Physical Sciences and Mathematics Commons^™

Gis Data: 2016 Chesapeake Bay Sav Coverage, Virginia Institute Of Marine Science, Sav Data Administrator

Data

Abstract: The 2015 Chesapeake Bay SAV Coverage was mapped from digital multispectral imagery with a 25cm GSD to assess water quality in the Bay. Each area of SAV was interpreted from the rectified imagry and classified into one of four density classes by the percentage of cover. The SAV beds were entered into an SDE GIS fetaure class using the quality control procedures documented below. The dataset contains all SAV areas that were identified from the areas flown. Some areas that are presumed to contain no SAV were not flown. Some small beds, particularly along narrow tributaries may not have …

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: 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 …

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).

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.

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).

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.

Bacteria Tmdl Development For Lower Chickahominy River Watershed Located In Charles City, James City, And New Kent Counties, Va, Virginia Institute Of Marine Science

Reports

Section 303(d) of the Clean Water Act (CWA) and the United States Environmental Protection Agency’s (USEPA’s) Water Quality Planning and Management Regulations (40 CFR Part 130) require states to develop total maximum daily loads (TMDLs) for waterbodies that are exceeding water quality standards (WQSs). TMDLs represent the total pollutant loading that a waterbody can receive without violating WQSs. The TMDL process establishes the allowable loadings of pollutants for a waterbody based on the relationship between pollution sources and in-stream water quality conditions. By following the TMDL process, states can establish controls based on water quality conditions to reduce pollution from …

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: The County Of Isle Of Wight, Virginia Shoreline Management Model, 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 Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

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 …

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

Reports

No abstract provided.

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 …

Associated Dataset: Climate Change Impacts On Southern Ross Sea Phytoplankton Composition, Productivity And Export, Daniel E. Kaufman, Marjorie A.M. Friedrichs, Walker O. Smith Jr., Eileen E. Hofmann, Michael S. Dinniman, John C.P. Hemmings

Data

This dataset includes data used in the publication Kaufman et al., 2017, JGR-Oceans, which investigates how these climatic changes in the Ross Sea, Antarctica, may alter phytoplankton composition, primary productivity and export. A one-dimensional version of the Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification was adapted for use in the Ross Sea (MEDUSA-RS). Glider measurements were used to force MEDUSA-RS, which includes diatoms and both solitary and colonial forms of Phaeocystis antarctica. Model performance was evaluated with glider observations, and experiments were conducted using projections of physical drivers for mid- and late-21st century. Additional scenarios examined the …

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

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

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

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

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

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …