USGS Response before, during and after Hurricane Florence

Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual proc

Ecosystems Mission Area, Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Pacific Coastal and Marine Science Center, Southwest Biological Science Center, Woods Hole Coastal and Marine Science Center

June 14, 2021

Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation

IntroductionStructure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimen

Ecosystems Mission Area, Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Maryland-Delaware-D.C. Water Science Center, Pacific Coastal and Marine Science Center, Southwest Biological Science Center, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center

May 27, 2021

Impact of SST and surface waves on Hurricane Florence (2018): A coupled modeling investigation

Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir-Simpson Category 4 to Category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling

Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center

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Science

Predicted probabilities of dune erosion from Hurricane Florence

September 20, 2018

Hurricane Florence - Forecast and Documentation of Coastal Change

Hurricane Florence coastal change forecast and pre- and post-storm photos documenting coastal change.

Natural Hazards Mission Area, St. Petersburg Coastal and Marine Science Center

September 20, 2018

Hurricane Florence - Forecast and Documentation of Coastal Change

Hurricane Florence coastal change forecast and pre- and post-storm photos documenting coastal change.

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Oblique aerial photograph near Rodanthe, NC, looking south along the coast on August 30, 2011, three days after landfall of Hurr

January 18, 2018

Forecasting Coastal Change

This project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. The overall objective is to improve real-time and scenario-based predictions of coastal change to support management of coastal infrastructure, resources, and safety.

Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Pacific Coastal and Marine Science Center, St. Petersburg Coastal and Marine Science Center

January 18, 2018

Forecasting Coastal Change

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