Global 0.05° Grid-Based Dataset of Keyhole Imagery with Spatio-Temporal Indicators (1960–1984)
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.
Authors
- HuanJun Liu
- Hao Li (ORCID: https://orcid.org/0000-0002-8484-2058)
- Jiaheng Wang (ORCID: https://orcid.org/0000-0002-5884-5933)
- Jinyu Sun
- Xinle Zhang (ORCID: https://orcid.org/0009-0003-9268-3880)
- Tao Wang
- Mingyuan Deng
- Mulin Shan
Institutions
- Liaocheng University (CN)
- Chinese Academy of Sciences (CN)
- Northeast Institute of Geography and Agroecology (CN)
- Jilin Agricultural University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2026-02-17
- DOI
- https://doi.org/10.1038/s41597-026-06866-4
- Primary Topic
- Remote-Sensing Image Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00