Towards an end-to-end airborne remote-sensing system for post-hazard assessment of damage to hyper-critical infrastructure: research progress and needs

The objective of this article is to synthesize research findings and requirements pertaining to development of time-sensitive remote-sensing systems (TSRSS) that support decision-making pertaining to post-hazard assessment of damage to what we define as hypercritical infrastructure (HCI), based on an aerial imaging approach known as repeat station imaging (RSI). The following TSRSS components are addressed and related findings are reported: (1) understanding information requirements of emergency managers pertaining to damage of HCI; (2) flight planning and data capture requirements for supporting bi-temporal RSI pairs; (3) automatic image registration and shadow classification and normalization routines applied to RSI pairs; (4) damage detection and delineation approach that exploits simple temporal differences in image brightness to automatically, reliably, and robustly delineates new cracks associated with damage; and (5) rapid data and information transfer to emergency managers. The highest priority follow-on research topics are: (1) integrating small unmanned aerial systems (sUAS) with the RSI approach, while enabling multiple view perspectives other than vertical (i.e. nadir pointing) and (2) developing and testing of machine learning routines for automatic identification of damage features from RSI pairs, particularly those captured from integrated sUAS-RSI.