Description: The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" “Standard” (http://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit (6th level) for the entire United States. Some areas may also include additional subdivisions representing the 14- and 16-digit hydrologic unit (HU). At a minimum, the HUs are delineated at 1:24,000-scale in the conterminous United States, 1:25,000-scale in Hawaii, Pacific basin and the Caribbean, and 1:63,360-scale in Alaska, meeting the National Map Accuracy Standards (NMAS). Higher resolution boundaries are being developed where partners and data exist and will be incorporated back into the WBD. WBD data are delivered as a dataset of polygons and corresponding lines that define the boundary of the polygon. WBD polygon attributes include hydrologic unit codes (HUC), size (in the form of acres and square kilometers), name, downstream hydrologic unit code, type of watershed, non-contributing areas, and flow modifications. The HUC describes where the unit is in the country and the level of the unit. WBD line attributes contain the highest level of hydrologic unit for each boundary, line source information and flow modifications.
Definition Expression: N/A
Copyright Text: Funding for the Watershed Boundary Dataset (WBD) was provided by the USDA-NRCS, USGS and EPA along with other federal, state and local agenciesies. Representatives from many agencies contributed a substantial amount of time and salary towards quality review and updating of the dataset in order to meet the WBD Standards. Acknowledgment of the originating agencies would be appreciated in products derived from these data. See dataset specific metadata for further information
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Shoreline Situation Reports (SSR) were first generated by VIMS in the 1970's to report the condition and status of the shore lands. The SSR series were published in hardcopy on a county by county basis for each Tidewater Virginia localities. The reports were intended to assist planners, managers, and regulators in decisions pertaining to management of coastal areas and natural resources therein. This Shoreline Inventory report continues a process which updates and expands the earlier reports. Data collected reports conditions surveyed in the immediate riparian zone, the bank, and along the shoreline. This dataset is the result of combining the most recent digital shoreline inventories for Virginia.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Shoreline Situation Reports (SSR) were first generated by VIMS in the 1970's to report the condition and status of the shore lands. The SSR series were published in hardcopy on a county by county basis for each Tidewater Virginia localities. The reports were intended to assist planners, managers, and regulators in decisions pertaining to management of coastal areas and natural resources therein. This Shoreline Inventory report continues a process which updates and expands the earlier reports. Data collected reports conditions surveyed in the immediate riparian zone, the bank, and along the shoreline. This dataset is the result of combining the most recent digital shoreline inventories for Virginia.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Shoreline Situation Reports (SSR) were first generated by VIMS in the 1970's to report the condition and status of the shore lands. The SSR series were published in hardcopy on a county by county basis for each Tidewater Virginia localities. The reports were intended to assist planners, managers, and regulators in decisions pertaining to management of coastal areas and natural resources therein. This Shoreline Inventory report continues a process which updates and expands the earlier reports. Data collected reports conditions surveyed in the immediate riparian zone, the bank, and along the shoreline. This dataset is the result of combining the most recent digital shoreline inventories for Virginia.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><P STYLE="font-size:16ptmargin:7 0 7 0;"><SPAN><SPAN>This Fishing Piers dataset was downloaded from the Virginia Department of Wildlife Resources (DWR) Gis Data website (https://dwr.virginia.gov/gis/data/) on April 14, 2021.</SPAN></SPAN></P><DIV><P><SPAN /></P></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset contains locational information for Virginia Department of Wildlife Resources (VDWR) owned public boating access sites. The coverage includes all of Virginia. These data are formatted as an ArcView shapefile and compiled by the VDGIF Fish and Wildlife Information Services (FWIS) from the VDGIF Capital Outlay database. These data are presented as point locations.</SPAN></P></DIV></DIV></DIV>
Description: USGS Structures from The National Map (TNM) consists of data to include the name, function, location, and other core information and characteristics of selected manmade facilities. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations. Structures currently being collected are: School, College/University, Fire Station/EMS Station, Law Enforcement, Prison/Correctional Facility, State Capitol, Hospital/Medical Center, Ambulance Services, Cemetery, and Post Office. Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The National Map viewer allows free downloads of public domain structures data in either Esri File Geodatabase or Shapefile formats. For additional information on the structures data model, go to https://nationalmap.gov/structures.html.
