2 Thirdly, systematic 3D analyses of horizontal and vertical settlement extent are often derived from between a few hundred to a thousand selected city regions (Jedwab et al., 2021b; Lall et al., 2021; Li et al., 2022; Zhou et al., 2022). The resulting empirical evidence therefore tends to favor the characteristics of urban areas, and large cities among them, focusing on developed economies rather than developing economies where most of the data needs are.

To address these limitations, this research focuses on several major improvements. Based on a unique combination of area-wide information provided by the World Settlement Footprint 3D (WSF3D) raster layer (Esch et al., 2022), with the exceptional precision of the Emporis point database of high-rise buildings (Emporis, 2022), a new dataset (WSF3Dv2) is generated with detailed information on the area, height, and volume of the building stock worldwide today. Since the data does not rely on local administrative data, the low data capacity of less developed economies does not constrain our analysis. At the same time, our data is most useful where alternative sources of data are limited, which is the case of poorer economies.

This research derives information on building area and height with a geometric resolution of 12m*12m with global coverage. Biases in terms of income status (e.g., from over-relying on data from developed economies), geographic region (e.g., driven by selection of sample regions) or settlement type (e.g., megacities) are avoided and completeness, representativeness, and general validity of the analyses and findings are assured. To meet requirements of German data security regulations (Palacios-Lopez et al., 2021) and for an open dissemination of the novel WSF3Dv2 data and derived results, all outcomes are finally provided in the form of zonal statistics (building area, building height, and building volume) aggregated to a grid of 90m*90m.

We then use the data to investigate the role of economic development in construction. National building stocks per capita increase convexly with income. Small differences are observed between low-income and lower-middle-income economies and it is only when countries become upper-middle-income economies (i.e., reach a per capita GDP of _∼_ $4,000) that space consumption per capita significantly increases with income. Next, we rely on the globally estimated volume-income relation to quantify global construction needs.

Developing nations in Asia and Latin America & the Caribbean (LAC) respectively account for _∼_ 60% and _∼_ 20% of _current_ global construction needs (South Asia explains two-thirds of developing Asia’s gap). African nations do not have large construction gaps because they have low incomes, and little variation in space consumption per capita is observed at such incomes.

Developing Asia then accounts for about 75% of _future_ , growth-driven global construction needs when considering a horizon of five years. In developing Asia, the effects of population growth and income growth compound each other. African nations, having low incomes and low economic growth rates, do not appear prominently in the rankings despite their fast population