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<p>The “Black Road” at Treblinka is a c. 2-km paved route of exceptional historical and memorial significance, linked to the functioning of the camps and later post-war transformations of the landscape. This study presents an integrated, predominantly non-invasive workflow for documenting and supporting the protection of this sensitive memory site, combining archival research, high-resolution UAV survey, AI-assisted surface segmentation, targeted archaeological test excavations, and chemical analyses. A corridor UAV survey produced a very high-resolution orthomosaic (c. 1.6 mm/pixel), used to create a spatial inventory of pavement elements, including reused matzevot visible within the structure. AI-based segmentation (SAM, ViT-H), followed by expert verification in GIS, enabled detailed mapping while limiting direct intervention. The study provides a practical framework for conservation planning, site management, ethically informed interpretation, and future monitoring of road preservation, while supporting an alternative access route for vehicles and pedestrians to reduce mechanical pressure on the historic road surface.</p>

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Predominantly non-invasive inventory and preservation-oriented documentation of the “Black Road” in Treblinka

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月25日

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  • Sebastian Różycki,
  • Jędrzej Proch,
  • Paulina Zachar,
  • Szymon Lenarczyk,
  • Łukasz Wilk

摘要

The “Black Road” at Treblinka is a c. 2-km paved route of exceptional historical and memorial significance, linked to the functioning of the camps and later post-war transformations of the landscape. This study presents an integrated, predominantly non-invasive workflow for documenting and supporting the protection of this sensitive memory site, combining archival research, high-resolution UAV survey, AI-assisted surface segmentation, targeted archaeological test excavations, and chemical analyses. A corridor UAV survey produced a very high-resolution orthomosaic (c. 1.6 mm/pixel), used to create a spatial inventory of pavement elements, including reused matzevot visible within the structure. AI-based segmentation (SAM, ViT-H), followed by expert verification in GIS, enabled detailed mapping while limiting direct intervention. The study provides a practical framework for conservation planning, site management, ethically informed interpretation, and future monitoring of road preservation, while supporting an alternative access route for vehicles and pedestrians to reduce mechanical pressure on the historic road surface.