Virginia Elevation Data underlying the analysis entitled "Maps of lands close to sea level along the middle Atlantic coast of the United States" by J.G. Titus and J. Wang, 2008.

Metadata:

• Identification_Information
• Data_Quality_Information
• Spatial_Data_Organization_Information
• Spatial_Reference_Information
• Entity_and_Attribute_Information
• Distribution_Information
• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: US Environmental Protection Agency

Publication_Date: February 2008

Title:

Virginia Elevation Data underlying the analysis entitled "Maps of lands close to sea level along the middle Atlantic coast of the United States" by J.G. Titus and J. Wang, 2008.

Geospatial_Data_Presentation_Form: raster digital data

Other_Citation_Details:

Data underlying the analysis reported in J.G. Titus and J. Wang, 2008.

Online_Linkage:  http://maps.risingsea.net/data.html

Larger_Work_Citation:

Citation_Information:

Originator: US Environmental Protection Agency

Publication_Date: February 2008

Title:

Maps of lands close to sea level along the middle Atlantic coast of the United States

Other_Citation_Details:

Full Citation: Titus, J.G. and J. Wang, 2008: Maps of lands close to sea level along the middle Atlantic coast of the United States: an elevation data set to use while waiting for LIDAR. In: Background Documents Supporting Climate Change Science Program Synthesis and Assessment Product 4.1: Coastal Elevations and Sensitivity to Sea Level Rise [J.G. Titus and E.M. Strange (eds.)]. EPA430R07004, U.S. Environmental Protection Agency, Washington, DC.

Description:

Abstract:

Coastal Virginia Digital Elevation Model (Environmental Systems Research Institute [ESRI] Grid format) represents an elevation map of the Virginia coastal zone created for the purposes of analyzing vulnerability to rising sea level. The domain of the data set extends from the upper tidal wetland boundary up to the 40 foot (NGVD29) contour line, but the primary focus of the analytical approach and quality control has focused on land below the 10 foot contour line. This data set has been derived from several sources of elevation data, including United States Geological Survey (USGS) 1:24,000 Digital Line Graphs (DLG), and DLG's created by the Henan Institute of Geography from Digital Raster Graphics and hardcopy 1:24,000 USGS topographic quadrangles. In addition, the analysis created a supplemental contour line representing the elevation of spring high water (SHW), which is generally between 0.7 and 3.5 feet above the National Geodetic Vertical Datum of 1929 (NGVD29) in Virginia. We defined the horizontal position of the supplemental contour by extracting the inland limit of the tidal wetland polygons in of the US Fish and Wildlife Service National Wetlands Inventory (NWI). We defined the vertical position of the supplemental contour by creating a "tidal elevation surface" using the National Ocean Service's (NOS) estimated tide ranges, NOS estimated sea level trends, the NOS published benchmark sheets, and the National Geodetic Survey North American Vertical Datum Conversion Utility (VERTCON) program to convert the Mean Tide Level (MTL) relative to the North American Vertical Datum of 1988 (NAVD88) to that of NGVD29. All elevation information was converted to a common vertical reference, usually NGVD29, and the DEM was generated from that input data using ESRI's interpolation algorithm TOPOGRID (within ArcGIS workstation GRID extension). We converted the absolute elevation estimates (usually NGVD29) into elevations relative to SHW using the "tidal elevation surface." For purposes of this data set, SHW is the upper boundary of tidal wetlands (including vegetated wetlands and intertidal beaches). Elevation is expressed in cm. 

The zip file associated with this data set should include:  

1.       README_VA_Elevation.doc, which provides a brief overview of the relationship between this dataset and related data

2.       InterpolationMethods_MEMO.doc

3.       VA_Data_Quality.jpg 

4.       DEM_LidarComparisonTable.doc

5.       DEM_Comparison_with_DLG_11_quads.xls

6.       Institute_of_Geography_DLG.xls 

7.       Titus_and_Wang_2008.pdf

However, to speed download, (2) and (7) (which are associated with all of the states) may have been removed

From online versions and included in a file called “Common_supplemental_metadata.zip”

Purpose:

The Virginia Digital Elevation Model provides a base map layer for assessing the possible influences of potential sea level rise on coastal regions. We recommend against using this data to create maps with scales greater than 1:100,000, regardless of the level of vertical precision portrayed.  Moreover, if the purpose of using this data is to create graphical depictions of risk with contour intervals of 50-100 cm, we recommend a considerably smaller scale unless the audience is likely to understand the limitations of the data.

