Physical Sciences and Mathematics Commons^™

Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith

Data

Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays.

Gis Data: New Kent County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

No abstract provided.

Catch The King Tide 2017 Data: Hampton, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …

Catch The King Tide 2017 Data: Portsmouth, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …

Catch The King Tide 2017 Data: Suffolk, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …

Catch The King Tide 2017: All King Tide Data, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …

Gis Data: Chesterfield County And Cities Of Colonial Heights, Petersburg, And Richmond Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for Chesterfield County and the Cities of Colonial Heights, Petersburg, and Richmond was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Chesterfield_lubc_2017). The second portrays the presence of beaches (Chesterfield_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Chesterfield_sstru_2017). The final shapefile includes all structures that are represented as points (e.g. piers)(Chesterfield_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, …

Chesterfield County And The Cities Of Colonial Heights, Petersburg, And Richmond, Virginia - Shoreline Inventory Report: Summary Tables, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Reports

The Shoreline Inventory Summary Tables quantify observed conditions based on river systems, such as the combined length of linear features (e.g. shoreline miles surveyed, miles of bulkhead and revetment), the total number of point features (e.g. docks, boathouses, boat ramps) & total acres of polygon features (tidal marshes).

Chesterfield County And The Cities Of Colonial Heights, Petersburg, And Richmond, Virginia - Shoreline Inventory Report: Methods And Guidelines, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Reports

The 2017Inventory for Chesterfield County and the Cities of Colonial Heights, Petersburg, and Richmond was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Chesterfield_lubc_2017). The second portrays the presence of beaches (Chesterfield_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Chesterfield_sstru_2017). The final shapefile includes all structures that are represented as points (e.g. piers)(Chesterfield_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data …

Summary Tables: 2017 Henrico County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Kileen, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Reports

The Shoreline Inventory Summary Tables quantify observed conditions based on river systems, such as the combined length of linear features (e.g. shoreline miles surveyed, miles of bulkhead and revetment), the total number of point features (e.g. docks, boathouses, boat ramps) & total acres of polygon features (tidal marshes).

Henrico County, Virginia - Shoreline Inventory Report: Methods And Guidelines, Marcia Berman, Karinna Nunez, Sharon Kileen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Reports

No abstract provided.

Adapt Virginia: A New Web Portal About Climate Change Adaptations (Www.Adaptva.Org), Center For Coastal Resources Management, Virginia Institute Of Marine Science

Reports

Rivers & Coast is a periodic publication of the Center for Coastal Resources Management, Virginia Institute of Marine Science. The goal of Rivers & Coast is to keep readers well informed of current scientific understanding behind key environmental issues related to watershed rivers and coastal ecosystems of the Chesapeake Bay.

Gis Data: King George County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Kory Angstadt, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for King George County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (King_George_lubc_2017). The second portrays the presence of beaches (King_George _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(King_George _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(King_George_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any …

Catch The King Tide 2017 Data: Gloucester & Mathews, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Gis Data: Henrico County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for Henrico County, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.

Gis Data: The County Of Isle Of Wight, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner

Data

The 2017 Inventory for the Isle of Wight County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP). Four GIS shapefiles are developed. The first describes land use and bank conditions (IsleofWight_lubc_2017). The second portrays the presence of beaches (IsleofWight_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(IsleofWight_sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(IsleofWight_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions …

Gis Data: Hanover County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for Hanover County, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.

Gis Data: The County Of Spotsylvania Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for Spotsylvania County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Spotsylvania_lubc_2017). The second portrays the presence of beaches (Spotsylvania_beaches_2017). The third reports shoreline structures that are described as arcs or lines (e.g. riprap)(Spotsylvania_sstru_2017). The final shapefile includes all structures that are represented as points (e.g. piers)(Spotsylvania_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions that pertain …

Hanover County, Virginia - Shoreline Inventory Report: Methods And Guidelines, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Reports

The 2017 Inventory for Hanover County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed.The first describes land use and bank conditions (Hanover _lubc_2017). The second portrays the presence of beaches (Hanover _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Hanover _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Hanover _astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use …

2016 Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith, L. Nagey

Data

Multispectral aerial imagery acquired in 2016 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays.

Catch The King Tide 2017 Data: Chesapeake, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Gis Data: City Of Fredericksburg,Virginia, Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for the City of Fredericksburg was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Fredericksburg_lubc_2017). The second portrays the presence of beaches (Fredericksburg_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Fredericksburg _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Fredericksburg _astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and …

Gis Data: Hanover County, Virginia, Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for Hanover County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed.The first describes land use and bank conditions (Hanover _lubc_2017). The second portrays the presence of beaches (Hanover _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Hanover _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Hanover _astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any …

Gis Data: Henrico County, Virginia, Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for Henrico County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP). Four GIS shapefiles are developed.The first describes land use and bank conditions (Henrico _lubc_2017). The second portrays the presence of beaches (Henrico _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Henrico _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Henrico _astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and …

Catch The King Tide 2017 Data: Outside Hampton Roads, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Catch The King Tide 2017 Data: Virginia Beach, Virginia, Jon Derek Loftis

Data

No abstract provided.

Catch The King Tide 2017 Data: Newport News, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Catch The King Tide 2017 Data: York & Poquoson, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Catch The King Tide 2017 Data: Norfolk, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …

Gis Data: Surry County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for Surry County, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.