K. Steinnocher, A. De Bono, B. Chatenoux, D. Tiede, L. Wendt:
"Estimating urban population patterns from stereo-satellite imagery.";
European Journal of Remote Sensing, Vol. 52 (2019), S. 12 - 25.

With more than half of the worldīs population living in towns and cities, urban areas get more
and more into the focus of humanitarian relief organisations such as ICRC, Médecins sans
Frontières (MSF), or SOS Childrenīs Villages. A key information required for almost any
intervention is an estimation of the population numbers for the towns and cities where
these organisations operate in. As census data are usually not available or outdated, population
numbers have to be estimated by alternative methods such as remote sensing. To do
that built-up densities are estimated from high-resolution image data and population numbers
are disaggregated proportional to the densities in a top-down approach. Alternatively,
population counts per density unit can be aggregated following a bottom-up approach. Both
approaches were tested applying normalised Digital Surface Models (nDSM) derived from tristereo
Pléiade images for Salzburg, Austria and Port-au-Prince, Haiti; the former for testing the
quality and stability of the approach in a well-known setting, the latter for testing the
approach in a critical environment. Key findings are that satellite-derived nDSMs provide
sufficient accuracy for estimating population distributions, as long as reliable information is
available for the separation of residential and non-residential urban areas.

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