Application and comparison of remote sensing techniques for data-driven disaster debris quantification.

Effective disaster debris management requires reasonable predictions pre-hazard and estimates post-hazard of debris for a community to get back to normal sooner. However, there is a lack of data related to post-disaster waste quantities that could validate and improve debris predictions. This knowledge gap can be addressed by using remote sensing technology to quantify disaster debris promptly following a hazard. This study aimed to demonstrate and compare multiple remote sensing tools available for quantifying disaster debris using post-disaster data collected following Hurricane Ida. The tools used in this study are satellite imagery, emergency response airborne imagery, unmanned aerial vehicles (UAVs), and terrestrial laser scanning (TLS). We found that satellite imagery is useful for quantifying vegetative debris generation and transportation across vast areas, however it is often limited by spatial and temporal resolutions. Emergency response airborne imagery, collected within days following the hazard, is well-suited for quantifying transported vegetative debris and can assist debris clearance of emergency service routes across large areas, although it can be limited spatially and temporally to the interests of the acquiring agency. UAVs and TLS can provide precise volumes of debris but UAVs may be a better option due to their lower cost and computational demand. Guidance is provided for selecting a remote sensing tool based on the desired application and available resources, which can assist decision making for disaster waste managers. [ABSTRACT FROM AUTHOR]