After The Storm: Assessing Hurricane Damage Using Remote Sensing Technology

By John Oncea, Editor

Assessing hurricane damage quickly and accurately is critical but can be difficult with conventional field surveying methods. Now, a LiDAR-based system is improving the process.

Hurricanes, along with tropical storms, are the greatest weather-related threat to the Florida Keys and surrounding coastal waters, according to NOAA. With only one major highway in and out of the Keys, it takes almost two full days to evacuate the southernmost city in the continental U.S. This makes the accurate prediction of hurricanes a life-saving job, something NOAA researchers are constantly trying to improve.

According to the Atlantic Oceanographic & Meteorological Laboratory, NOAA relies on five methods to improve hurricane track and intensity forecasts, including the development of next-generation tropical cyclone models, collocating ocean observing instruments, improving small uncrewed aircraft systems, the development of new instruments, and flying aircraft further east to study how storms begin.

The 2024 hurricane season – running from June 1 to November 30 – is predicted to be worse than most with an 85% chance of an above-normal season, a 10% chance of a new-normal season, and a 5% chance of a below-normal season. “NOAA is forecasting a range of 17 to 25 total named storms (winds of 39 mph or higher). Of those, 8 to 13 are forecast to become hurricanes (winds of 74 mph or higher), including 4 to 7 major hurricanes (category 3, 4, or 5; with winds of 111 mph or higher). Forecasters have a 70% confidence in these ranges.”

Predicting hurricanes is critical and so, too, is rapidly assessing damage for rescue, recovery, and emergency planning after the storm hits. With that in mind, Florida Atlantic University has developed a novel technique that uses aerial imagery data and LiDAR to provide high-resolution assessments of detailed hurricane damage.

Assessing Hurricane Damage Through Field Reconnaissance

Traditionally, assessing hurricane damage was done through field reconnaissance – visually capturing and cataloging damage information on-site after the hurricane event. This approach, according to Louisiana State University, involves the following key aspects:

• Surveyors physically visit the affected areas and buildings to conduct visual inspections and document the damage conditions.
• Data is collected using paper and pen, taking notes, and filling out pre-made forms to record observations on the level and type of damage sustained by structures.
• Rapid assessments aim to quickly gather an overall impression of the degree of damage, while detailed assessments involve more comprehensive evaluations.

While this allows surveyors to document perishable data about the building’s condition before repairs are made it does come with some limitations, including data that is not systematically categorized, geo-located, or tied directly to hazard intensity, limiting its usefulness for analysis and modeling. It also can be time consuming, labor intensive, and puts surveyors conducting on-site assessments in harm’s way.

To address these issues, field reconnaissance is increasingly being combined with remote sensing techniques like aerial imagery and LiDAR to enhance damage assessment capabilities. This integrated approach leverages the strengths of both methods for more comprehensive and efficient post-hurricane damage evaluation.

Adding Remote Sensing To Hurricane Assessment

Using a LiDAR-based system to assess hurricane damage is revolutionizing the process by enabling rapid and accurate damage assessment. Mobile LiDAR systems use laser scanners mounted on vehicles to rapidly scan and collect millions of precise 3D measurements of buildings, roads, utilities, and more, creating highly detailed 3D virtual reality models of the impacted areas.

For instance, after Hurricane Sandy researchers from Rutgers University used mobile LiDAR to scan around 80 miles of devastated coastal areas in New York and New Jersey. The high-resolution 3D data helped analyze how different infrastructures reacted to the hurricane’s winds and flooding.

Compared to traditional damage assessments involving preliminary evaluation followed by reconstruction surveying, mobile LiDAR cuts the time in half by concurrent mapping and producing 3D condition data. Machine learning techniques are now being combined with LiDAR data from drones/UAVs to further automate and accelerate post-hurricane damage assessment of buildings and infrastructure.

This rapid LiDAR-based damage assessment provides critical data for efficient demolition, recycling, reconstruction planning, and improving disaster preparedness. It establishes a high-resolution pre-disaster baseline for communities to reference after future events.

The integration of mobile LiDAR scanning, aerial LiDAR, and machine learning is transforming post-hurricane damage assessment from a lengthy manual process to a highly automated and expedited system for data-driven recovery and future planning.

Detailing Hurricane Ian With Remote Sensing

“Category 4 Hurricane Ian made landfall in Florida’s Lee County on Sept. 28, 2022, battering the region with wind speeds of 155 miles per hour and storm surge up to 13 feet – the highest storm surge documented in Southwest Florida in the past 150 years,” writes Florida Atlantic University (FAU).

According to the National Hurricane Center, “Ian was responsible for over 150 direct and indirect deaths and over $112 billion in damage, making it the costliest hurricane in Florida’s history and the third costliest in United States history.”

Hurricane Ian wreaked havoc on Florida with heavy rainfall leading to catastrophic flooding, especially in areas such as Fort Myers and Naples. Some regions experienced up to 20 inches of rain and many buildings, particularly in coastal communities, were either heavily damaged or destroyed. Infrastructure, including bridges and roads, also was severely affected.

In terms of intensity, damage, and fatalities, Hurricane Ian stands alongside some of the most notorious hurricanes in U.S. history, such as Hurricane Katrina (2005), Hurricane Michael (2018), and Hurricane Harvey (2017). Its impact highlighted the vulnerability of coastal and low-lying areas to powerful storms and underscored the importance of robust disaster preparedness and resilient infrastructure.

FAU, using aerial imagery data and LiDAR, “identified the hardest-hit areas of Southwest Florida’s Estero Island and estimated the extent of structural damage. Researchers also compared pre- and post-storm structural or morphological changes to the beach. The study is the first to apply an advanced multi-faceted approach that links damage assessment to post-storm change in the structure of barrier islands.”

The study, published in the Journal of Marine Science and Engineering, found a total of 2,427 structures on Estero Island were affected by Hurricane Ian, with 170 structures suffering extensive damage. Only one structure in the study area was classified as “not affected.” Using data from the Lee County tax appraiser, researchers estimated the total assessed value of the heavily damaged structures at more than $200 million.

Overall, 734 buildings had 30 to 50 percent structural damage, most of which were single-family and multi-unit residences. Researchers identified 158 buildings that were severely damaged with partial or complete roof failure.

The highest percentage of damaged structures occurred on the central and northern portions of the island, where most of the structures were single-family and multi-family residences. Most of the structures that experienced 0 to 30 percent damage were classified as low-rise condominiums (three stories or less), commercial shopping centers, and stores. Among the “severely damaged” and “destroyed” structures were seven mobile home subdivisions.

“Employing this advanced technology of aerial imagery and airborne LiDAR enabled us to collect extensive data from Hurricane Ian’s aftermath and analyze large-scale datasets rather quickly,” said Tiffany Roberts Briggs, Ph.D., senior author, chair and an associate professor in the Department of Geosciences within FAU’s Charles E. Schmidt College of Science. “We found no correlation between the ground elevation or year built for the extent of damages in this analysis, which emphasizes the role of the extreme inundation and the importance of other factors contributing to vulnerability. Results from our study can help improve disaster planning by developing new policies and guidelines for coastal development in some of the most vulnerable and storm-exposed areas.”

“Although our study focused on Estero Island, this new remote sensing approach is generalizable,” said Diana Mitsova, Ph.D., corresponding author, chair and professor, FAU Department of Urban and Regional Planning within the Charles E. Schmidt College of Science and an affiliate professor, FAU Department of Geosciences. “As this technology continues to advance and becomes more readily available, it will offer a broad range of high-resolution coverage that can help prioritize emergency response efforts immediately following catastrophic natural disasters and other events.”