Supplemental_Information:

Elevations relative to spring high water during the year 2000.

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2000

Currentness_Reference:

ground condition

Status:

Progress: Complete

Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -78.069555

East_Bounding_Coordinate: -74.985170

North_Bounding_Coordinate: 39.070197

South_Bounding_Coordinate: 36.113572

Keywords:

Theme:

Theme_Keyword_Thesaurus: General

Theme_Keyword: Virginia Elevation

Theme_Keyword: DEM

Theme_Keyword: Coastal Elevation

Place:

Place_Keyword_Thesaurus: Geographic Names Information Service (GNIS)

Place_Keyword: Virginia VA

Access_Constraints: None

Use_Constraints:

None

Point_of_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: James G. Titus

Contact_Organization: U.S. Environmental Protection Agency, Climate Change Division

Contact_Position: Project Manager

Contact_Address:

Address_Type: mailing address

Address:

Mailcode 6207J

City: Washington

State_or_Province: DC

Postal_Code: 20460

Contact_Voice_Telephone: 202-343-9307

Contact_Facsimile_Telephone: 202-343-2338

Contact_Electronic_Mail_Address: Titus.Jim@epamail.epa.gov

Hours_of_Service: 9:00 - 6:00 Eastern

Data_Set_Credit:

Jue Wang, GIS Practice, ICF Consulting, Inc.

Native_Data_Set_Environment:

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.0.1770

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Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

The underlying data used in the creation of this layer may contain errors or omissions. The accuracy of this data set generally corresponds to the source data used in the layer development. See "VA_Data_Quality.jpg" for  an index of the source data used (that accompanied this data set in the zip file.)

See the sections on Positional Accuracy for more detailed information.

Additional consideration: The vertical values and their associated positions were generated using the interpolation function "TOPOGRID" within the ESRI GRID module. TOPOGRID uses input elevation data such as contours and elevation point data along with supplemental information such as stream networks, lakes (of known elevation), and bounding areas to generate a hydrologically-correct DEM. Each state DEM was generated using TOPOGRID but the specific parameters were unique to the data sets available and issues related to each state.

There are known issues relating to the interpolation algorithm TOPOGRID.

TOPOGRID Plateau Problem. The TOPOGRID function generates disproportionately large areas with the same value of the input contour lines, e.g., if we have 5 and 10 foot contour lines, there would be substantially more areas with values between 4 to 6 and 9 to 11, than 6 to 9 feet. At the upper tips of narrow valleys, the cell values tend to be the same as the bounding contours so the valleys become plateaus. The TOPOGRID function within the ESRI GRID module tends to calculate a trend from neighboring contour lines. As a result, TOPOGRID frequently creates areas of erroneous depressions on the plains adjacent to steep slopes, often substantially below the contours between which those depressions lay. It also creates plateaus along contours, which can be problematic because they overstate the amount of land barely above the wetlands and right at the first contour, while understating the amount of land halfway between the wetlands and the first contour. To address these problems, we processed the areas above and below the first contour separately. However, this caused another problem. In narrow valleys in the area below the first contour, the output DEM values were similar or identical to those of the bounding contour lines due to the lack of elevation information that TOPOGRID needs to calculate trend. The most problematic regions occurred where there was a stream valley below the first contour (e.g. between two parallel 5 foot contours), neither open water nor tidal wetlands along most of the length of the valley, but open water or tidal wetlands at one end of the valley (e.g. a typical non-tidal stream flowing into tidal waters). In some cases, the trend from the wetlands or open water at the mouth toward the bounding first contour would provide values even higher than that first contour farther up the valley. And in general, TOPOGRID would be more likely to assume a flat area between the contours, than to characterize it as a valley.

