Kathryn M Weber
Kathryn Weber is an Oceanographer with the Coastal Change Project at the Woods Hole Coastal and Marine Science Center
Science and Products
Filter Total Items: 13
Beach foreshore slope for the West Coast of the United States
This data release contains foreshore slopes for primarily open-ocean sandy beaches along the west coast of the United States (California, Oregon and Washington). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 2002 and 2011. The shoreline positions have been previously published, but the slopes have not. A reference baseline was defined
USGS National Shoreline Change - 2017 lidar-derived mean high water shoreline and associated shoreline change data for coastal North Carolina
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These dat
USGS National Shoreline Change - A GIS compilation of new lidar-derived shorelines (2010, 2017, and 2018) and associated shoreline change data for coastal South Carolina
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These dat
A GIS Compilation of Vector Shorelines for Puerto Rico from 2015 to 2018
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software to compute their rates of change. Keeping a record of h
USGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts.
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. T
Massachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines (1844-2018)
The U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management compiled Massachusetts vector shorelines into an updated dataset for the Office's Shoreline Change Project. The Shoreline Change Project started in 1989 to identify erosion-prone areas of the Massachusetts coast by compiling a database of historical shoreline positions. Trends of shoreline position
Mean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)
This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array of
Barrier island geomorphology and shorebird habitat metrics: 16 sites on the U.S. Atlantic Coast, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leve
Barrier island geomorphology and shorebird habitat metrics: Four sites in New York, New Jersey, and Virginia, 2010-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leve
Massachusetts Shoreline Change Project, 2018 Update: A GIS Compilation of Shoreline Change Rates Calculated Using Digital Shoreline Analysis System Version 5.0, With Supplementary Intersects and Baselines for Massachusetts
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of
Massachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines for the 2018 update
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-f
Dune Metrics for the Massachusetts Coast as Derived From 2013-14 Topographic Lidar Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreli
Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data
The U.S. Geological Survey Coastal and Marine Geology Program uses three methods to derive a datum-based, mean high water shoreline on open-ocean coasts from light detection and ranging (lidar) elevation surveys. This work compared the shorelines produced by the three methods for two different surveys: one survey with simple beach morphology, and one survey with complex beach morphology. For the s
Authors
Amy S. Farris, Kathryn M. Weber, Kara S. Doran, Jeffrey H. List
UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery
The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and vis
Authors
Emily J. Sturdivant, Erika Lentz, E. Robert Thieler, Amy S. Farris, Kathryn M. Weber, David P. Remsen, Simon Miner, Rachel E. Henderson
Using topographic lidar data to delineate the North Carolina Shoreline
In North Carolina, shoreline change rates are an important component of the state's coastal management program. To enhance methods of measuring shoreline change, the NC Division of Coastal Management (DCM) is considering using mean high water (MHW) shorelines extracted from lidar data together with traditional wet/dry shorelines digitized from aerial photography. To test their compatibility, a wet
Authors
Patrick W. Limber, Jeffrey H. List, Jeffrey D. Warren, Amy S. Farris, Kathryn M. Weber
An operational mean high water datum for determination of shoreline position from topographic Lidar data
No abstract available.
Authors
Kathryn M. Weber, Jeffrey H. List, Karen L.M. Morgan
Science and Products
- Data
Filter Total Items: 13
Beach foreshore slope for the West Coast of the United States
This data release contains foreshore slopes for primarily open-ocean sandy beaches along the west coast of the United States (California, Oregon and Washington). The slopes were calculated while extracting shoreline position from lidar point cloud data collected between 2002 and 2011. The shoreline positions have been previously published, but the slopes have not. A reference baseline was definedUSGS National Shoreline Change - 2017 lidar-derived mean high water shoreline and associated shoreline change data for coastal North Carolina
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These datUSGS National Shoreline Change - A GIS compilation of new lidar-derived shorelines (2010, 2017, and 2018) and associated shoreline change data for coastal South Carolina
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These datA GIS Compilation of Vector Shorelines for Puerto Rico from 2015 to 2018
The U.S. Geological Survey (USGS) maintains shoreline positions for the United States coasts from both older sources, such as aerial photographs or topographic surveys, and contemporary sources, such as lidar-point clouds and digital elevation models. These shorelines are compiled and analyzed in the Digital Shoreline Analysis System software to compute their rates of change. Keeping a record of hUSGS National Shoreline Change: A GIS compilation of Updated Vector Shorelines (1800s - 2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts.
During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. TMassachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines (1844-2018)
The U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management compiled Massachusetts vector shorelines into an updated dataset for the Office's Shoreline Change Project. The Shoreline Change Project started in 1989 to identify erosion-prone areas of the Massachusetts coast by compiling a database of historical shoreline positions. Trends of shoreline positionMean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)
This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array ofBarrier island geomorphology and shorebird habitat metrics: 16 sites on the U.S. Atlantic Coast, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leveBarrier island geomorphology and shorebird habitat metrics: Four sites in New York, New Jersey, and Virginia, 2010-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leveMassachusetts Shoreline Change Project, 2018 Update: A GIS Compilation of Shoreline Change Rates Calculated Using Digital Shoreline Analysis System Version 5.0, With Supplementary Intersects and Baselines for Massachusetts
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a shoreline from 1994 was added to calculate both long- and short-term shoreline change rates along ocean-facing sections ofMassachusetts Shoreline Change Project: A GIS Compilation of Vector Shorelines for the 2018 update
The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-fDune Metrics for the Massachusetts Coast as Derived From 2013-14 Topographic Lidar Data
This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreli - Publications
Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data
The U.S. Geological Survey Coastal and Marine Geology Program uses three methods to derive a datum-based, mean high water shoreline on open-ocean coasts from light detection and ranging (lidar) elevation surveys. This work compared the shorelines produced by the three methods for two different surveys: one survey with simple beach morphology, and one survey with complex beach morphology. For the sAuthorsAmy S. Farris, Kathryn M. Weber, Kara S. Doran, Jeffrey H. ListUAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery
The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visAuthorsEmily J. Sturdivant, Erika Lentz, E. Robert Thieler, Amy S. Farris, Kathryn M. Weber, David P. Remsen, Simon Miner, Rachel E. HendersonUsing topographic lidar data to delineate the North Carolina Shoreline
In North Carolina, shoreline change rates are an important component of the state's coastal management program. To enhance methods of measuring shoreline change, the NC Division of Coastal Management (DCM) is considering using mean high water (MHW) shorelines extracted from lidar data together with traditional wet/dry shorelines digitized from aerial photography. To test their compatibility, a wetAuthorsPatrick W. Limber, Jeffrey H. List, Jeffrey D. Warren, Amy S. Farris, Kathryn M. WeberAn operational mean high water datum for determination of shoreline position from topographic Lidar data
No abstract available.AuthorsKathryn M. Weber, Jeffrey H. List, Karen L.M. Morgan