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January 24, 20261 citations

Homogenization of Northern Belgian landscapes through centuries of reclamation, agricultural transition, and urbanization.

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LKLuc De KeersmaekerPRPieter RoggemansLPLien Poelmans

Key Points

  • The central aim is to quantify historical land-use changes in northern Belgium from 1774 to 2022.
  • Utilized deep learning image segmentation (GeoAI) on historical maps.
  • Analyzed three periods of landscape change: reclamation, agricultural transition, and urbanization.
  • Generated high-resolution historical land-use maps.
  • Reclamation from 1774-1873 halved the area of natural landscapes.
  • Agricultural transition between 1873-1969 doubled areas of grassland and orchard.
  • Urbanization from 1969-2022 reduced agricultural land-use significantly.

Abstract

We quantify historical land-use with deep learning image segmentation (GeoAI), applied to tiled historical maps, and identify 3 successive drivers of long-term (1774-2022) landscape transformation in northern Belgium (13,800 km2). Between 1774 and 1873, reclamation halved the area of long-established forests, heathland, marshland, and the intertidal zone, i.e. natural and semi-natural land-use. Agricultural transition by globalization was the main driver in the next time interval (1873-1969), as the area of grassland and orchard doubled at the expense of arable land. Urbanization marked the last time interval (1969-2022) and reduced agricultural land-use. The reclamation of fertile soils first increased the association of land-use with soil, but after 1873 this association progressively weakened and land-use interspersed. Here, we demonstrate that GeoAI can generate high-resolution area-wide historical land-use maps to study the extent and rate of landscape transformation, which in our case resulted in the homogenization of previously distinct landscapes.

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Cite This Study

Keersmaeker et al. (2026) studied this question.

synapsesocial.com/papers/6974602bbb9d90c67120a1dahttps://doi.org/10.1038/s41467-026-68594-y
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