We did not use stream data in constructing the DEM for Virginia. (See comparable DEMs for Delaware, Maryland, New York and North Carolina, where stream data was available.).

Evaluation of other interpolation methods. 

Several interpolation methods were evaluated before the TOPOGRID function was selected. Specifically, Spline, Inverse Distance Weighting (IDW), and Triangulated Irregular Network (TIN) methods were evaluated and compared to the TOPOGRID function. Statistics and graphical examples of cross sections specific to each interpolation method are presented in the accompanying "InterpolationMethods_MEMO.doc" memo included in the zip file associated with this data set.

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Explanation:

An accuracy assessment was made between the source  DLG's and the DEM for a select number of quads. See "DEM_Comparison_with_DLG_11_quads.xls"  which accompanies this data set in the zip file.

An additional assessment was made between the DEM and lidar data where it was available in Maryland and North Carolina. The results can be found in the "DEM_LidarComparisonTable.doc" that accompanied this data set in the zip file.

See the sections on Positional Accuracy (Horizontal and Vertical).

Logical_Consistency_Report:

Refer to the Titus and Wang 2008 technical report that documents this study for information on the publication date for data and procedures used in the development of this layer.

See the sections on Positional Accuracy (Horizontal and Vertical) for additional information.

Note that the discussions presented in the accuracy reports refer to contour intervals using two different systems of measurements (meters and feet). We use the two diffent systems to reflect the actual contour intervals used by USGS over the years, which vary on a quadrangle by quadrangle basis.

Completeness_Report:

This elevation data set generally reflects that of the source data used in the layer development.

See the sections on Positional Accuracy (Horizontal and Vertical) for additional information.

The vertical values and their associated positions were generated using the interpolation function "TOPOGRID" within the ESRI GRID module. TOPOGRID uses input elevation data such as contours and elevation point data along with supplemental information such as stream networks, lakes (of known elevation), and bounding areas to generate a hydrologically-correct DEM. Each state DEM was generated using TOPOGRID but the specific parameters were unique to the data sets available and issues related to each state. The specifics to each state DEM are described under positional accuracy section of the metadata and in process steps.

There are known issues relating to the interpolation algorithm TOPOGRID.

TOPOGRID Plateau Problem.  The TOPOGRID function generates disproportionately large areas with the same value of the input contour lines, e.g., if we have 5 and 10 foot contour lines, there would be substantially more areas with values between 4 to 6 and 9 to 11, than 6 to 9 feet. At the upper tips of narrow valleys, the cell values tend to be the same as the bounding contours so the valleys become plateaus.

The TOPOGRID function within the ESRI GRID module tends to calculate a trend from neighboring contour lines.  As a result, TOPOGRID frequently creates erroneous depressions on the plains adjacent to steep slopes, often substantially below the contours between which those depressions lay. It also creates plateaus along contours, which can be problematic because they overstate the amount of land barely above the wetlands and right at the first contour, while understating the amount of land halfway between the wetlands and the first contour. To address these problems, we processed the areas above and below the first contour separately. However, this caused another problem. In narrow valleys in the area below the first contour, the output DEM values were similar or identical to those of the bounding contour lines due to the lack of elevation information that TOPOGRID needs to calculate trend. The most problematic regions occurred where there was a stream valley below the first contour (e.g. between two parallel 5 foot contours), no open water or tidal wetlands along most of the length of the valley, but open water or tidal wetlands at one end of the valley (e.g. a typical non-tidal stream flowing into tidal waters). In some cases, the trend from the wetlands or open water at the mouth toward the bounding first contour would provide values even higher than that first contour farther up the valley. And in general, TOPOGRID would be more likely to assume a flat area between the contours, than to characterize it as a valley.

We did not use stream data in constructing the DEM for Virginia. (See comparable DEMs for Delaware, Maryland, New York and North Carolina, where stream data was available.).

Omissions. 

