Landsat Before, After Images Show Flooding in Carolinas From Florence
USGS Keeps Vital Information Flowing in Carolina Flood Catastrophe
USGS deploying more gauges for Florence, preparing to measure flooding
USGS Scientists Prepare for Storms in Three Seas
USGS: Florence Likely to Cause Short- and Long-Term Beach Erosion
USGS Installing Rapid-Deployment Gauges in Virginia for Florence
USGS Is Installing About 160 Sensors Along NC, SC Coasts For Florence
Before, During, and After the Storm, USGS is There
Hurricane Florence
Information about Hurricane Florence.
Event Support Map
Event Support Map
A multi-layered map that includes forecasts, storm tracks, topographic maps, and more in one place.
Flood Event Viewer (FEV)
Flood Event Viewer (FEV)
See when flooding occurs and how high water levels reach at hundreds of locations and check historic flood data from past storms.
News
USGS: Florence set at least 28 flood records in Carolinas
USGS: Florence set at least 28 flood records in Carolinas
How Hurricanes Michael, Florence May Have Spread Nonnative Species
How Hurricanes Michael, Florence May Have Spread Nonnative Species
Hurricane Florence Preliminary Peak Stage and Streamflow Data Report
Hurricane Florence Preliminary Peak Stage and Streamflow Data Report
Publications
Labeling poststorm coastal imagery for machine learning: Measurement of interrater agreement
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
By
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
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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, Hurricane Florence, Hurricanes
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
Science
Hurricane Florence - Forecast and Documentation of Coastal Change
Hurricane Florence coastal change forecast and pre- and post-storm photos documenting coastal change.
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.
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Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Pacific Coastal and Marine Science Center, St. Petersburg Coastal and Marine Science Center, Hurricane Dorian, Hurricane Florence, Hurricane Harvey, Hurricane Irma, Hurricane Jose, Hurricane Maria, Hurricane Matthew, Hurricane Michael, Hurricane Nate, Hurricane Sandy