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Shoreline Situation Reports (SSR) were first generated by VIMS in the 1970's to report the condition and status of the shore lands. The SSR series were published in hardcopy on a county by county basis for each Tidewater Virginia localities. The reports were intended to assist planners, managers, and regulators in decisions pertaining to management of coastal areas and natural resources therein. This Shoreline Inventory report continues a process which updates and expands the earlier reports. Data collected reports conditions surveyed in the immediate riparian zone, the bank, and along the shoreline. This dataset is the result of combining the most recent digital shoreline inventories for Virginia.</SPAN></P></DIV></DIV></DIV>
Name: Living Shoreline: Suitable Area for Marsh Ranked for Co-Benefits
Display Field: TARGET_FID
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><P><SPAN>The Center for Coastal Resources Management (CCRM) at the Virginia Institute of Marine Science (VIMS) has been developing tools to guide local governments in shoreline management. Using a number of criteria, the Shoreline Management Model (SMM) determines appropriate shoreline best management practices. This layer contains only those areas determined to be suitable for non-structural plant marsh or plant marsh with sill recommedations. These areas are prioritized using a scoring method that considers nutrient removal potential, benefits provided to coastal buildings, the potential for the project to provide habitat continuity and enhancement, and the potential the project to add resilience for socially vulnerable communities.</SPAN></P><P><SPAN>(For more information on the Shoreline Management Model, see https://www.vims.edu/ccrm/ccrmp/bmp .)</SPAN></P></DIV>
Definition Expression: N/A
Copyright Text: Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS),
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 14 0;"><SPAN>Polygons depict areas where vulnerable buildings (i.e., buildings on ground that is less than 10-feet in elevation) receive no benefits from NNBFs. These are areas where localities or landowners may consider creating new or restoring NNBFs to provide multiple benefits to communities. </SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><P><SPAN>This data layer contains polygon representations of National Priority List ("Superfund") sites throughout US EPA Region 3. Congress passed the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA, also known as "Superfund") in response to a growing national concern about the release of hazardous substances from abandoned waste sites. The term “boundary” should be used with caution as it could be interpreted several different ways. The polygons in this file could be property boundaries where the area of contamination is somewhere within the property but not completely encompassing it. They could be “best guess” limits of actual contamination, they could be limits of where remediation work is actually occurring, or several other definitions. For this sort of detail it is best to contact the project manager assigned to the individual facility.</SPAN></P></DIV></DIV>
Definition Expression: N/A
Copyright Text: US Environmental Protection Agency - Region 3
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The following paragraphs are taken directly from the "</SPAN><SPAN STYLE="font-weight:bold;">Mapping Inequality Redlining in New Deal America</SPAN><SPAN>" website (https://dsl.richmond.edu/panorama/redlining/#loc=13/36.878/-76.313&city=norfolk-va&area=D3&text=intro ). "Among the thousands of area descriptions created by agents of the federal government's Home Owners' Loan Corporation (HOLC) between 1935 and 1940, ... . HOLC staff members, using data and evaluations organized by local real estate professionals--lenders, developers, and real estate appraisers--in each city, assigned grades to residential neighborhoods that reflected their "mortgage security" that would then be visualized on color-coded maps. Neighborhoods receiving the highest grade of "A"--colored green on the maps--were deemed minimal risks for banks and other mortgage lenders when they were determining who should received loans and which areas in the city were safe investments. Those receiving the lowest grade of "D," colored red, were considered "hazardous."</SPAN></P><P><SPAN>Conservative, responsible lenders, in HOLC judgment, would "refuse to make loans in these areas [or] only on a conservative basis." HOLC created area descriptions to help to organize the data they used to assign the grades. Among that information was the neighborhood's quality of housing, the recent history of sale and rent values, and, crucially, the racial and ethnic identity and class of residents that served as the basis of the neighborhood's grade. These maps and their accompanying documentation helped set the rules for nearly a century of real estate practice."</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The Virginia Institute of Marine Science published the first Tidal marsh Inventories using data collected in the early 1970's. </SPAN><SPAN>Using high resolution color infra-red imagery from 2009, 2011 and 2013 new Tidal Marsh Inventories have been developed beginning in 2010. Marsh boundaries were generated using heads-up digitizing techniques at a scale of 1:1,000. From 2010 through 2014 marsh polygons were classified by morphologic type: fringe, extensive, embayed, or marsh island. Beginning in 2015, morphologic classification was discontinued. Marshes were ground-truthed in the field where a community type index was assigned to each marsh based on plant community make-up.