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

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Authors: Tao Wang, Xinle Zhang, Mulin Shan, Mingyuan Deng, Jiaheng Wang, Huanjun Liu, Hao Li, Jinyu Sun
Cited by: 0
References: 30

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.

Fields of Study & Subjects

Satellite Image Processing and Photogrammetry Remote Sensing and Land Use Remote Sensing in Agriculture

Publication details

Journal / source
Scientific Data
Volume
13
Issue
1
Publication date
17 February 2026
Language
EN