Enhancing GHSL Population Grids Using Hexagon KH-9 Built-up Data: Refining 1970s Rural and Peri-Urban Distributions in Istanbul

TL;DR

This paper introduces a novel method that combines declassified reconnaissance imagery with census data to improve the accuracy of historical population grids, especially in rural and peri-urban areas, using Istanbul as a case study.

Contribution

It is the first to integrate Hexagon KH-9 imagery into gridded population mapping, enhancing historical population distribution accuracy in data-scarce regions.

Findings

Hexagon KH-9 imagery improves rural and peri-urban population representation.

Combining imagery with census data refines population distribution accuracy.

The method significantly reduces misallocation of populations in undeveloped areas.

Abstract

Accurate reconstruction of historical population distributions from the 1970s to the 1990s remains a significant limitation in global gridded population products due to coarse built-up data and limited census records. This study is, to our knowledge, the first to integrate declassified Hexagon KH-9 reconnaissance imagery into gridded population mapping. We enhance the GHS-POP framework by combining segmented built-up land cover from the HexaLCSeg dataset, derived from 1977 KH-9 imagery, with geocoded settlement-level census data to construct high-resolution historical population grids. Applied to Arnavutkoy and Cekmekoy in Istanbul for the period 1975-1990, we evaluate three dasymetric approaches, including a standard GHSL baseline, a Hexagon-enhanced workflow, and a fully integrated model incorporating local census records. Pixel-wise and zonal analyses show that GHSL misallocates populations to historically undeveloped regions, while the Hexagon-derived dataset substantially improves the representation of fragmented rural and peri-urban areas often missing from global products. Incorporating settlement-level LAU-2 census data further refines spatial population distribution. The results demonstrate that combining historical reconnaissance imagery with high-resolution census data improves the accuracy of historical population grids, and given the global coverage of declassified missions, this methodology offers significant potential for reconstructing historical population patterns in data-scarce regions worldwide.