1/12/23 AEG Event about Drone Technology

HAPPY NEW YEAR!

DINNER MEETING ANNOUNCEMENT

Utilizing Drone Technology and LiDAR to Monitor the Geo-Economic Resiliency of Engineered Berm-Dunes Installed Post-Hurricane Sandy Along the New Jersey Coast
 

Thursday, January 12, 2023

At the Clarion Hotel in Somerset, New Jersey

Jesse Kolodin, Ph.D., Licensed FAA Part-107 UAS Pilot

This meeting is sponsored by:

ABSTRACT
  Following the devastating storm surge impacts of Hurricane Sandy (2012), several New Jersey coastal communities installed engineered berm-dune structures along their shorelines to protect from the increasing threats of sea-level rise combined with more frequent and intense storm activity. To better understand the geomorphic evolution of these systems, our research team used Drones or Unmanned Aircraft Vehicles (UAV), equipped with high-resolution remote sensors and Light Detection and Ranging (LiDAR) capabilities, to quantify the average rates of berm-dune erosion to help beachfront communities better evaluate their long-term costs of renourishment.
  To investigate whether beachfront communities can adapt their budgeting strategies to pay their cost-share for berm-dune maintenance, we use a hedonic modeling approach, built upon a coupled “geo-economic” framework, to quantify the long-term net benefits that three NJ beachfront communities in Long Beach Island, NJ (LBI), namely, Long Beach Township, Ship Bottom, and Beach Haven, would receive from the installation and maintenance of these engineered structures.
  Our study was designed to estimate how the average rates of berm-dune erosion impact the long-term geomorphology of the natural-human system. However, a major uncertainty that influences the frequency of renourishment and the associated costs a community must pay is the ability to quantify the dual-fluxes driving the sediment budget, which is both diminished by natural erosion and enhanced through wind-driven aeolian sediment accumulation to the berm-dune. With the use of drone technology, we capture high-resolution topographic data and measure the vegetation cover that promotes sediment deposition to the dune. To do this, we deployed mid-sized drones equipped with high-resolution RGB and Multi-spectral cameras to capture standard and near-infrared imagery.
  In addition, we used a larger-sized drone equipped with a LiDAR system for topographic point cloud data. With our Multi-spectral imagery, we processed the data using machine learning algorithms in ESRI ArcPro called “support vector machines” to first separate the two classes of sand and vegetation found along the dune. With these results, we then further classify the vegetation by species as a Normalized Difference Vegetation Index (NDVI). Our RGB imagery allows us to process both an orthomosaic GIS layer and digital elevation model (DEM) using photogrammetry techniques. Lastly, our LiDAR-equipped drone provides us with ~2cm resolution point-cloud (topographic) data for both first and last returns (i.e., with and without vegetated surfaces). 
  In conjunction to the field work, our theoretical geo-economic analysis showed that as aggregate assessed property values within the three LBI communities increased in the year following berm-dune construction, a positive correlation emerges, wherein the increase in property value ultimately becomes a by-product of the added protection provided by engineered berm-dunes. Our study also indicates that a decrease in property values within a beachfront community is correlated with a community’s opposition to berm-dune construction, due to potential losses of both ocean views and private access to the beachfront. The key factor that controls the frequency and associated costs of renourishment is the average rate of berm-dune erosion.
  This study demonstrated that the use of drone technology to gather high resolution aerial imagery is a helpful and cost-effective decision-making tool that beachfront communities could use to prepare for the long-term costs of shoreline protection. Furthermore, the application of drone monitoring proved successful in that large areas of the coast could be covered easily and repetitively, and at the scale needed for the study. Similar data gathering technology using drone technology is widely applicable in many other types of environmental field investigations and site remediation projects where the rapid acquisition of large-scale data over wide areas is vital.

BIOGRAPHY
Jesse Kolodin is an adjunct professor and a director of the drone research program at Montclair State University (NJ). On a day-to-day basis, he is an insurance regulator with New Jersey’s Department of Banking and Insurance. Jesse has his BA in economics from Ithaca College (NY), an MS in Geosciences from Montclair State University, and a Ph.D. in Environmental Science and Management from Montclair State University, including a post-doctoral fellowship with the Eagleton Institute of Science and Politics Program from Rutgers University (NJ). He is a licensed FAA Part-107 UAS (Drone) pilot and instructs the undergraduate/graduate drone course at Montclair State University, which he initially wrote in 2020 for the Earth and Environmental Department.