MacManus; Martino Pesaresi; Christina Corbane; Olena Borkovska; Jane Mills; Linda Pistolesi; John Squires; Richard Sliuzas. 2018. "Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice." International Journal of Digital Earth 13, no. 1: 61-77.
Data on land use and land cover (LULC) are a vital input for policy-relevant research, such as modelling of the human population, socioeconomic activities, transportation, environment, and their interactions. In Europe, CORINE Land Cover has been the only data set covering the entire continent consistently, but with rather limited spatial detail. Other data sets have provided much better detail, but either have covered only a fraction of Europe (e.g. Urban Atlas) or have been thematically restricted (e.g. Copernicus High Resolution Layers). In this study, we processed and combined diverse LULC data to create a harmonised, ready-to-use map covering 41 countries. By doing so, we increased the spatial detail (from 25 to one hectare) and the thematic detail (by seven additional LULC classes) compared to the CORINE Land Cover. Importantly, we decomposed the class ‘Industrial and commercial units’ into ‘Production facilities’, ‘Commercial/service facilities’ and ‘Public facilities’ using machine learning to exploit a large database of points of interest. The overall accuracy of this thematic breakdown was 74%, despite the confusion between the production and commercial land uses, often attributable to noisy training data or mixed land uses. Lessons learnt from this exercise are discussed, and further research direction is proposed.
Konštantín Rosina; Filipe Batista E Silva; Pilar Vizcaino; Mario Marín Herrera; Sérgio Freire; Marcello Schiavina. Increasing the detail of European land use/cover data by combining heterogeneous data sets. International Journal of Digital Earth 2018, 13, 602 -626.
AMA StyleKonštantín Rosina, Filipe Batista E Silva, Pilar Vizcaino, Mario Marín Herrera, Sérgio Freire, Marcello Schiavina. Increasing the detail of European land use/cover data by combining heterogeneous data sets. International Journal of Digital Earth. 2018; 13 (5):602-626.
Chicago/Turabian StyleKonštantín Rosina; Filipe Batista E Silva; Pilar Vizcaino; Mario Marín Herrera; Sérgio Freire; Marcello Schiavina. 2018. "Increasing the detail of European land use/cover data by combining heterogeneous data sets." International Journal of Digital Earth 13, no. 5: 602-626.
The presence of green spaces within city centres has been recognized as a valuable component of the city landscape. Vegetation provides a variety of benefits including energy saving, improved air quality, reduced noise pollution, decreased ambient temperature and psychological restoration. Evidence also shows that the amount of vegetation, known as ‘greenness’, in densely populated areas, can also be an indicator of the relative wealth of a neighbourhood. The ‘grey-green divide’, the contrast between built-up areas with a dominant grey colour and green spaces, is taken as a proxy indicator of sustainable management of cities and planning of urban growth. Consistent and continuous assessment of greenness in cities is therefore essential for monitoring progress towards the United Nations Sustainable Development Goal 11. The availability of multi-temporal greenness information from Landsat data archives together with data derived from the city centres database of the Global Human Settlement Layer (GHSL) initiative, offers a unique perspective to quantify and analyse changes in greenness across 10,323 urban centres all around the globe. In this research, we assess differences between greenness within and outside the built-up area for all the urban centres described by the city centres database of the GHSL. We also analyse changes in the amount of green space over time considering changes in the built-up areas in the periods 1990, 2000 and 2014. The results show an overall trend of increased greenness between 1990 and 2014 in most cities. The effect of greening is observed also for most of the 32 world megacities. We conclude that using simple yet effective approaches exploiting open and free global data it is possible to provide quantitative information on the greenness of cities and its changes over time. This information is of direct interest for urban planners and decision-makers to mitigate urban related environmental and social impacts.
Christina Corbane; Pesaresi Martino; Politis Panagiotis; Florczyk J. Aneta; Melchiorri Michele; Freire Sergio; Schiavina Marcello; Ehrlich Daniele; Naumann Gustavo; Kemper Thomas. The grey-green divide: multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer (GHSL). International Journal of Digital Earth 2018, 13, 101 -118.
