Quantifying Disaster Debris Faster with Remote Sensing
The Challenge: After a major disaster like a hurricane, the sheer volume of debris can be overwhelming, choking roads, slowing recovery, and costing billions to manage. For emergency managers, planning an effective cleanup operation depends on one critical question: How much debris is there? Existing prediction models are often inaccurate, and getting real-world data is difficult, leaving communities struggling to allocate the right number of trucks, personnel, and disposal sites.
A researcher sets up a GNSS antennae amid debris piles to collect spatial and georeferencing data.
A New Approach: To tackle this data gap, a research team from Louisiana State University set out to directly compare different remote sensing technologies for quantifying disaster debris in the aftermath of Hurricane Ida in 2021. With support from NSF, the team deployed to the hard-hit community of Grand Isle, Louisiana. The RAPID Facility provided crucial instrumentation for the mission, including a high-resolution Terrestrial Laser Scanner (TLS) and a survey-grade Unmanned Aerial Vehicle (UAV), which the team used to collect data at a Temporary Debris Management Site (TDMS).
Data & Discovery: At the debris site, the researchers created precise 3D models of the massive debris piles using both the ground-based TLS and the aerial UAV. By comparing the results, they were able to conduct a first-of-its-kind, head-to-head evaluation of the technologies in a real-world disaster zone. The team discovered that while both tools could produce accurate volume calculations, the UAV offered a more practical and efficient solution. The UAV provided more complete coverage of the debris piles from the air, was less affected by ground obstructions, and had significantly lower equipment costs and computational demands than the higher-resolution TLS. In total, the team calculated that approximately 8,994 cubic meters of debris had been collected at the site in the 46 days following the hurricane.
Impact: This RAPID-supported research provides a critical framework for disaster response agencies, offering clear guidance on which remote sensing tools are best suited for different debris quantification tasks. The study demonstrates that UAVs represent a "sweet spot" of accuracy, cost, and efficiency for measuring debris at collection sites, providing a field-tested workflow that communities can adopt to get rapid, data-driven estimates. By making debris quantification faster and more accessible, this work helps fill a critical knowledge gap, enabling more accurate pre-disaster planning and more efficient post-disaster cleanup operations, ultimately helping communities get back to normal sooner.
Citation: Bekkaye, J. H., & Jafari, N. H. (2024). Application and comparison of remote sensing techniques for data-driven disaster debris quantification. International Journal of Remote Sensing, 45(8), 2808-2831.