Understanding Non-optical Remote-sensed Images: Needs, Challenges and Ways Forward

TL;DR

This paper discusses the increasing importance of non-optical remote sensing images, highlighting unique challenges and proposing pathways toward real-time understanding systems to support disaster management, agriculture, and sustainable development.

Contribution

It provides a comprehensive overview of the needs, challenges, and potential future directions for real-time understanding of non-optical remote-sensed images, an area less explored compared to optical images.

Findings

Non-optical images are crucial for disaster and agricultural management.

Processing non-optical images presents unique challenges compared to optical images.

Current approaches need to evolve for reliable real-time understanding.

Abstract

Non-optical remote-sensed images are going to be used more often in man- aging disaster, crime and precision agriculture. With more small satellites and unmanned air vehicles planning to carry radar and hyperspectral image sensors there is going to be an abundance of such data in the recent future. Understanding these data in real-time will be crucial in attaining some of the important sustain- able development goals. Processing non-optical images is, in many ways, different from that of optical images. Most of the recent advances in the domain of image understanding has been using optical images. In this article we shall explain the needs for image understanding in non-optical domain and the typical challenges. Then we shall describe the existing approaches and how we can move from there to the desired goal of a reliable real-time image understanding system.