AMA StyleChristina Corbane, Pesaresi Martino, Politis Panagiotis, Florczyk J. Aneta, Melchiorri Michele, Freire Sergio, Schiavina Marcello, Ehrlich Daniele, Naumann Gustavo, Kemper Thomas. The grey-green divide: multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer (GHSL). International Journal of Digital Earth. 2018; 13 (1):101-118.
Chicago/Turabian StyleChristina Corbane; Pesaresi Martino; Politis Panagiotis; Florczyk J. Aneta; Melchiorri Michele; Freire Sergio; Schiavina Marcello; Ehrlich Daniele; Naumann Gustavo; Kemper Thomas. 2018. "The grey-green divide: multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer (GHSL)." International Journal of Digital Earth 13, no. 1: 101-118.
Exposure is reported to be the biggest determinant of disaster risk, it is continuously growing and by monitoring and understanding its variations over time it is possible to address disaster risk reduction, also at the global level. This work uses Earth observation image archives to derive information on human settlements that are used to quantify exposure to five natural hazards. This paper first summarizes the procedure used within the global human settlement layer (GHSL) project to extract global built-up area from 40 year deep Landsat image archive and the procedure to derive global population density by disaggregating population census data over built-up area. Then it combines the global built-up area and the global population density data with five global hazard maps to produce global layers of built-up area and population exposure to each single hazard for the epochs 1975, 1990, 2000, and 2015 to assess changes in exposure to each hazard over 40 years. Results show that more than 35% of the global population in 2015 was potentially exposed to earthquakes (with a return period of 475 years); one billion people are potentially exposed to floods (with a return period of 100 years). In light of the expansion of settlements over time and the changing nature of meteorological and climatological hazards, a repeated acquisition of human settlement information through remote sensing and other data sources is required to update exposure and risk maps, and to better understand disaster risk and define appropriate disaster risk reduction strategies as well as risk management practices. Regular updates and refined spatial information on human settlements are foreseen in the near future with the Copernicus Sentinel Earth observation constellation that will measure the evolving nature of exposure to hazards. These improvements will contribute to more detailed and data-driven understanding of disaster risk as advocated by the Sendai Framework for Disaster Risk Reduction.
Daniele Ehrlich; Michele Melchiorri; Aneta J. Florczyk; Martino Pesaresi; Thomas Kemper; Christina Corbane; Sergio Freire; Marcello Schiavina; Alice Siragusa. Remote Sensing Derived Built-Up Area and Population Density to Quantify Global Exposure to Five Natural Hazards over Time. Remote Sensing 2018, 10, 1378 .
AMA StyleDaniele Ehrlich, Michele Melchiorri, Aneta J. Florczyk, Martino Pesaresi, Thomas Kemper, Christina Corbane, Sergio Freire, Marcello Schiavina, Alice Siragusa. Remote Sensing Derived Built-Up Area and Population Density to Quantify Global Exposure to Five Natural Hazards over Time. Remote Sensing. 2018; 10 (9):1378.
Chicago/Turabian StyleDaniele Ehrlich; Michele Melchiorri; Aneta J. Florczyk; Martino Pesaresi; Thomas Kemper; Christina Corbane; Sergio Freire; Marcello Schiavina; Alice Siragusa. 2018. "Remote Sensing Derived Built-Up Area and Population Density to Quantify Global Exposure to Five Natural Hazards over Time." Remote Sensing 10, no. 9: 1378.
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.
Michele Melchiorri; Aneta J. Florczyk; Sergio Freire; Marcello Schiavina; Martino Pesaresi; Thomas Kemper. Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer. Remote Sensing 2018, 10, 768 .
AMA StyleMichele Melchiorri, Aneta J. Florczyk, Sergio Freire, Marcello Schiavina, Martino Pesaresi, Thomas Kemper. Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer. Remote Sensing. 2018; 10 (5):768.
Chicago/Turabian StyleMichele Melchiorri; Aneta J. Florczyk; Sergio Freire; Marcello Schiavina; Martino Pesaresi; Thomas Kemper. 2018. "Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer." Remote Sensing 10, no. 5: 768.