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This project contains imagery collected from uncrewed aircraft system (UAS) flights over three barrier islands, Fort Myers Beach (FMB), San Carlos (SC), and Sanibel Island (SI), that are near Fort Myers, Florida, following Hurricane Ian. These barrier islands had substantial impacts from the hurricane, including the destruction of many residences and infrastructure, coastal degradation, and other environmental impacts. The imagery here was collected using a low-flying fixed-wing UAS with a high-resolution camera system that simultaneously collected oblique and nadir images from five lenses. The raw data set is very comprehensive and very dense. The extent of the collected data can be seen in the Hazmapper map. The data was processed into 3D models using structure from motion. The resulting 3D models have amazing damage detail and are measurement quality. They can be used to fully characterize damage to buildings, infrastructure, and the natural environment. The complete models are available here, with one model developed for each UAS flight (18 total flights). However, the complete models are very large data sets and require significant GPU power to open and manipulate. Thus, the data set is also divided into “tiled” areas on a 300-meter grid. Each tiled area is provided in both a full-resolution 3D model and a reduced-resolution preview that can be used for quick inspection. The tiles are named and distributed as shown here: https://arcg.is/19TLr5. The abbreviations for Fort Myers Beach (FMB), San Carlos (SC), and Sanibel Island (SI) are used throughout. The data set was collected and processed by the NHERI RAPID Facility and was part of the deployment by the Structural Engineering Extreme Events Reconnaissance Network (StEER). 

This Grant for Rapid Response Research (RAPID) project will collect and analyze perishable data on historical buildings. The Tumwata Village (formerly known as Blue Heron Paper Mill Site) located by the Willamette Falls in Oregon City, Oregon, has a very intriguing history and was recently purchased by the Confederated Tribes of Grand Ronde with the intent to restore the falls to their natural state and preserve some of the oldest structures. The site presents a unique opportunity to perform rapid investigations to collect and analyze perishable data on these historical buildings and develop new knowledge in the area of building assessments in corrosive environments. This industrial site contains a wide range of structure types (steel frames, concrete frames, timber frames, masonry walls and massive concrete walls) that were built over a period of 150 years and that employ many construction details that are common in older structures. The data collected and the results of the research will be applicable to many buildings in coastal communities throughout the country. Lidar data sets collected from these buildings will support the development of new methods to analyze and synthesize large data sets as well as integrate visual observations and material testing to quantify structural deterioration damages. The challenge in developing artificial intelligence (AI) technologies to find and quantify damage in structural systems using lidar data is the need to train the methods on existing data sets that show a wide range of damage states. The data to be collected from this site will provide an extensive training data set relevant to structural components common to older buildings. Development of such AI technologies for fast identification and quantification of damage would be transformative for the natural hazards research community and would expand the ability to learn from archived lidar datasets. The collected dataset will be available to researchers to serve as high quality training data in algorithm development. 

The focus of this project was to investigate the performance of mangroves as nature-based solutions for coastal protection. The data can be used by coastal and ecological engineers to capture physical dimensions of mangroves and correspondingly develop 3D models for numerical and experiments. 

RAPID Facility staff collected pre-hurricane coastal UAS imagery on September 26 - 27, 2022. 

Reconnaissance following Hurricane Ida. Wind damage to light structures, flooding, levee failures, coastal erosion. Field photos, Lidar, UAVs.