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<p>The American satellite reconnaissance program (Keyhole imagery) is serving as a significant data source for geoscience research because of its high-resolution and early temporal coverage, while lack of spatial and temporal description of its uneven distribution could hinder researchers from selecting/accessing appropriate the Keyhole images. Here we introduce a global grid–based dataset that organizes declassified U.S. Keyhole imagery (1960–1984) for direct reuse, built on a global equal-area sinusoidal grid. This dataset standardizes scene metadata and provides indicators designed to inform study design and data integration: coverage count (how often a place was imaged), unique acquisition dates (temporal sampling richness), first/last observation year (temporal bounds), observation span (duration), peak observation year and a three-year window (temporal concentration), resolution class (C1–C3), temporal-coverage class across five five-year intervals, and resolution-coverage class (A–G) for multi-scale availability. This dataset enables users to quickly locate usable scenes, assess temporal suitability, combine historical images with modern satellites, and determine which non-free images to purchase if free images were unsuitable for their research.</p>

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Global 0.05° Grid-Based Dataset of Keyhole Imagery with Spatio-Temporal Indicators (1960–1984)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月17日

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  • Tao Wang,
  • Xinle Zhang,
  • Mulin Shan,
  • Mingyuan Deng,
  • Jiaheng Wang,
  • Huanjun Liu,
  • Hao Li,
  • Jinyu Sun

摘要

The American satellite reconnaissance program (Keyhole imagery) is serving as a significant data source for geoscience research because of its high-resolution and early temporal coverage, while lack of spatial and temporal description of its uneven distribution could hinder researchers from selecting/accessing appropriate the Keyhole images. Here we introduce a global grid–based dataset that organizes declassified U.S. Keyhole imagery (1960–1984) for direct reuse, built on a global equal-area sinusoidal grid. This dataset standardizes scene metadata and provides indicators designed to inform study design and data integration: coverage count (how often a place was imaged), unique acquisition dates (temporal sampling richness), first/last observation year (temporal bounds), observation span (duration), peak observation year and a three-year window (temporal concentration), resolution class (C1–C3), temporal-coverage class across five five-year intervals, and resolution-coverage class (A–G) for multi-scale availability. This dataset enables users to quickly locate usable scenes, assess temporal suitability, combine historical images with modern satellites, and determine which non-free images to purchase if free images were unsuitable for their research.