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

## TL;DR

This paper introduces a global dataset of high-resolution Keyhole satellite imagery from 1960–1984, organized to help researchers easily find and use historical images.

## Contribution

A new global grid-based dataset of Keyhole imagery with spatio-temporal indicators to facilitate image selection and integration.

## Key findings

- The dataset includes metadata indicators like coverage count, acquisition dates, and resolution classes.
- It enables researchers to assess temporal suitability and combine historical images with modern satellites.
- The dataset helps identify which non-free images to purchase if free images are insufficient for research.

## 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.