Event-Based Vision in Space: Applications, Trends, and Future Directions

2026-05-31

AI Summary

Traditional spaceborne optical sensors are hindered by motion blur, high power consumption, and data redundancy, limiting their efficacy for efficient Earth observation. This work systematically reviews recent advances in event-based cameras for spaceborne remote sensing and introduces, for the first time, a four-dimensional classification framework tailored to space applications—encompassing high-speed atmospheric observation, environmental change detection, on-orbit intelligent processing, and geospatial modeling—to underscore the transformative potential of event vision as a new paradigm in remote sensing. Leveraging inherent characteristics such as asynchronous sensing, neuromorphic engineering, high dynamic range imaging, and microsecond-level temporal resolution, this technology substantially enhances observational efficiency while reducing both energy consumption and data volume, thereby offering a promising pathway toward sustainable space exploration.

Abstract

Earth Observation (EO) is undergoing a significant transformation driven by the deployment of novel sensing technologies. Traditional frame-based optical sensors often struggle with motion blur, high power consumption, and extreme data redundancy in challenging orbital environments. In contrast, event-based sensors, also known as neuromorphic cameras, offer a bio-inspired asynchronous approach. By capturing only local illumination changes, they provide microsecond temporal resolution, an extremely high dynamic range, and exceptional energy efficiency. Although the use of these sensors is rapidly expanding from terrestrial systems to orbital platforms, the scientific literature surrounding their space-based applications remains heavily fragmented. To bridge this gap, this article presents a comprehensive review of the state-of-the-art in event-based vision in the space domain. Based on the retrieved literature, we introduce a taxonomy structured around four primary domains: 1) atmospheric and high-speed observation; 2) environmental monitoring and change detection; 3) operational support and onboard processing; and 4) geospatial modeling and predictive analysis. As a result, this survey highlights that neuromorphic engineering is far more than a supplementary imaging technique; it is a paradigm shift that can be used to directly address critical bottlenecks in modern remote sensing and sustainable space exploration.

Problem

• event-based vision
• space applications
• neuromorphic cameras
• Earth Observation
• remote sensing

Innovation

• event-based vision
• neuromorphic cameras
• space applications
• remote sensing
• asynchronous sensing