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Updated: Feb 19, 2026

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
Published on: April 18, 2025
Global 0.05° Grid-Based Dataset of Keyhole Imagery with Spatio-Temporal Indicators (1960-1984)
Tao Wang1, Xinle Zhang2, Mulin Shan1
1School of Geography and Environment, Liaocheng University, Liaocheng, 252059, China.
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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