</SPAN></P><P><SPAN /></P><P><SPAN /></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This data set represents the extent and approximate location of historic wetland habitats in certain areas of the conterminous United States. The identification of these historic wetlands is limited by the methodology outlined in the associated Historic Wetlands Project Metadata and is not intended to be a comprehensive inventory of all historic wetlands. The U.S. Fish and Wildlife Service (Service) is the principal Federal agency that provides information to the public on the extent and status of the Nation's wetlands and provides stewardship for the wetlands data that comprise the Wetlands Layer of the National Spatial Data Infrastructure. In the formulation of this data layer, historic wetlands are defined as areas where there is evidence that a wetland once existed. This evidence can be from historical map information inventories of past wetland extent or other information collected that relate directly to data on wetland filling, drainage or other modifications. Historic wetlands have been identified using several different techniques depending on the availability and type of information used to locate these areas and user needs. For example, historical maps often provide information about past wetland extent or location and can be useful tools to identify historic wetlands. Historic wetlands have been identified as polygonal data. No linear features have been included. Historic wetland polygons are not classified as wetlands and have no wetland labels or attribution. Since these features no longer exist, boundary delineations are considered approximations based on topography, previously mapped information or indications of historic water levels.</SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Layer containing polygons delineating NNBFs including beaches, dunes, non-tidal and tidal wetlands, wooded areas, and scrub-shrub areas. Data is sourced from various datasets including VIMS Center for Coastal Resources Management (CCRM) Comprehensive Coastal Inventory (CCI) and Tidal Marsh Inventory (TMI), VIMS Shoreline Studies program, 2016 Virginia Land Cover Dataset, and the 2017 National Wetlands Inventory. </SPAN></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset contains the boundaries for lands of conservation and recreational interest in Virginia. The Conservation Lands Database is constantly being edited and updated. Historic easements are held by the Virginia Board of Historic Resources and administered by the Virginia department of Historic Resources. Data is released to the public quarterly and posted to the download section of the website: http://www.dcr.virginia.gov/natural_heritage/cldownload.shtml</SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
Description: EJSCREEN is an environmental justice (EJ) screening and mapping tool that provides EPA with a nationally consistent dataset and methodology for calculating "EJ indexes," which can be used for highlighting places that may be candidates for further review, analysis, or outreach as the agency develops programs, policies and other activities. The tool provides both summary and detailed information at the Census block group level or a user-defined area for both demographic and environmental indicators. The summary information is in the form of EJ Indexes which combine demographic information with a single environmental indicator (such as proximity to traffic) that can help identify communities living in areas with greater potential for environmental and health impacts. The tool also provides additional detailed demographic and environmental information to supplement screening analyses. EJSCREEN displays this information in color-coded maps, bar charts, and standard reports. Users should keep in mind that screening tools are subject to substantial uncertainty in their demographic and environmental data, particularly when looking at small geographic areas, such as Census block groups. Data on the full range of environmental impacts and demographic factors in any given location are almost certainly not available directly through this tool, and its initial results should be supplemented with additional information and local knowledge before making any judgments about potential areas of EJ concern.
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 11 0;"><SPAN>The main data sources used to construct these data were: the Census, the EPA's EJ Index, CCRM, USGS's NLCD land cover data, and NOAA's SLOSH data. The SLOSH data was intersected with the four developed land cover layers of the NLCD data to provide estimates of the percentages of developed land that would be flooded in each block group. These block groups represent those that intersect with the Elizabeth River watershed shapefile provided by CCRM, which lie in the four counties considered in this analysis: Chesapeake City, Norfolk City, Portsmouth City, and Virginia Beach City. The final five variables in the table are the indexes created using Principal Components Analysis (PCA). The variables used in each PCA are the following:</SPAN></P><P STYLE="margin:0 0 11 0;"><SPAN STYLE="font-weight:bold;"><SPAN>Combined demographic</SPAN></SPAN><SPAN><SPAN>= </SPAN></SPAN><SPAN><SPAN>“</SPAN></SPAN><SPAN><SPAN>pctmin","pctlowinc","pctlths", "pctlingiso","pctunder5","pctover64", "MedianStructureAge","DevelopedArea","MedianHHincome", "PublicAssistanceShare","NotInLaborForceShare","NoInternetShare", "AtLeastBachelorsShare","BlackShare","BlackHHShare", "IncomeBelowPovertyShare","RenterShare</SPAN></SPAN></P><P STYLE="margin:0 0 11 0;"><SPAN><SPAN>40.8% of the variance was explained using first PC, which was used as the index score. That PC score was standardized against others within the Elizabeth River watershed using the EJ Screen methodology.</SPAN></SPAN></P><P STYLE="margin:0 0 11 0;"><SPAN STYLE="font-weight:bold;"><SPAN>Combined environmental</SPAN></SPAN><SPAN><SPAN>= "EJ.DISPARITY.cancer.eo.EJLocal","EJ.DISPARITY.resp.eo.EJLocal", "EJ.DISPARITY.dpm.eo.EJLocal","EJ.DISPARITY.pm.eo.EJLocal", "EJ.DISPARITY.o3.eo.EJLocal","EJ.DISPARITY.traffic.score.eo.EJLocal "EJ.DISPARITY.pctpre1960.eo.EJLocal","EJ.DISPARITY.proximity.rmp.eo.EJLocal", "EJ.DISPARITY.proximity.tsdf.eo.EJLocal","EJ.DISPARITY.proximity.npl.eo.EJLocal", "EJ.DISPARITY.proximity.npdes.eo.EJLocal"</SPAN></SPAN></P><P STYLE="margin:0 0 11 0;"><SPAN><SPAN>35.4% </SPAN></SPAN><SPAN><SPAN>of the variance was explained using first PC, which was used as the index score. That PC score was standardized against others within the Elizabeth River watershed using the EJ Screen methodology.</SPAN></SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The following paragraphs are taken directly from the "</SPAN><SPAN STYLE="font-weight:bold;">Mapping Inequality Redlining in New Deal America</SPAN><SPAN>" website (https://dsl.richmond.edu/panorama/redlining/#loc=13/36.878/-76.313&city=norfolk-va&area=D3&text=intro ). "Among the thousands of area descriptions created by agents of the federal government's Home Owners' Loan Corporation (HOLC) between 1935 and 1940, ... . HOLC staff members, using data and evaluations organized by local real estate professionals--lenders, developers, and real estate appraisers--in each city, assigned grades to residential neighborhoods that reflected their "mortgage security" that would then be visualized on color-coded maps. Neighborhoods receiving the highest grade of "A"--colored green on the maps--were deemed minimal risks for banks and other mortgage lenders when they were determining who should received loans and which areas in the city were safe investments. Those receiving the lowest grade of "D," colored red, were considered "hazardous."</SPAN></P><P><SPAN>Conservative, responsible lenders, in HOLC judgment, would "refuse to make loans in these areas [or] only on a conservative basis." HOLC created area descriptions to help to organize the data they used to assign the grades. Among that information was the neighborhood's quality of housing, the recent history of sale and rent values, and, crucially, the racial and ethnic identity and class of residents that served as the basis of the neighborhood's grade. These maps and their accompanying documentation helped set the rules for nearly a century of real estate practice."</SPAN></P></DIV></DIV></DIV>
Description: The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.
Description: <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The shoreline for the Elizabeth River Watershed has been extracted from the Virginia Shoreline Inventory dataset. Shoreline was digitized from high resolution imagery (2009, 2011, and/or 2013) provided by </SPAN><SPAN><SPAN>Virginia Base Mapping Program (VBMP).</SPAN></SPAN></P><P><SPAN /></P></DIV></DIV>
Definition Expression: N/A
Copyright Text: Virginia Geographic Information Network (VGIN). Center for Coastal Resources Management(CCRM), Virginia Institute of Marine Science(VIMS)
Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The shoreline for the Elizabeth River Watershed has been extracted from the Virginia Shoreline Inventory dataset. Shoreline was digitized from high resolution imagery (2009, 2011, and/or 2013) provided by </SPAN><SPAN><SPAN>Virginia Base Mapping Program (VBMP).</SPAN></SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
Definition Expression: N/A
Copyright Text: Virginia Geographic Information Network (VGIN). Center for Coastal Resources Management(CCRM), Virginia Institute of Marine Science(VIMS)
Description: <DIV STYLE="text-align:Left;"><P STYLE="font-size:16ptmargin:7 0 7 0;"><SPAN>This layer has been extracted from the Virginia Geographic Information Network (VGIN) 2016 Virginia Land Cover Dataset. Land cover classes Forest, Tree, and Scrub/shrub are shown here to represent Tree Canopy cover.</SPAN></P><DIV><P><SPAN /></P></DIV></DIV>
Definition Expression: N/A
Copyright Text: Virginia Geographic Information Network (VGIN)
Name: Environmental/Demographic Vulnerable Census Blocks
Display Field: DmgrphcsName
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: <DIV STYLE="text-align:Left;"><DIV><P><SPAN>This layer is the selected subset of the Enivormental and Demographic Vulnerability Index layers. Ony census blocks that are scored high or very high for vulnerability in both the Environmental and Demographic Index have been selected. This layer also contains landcover(2016) type percentages for each census block.</SPAN></P></DIV></DIV>