Title: Multi-scale estimation of Land Use Efficiency (SDG 11.3.1) across 25 years using Global Open and Free Data
Authors: SCHIAVINA MARCELLOMELCHIORRI MICHELECORBAN CHRISTINAFLORCZYK ANETACARNEIRO FREIRE SERGIO MANUELPESARESI MARTINOKEMPER THOMAS
Citation: SUSTAINABILITY vol. 11 no. 20 p. 5674
Publisher: MDPI
Publication Year: 2019
JRC N°: JRC117902
ISSN: 2071-1050 (online)
URI: https://www.mdpi.com/2071-1050/11/20/5674
https://publications.jrc.ec.europa.eu/repository/handle/JRC117902
DOI: 10.3390/su11205674
Type: Articles in periodicals and books
Abstract: 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.
JRC Directorate:Space, Security and Migration

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