Abstract
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.
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Data availability
The data are available on Figshare (https://doi.org/10.6084/m9.figshare.30017944)28.
Code availability
The processing codes are available on Figshare (https://doi.org/10.6084/m9.figshare.30017944)28.
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Acknowledgements
This work was jointly supported by the National Key R&D Plan of China (grant no. 2024YFD1501100) and Doctoral Startup Foundation of Liaocheng University (318052031). To improve clarity and readability, parts of the manuscript were polished with the assistance ofartificial intelligence (AI)–based language tools.
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Hao Li and Jinyu Sun designed the research plan. Tao Wang, Hao Li and Xinle Zhang designed the research plan and wrote the paper. Mulin Shan, Mingyuan Deng and Jiaheng Wang contributed to data collection and the analysis of the results. Huanjun Liu and Jinyu Sun reviewed the draft.
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Wang, T., Zhang, X., Shan, M. et al. Global 0.05° Grid-Based Dataset of Keyhole Imagery with Spatio-Temporal Indicators (1960–1984). Sci Data (2026). https://doi.org/10.1038/s41597-026-06866-4
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DOI: https://doi.org/10.1038/s41597-026-06866-4
