From Urban Extent to Urban Fabric : Remote Sensing Evidence for SDG 11
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Two neighbourhoods can have same population density, urban extent but different urban fabric, should they be treated in a similar way in policy? Satellite imagery and remote sensing analysis can show which has high-rise, well-structured blocks and the other with dense, low-rise informal fabric. Remotely sensed information can therefore strengthen the implementation of Sustainable Development Goal (SDG) 11 by making horizontal and vertical urban change visible, measurable, and comparable across space and time. When land cover, building footprints, building height, population and construction materials information are analysed together, they provide a comprehensive account of how the built environment is expanding, densifying and consuming land and other resources. Remote sensing can be used to analyse exposure of residents to climate hazards, and create opportunities for more efficient, equitable, and resilient urban development. This enables governments to monitor densification, housing conditions, land-use efficiency and exposure to hazards in a consistent and comparable way. This combined evidence-based analysis is particularly valuable in data-poor or crisis-affected settings where cadastral records, building stock inventories, or survey data is incomplete, outdated, or inaccessible. By linking urban form typologies to building archetypes, the data can be used to estimate current material use, forecast future materials demand and debris generation. In addition, through modelling different development scenarios, we can incorporate low-carbon and circular construction strategies. The brief outlines how these capabilities can be integrated into national and sub-national SDG 11 monitoring systems and urban-planning workflows. Introduction SDG 11 calls for cities that are inclusive, safe, resilient and sustainable, requiring spatially explicit and reliable data on urban conditions (United Nations, 2015; UN-Habitat, n.d.). Conventional urban data systems often lack spatial resolution, temporal frequency, or territorial coverage needed for policy action (Angel et al., 2011). Many cadastral datasets are outdated or inconsistent, limiting governments’ ability to monitor housing quality, land-use efficiency, exposure to hazards and environmental performance (UN-Habitat, 2021). This challenge is especially acute in rapidly urbanizing or climate-vulnerable settings, where remote sensing provides a consistent and scalable complement to official statistics (Andersson & Crnojevic, 2025). This brief introduces an integrated approach combining land cover, building footprints, building height, population and construction-materials information to move from simple urban extent mapping toward a more policy-relevant understanding of the built environment. What remotely sensed information adds to SDG 11 monitoring Four complementary information layers are particularly important for understanding the built environment.