Neither stream networks nor lake features were used as inputs into the TOPOGRID function in creation of this data set. The absence of a hydrologic network explains a significant proportion of the greatest errors in the vicinity of non-tidal streams at elevations below the first contour. TOPOGRID infers stream valleys above the first contour by the pattern of a valley without the stream data. The decision to split the data into land below and above the first contour (discussed in process step #4 "Interpolation of Digital Elevation Model ") had the effect of increasing the potential errors resulting from the absence of stream data. However, the magnitude of any errors induced by this problem was limited by the "first contour truncating" (also discussed in process step #4). The net effect was to put back some of the plateaus eliminated by dividing the data, but not all of those plateaus. Moreover, errors introduced by of omitting stream were avoided in areas with tidal streams or tidal wetlands, by the use of tidal wetlands data, which served the same function. 

Other Issues:

In addition to excluding streams, the decision to process 3 elevation areas separately within TOPOGRID (as described in the process step #4 - "Interpolation of Digital Elevation Model") and then combine them into a single DEM removes the algorithm from its theoretical underpinning, because it separates each elevation zone from the context of the overall environment that TOPOGRID uses to generate a hydrologically-correct DEM.  Because the objective of this DEM is to estimate elevations of lands close to sea level, rather than characterize drainage correctly, the ad hoc response to the TOPOGRID plateau problem is not as unreasonable as would have been the case were this data to be used for analyzing hydrology. Nevertheless, modification of the tolerance values and other parameters within TOPOGRID, and inclusion of additional vertical data in areas of known errors (determined through the use of diagnostic outputs within the TOPOGRID function), probably could have substantially diminished the plateau problem in the vicinity of the first topographic contour.  Because the plateau problem around the edge of tidal wetlands was often caused largely by the relative complexity of the wetland supplemental contour compared with other contours, the case for dividing the data as we did is probably greater along the wetland boundary than along the first contour.

Also see the sections on Positional Accuracy (Horizontal and Vertical) and process steps.

Positional_Accuracy:

Horizontal_Positional_Accuracy:

Horizontal_Positional_Accuracy_Report:

The source data generally were 1:24,000 scale or better. Therefore our use of 30 meter cells deteriorated the horizontal accuracy. Assuming that 90% of well defined points are within 30 meters of the indicated location would imply a scale of 1:60,000 under National Map Accuracy Standards. (That assumption may be conservative because 100% of the points in a 30 meter cell are less than 21.2 meters of the center of the cell.  If the input map has 1:24,000 scale [well defined points within 12.2 meters]  and errors are random, then more than 90% of the points will be within 24.5 meters of the indicated location, which would imply a scale of 1:50,000.) However, our interpolation program may further deteriorate the horizontal accuracy.  Under some circumstances, the horizontal error appears to be as great as the width of a cell.  Given that the diagonal in this case would be 42.4 m, if errors are random, then the scale might be as poor as 1:86,000 in areas where those 1-cell errors are common.

Neither stream networks nor lake features were used as inputs into the TOPOGRID function in creation of this data set for reasons discussed in the completeness report. The addition of a hydrologic network would increase the accuracy of the resulting DEM.

Quantitative_Horizontal_Positional_Accuracy_Assessment:

Horizontal_Positional_Accuracy_Value: 40-42.5 meters

Horizontal_Positional_Accuracy_Explanation:

In the event the horizontal error is as great as the width of a cell, the diagonal would be 42.4 m.

Vertical_Positional_Accuracy:

Vertical_Positional_Accuracy_Report:

The vertical accuracy of this data set generally corresponds to that of the source data (described below) used in the layer development, plus errors induced through the various processing steps. The procedures used to interpolate between contours do not necessarily correspond to the actual geometry of the land surfaces. Therefore, points that are near a contour have greater accuracy than points that are farther away from a contour. 

In order to assess the vertical accuracy of  DEMs generated by ICF Consulting, Russ Jones of Stratus Consulting Inc. compared DEMs with LIDAR data in two areas: 1) an area south of Rock Hall along the eastern shore of Maryland, and 2) portions of North Carolina. Table 1 within DEM_LidarComparisonTable.doc summarizes the comparison.  The analysis suggests a Root Mean Square (RMS) discrepancy between LIDAR and this DEM approximately one-half of the input contour interval in cases where the contour interval was 1 meter, 5 feet, or 2 meters. If the LIDAR comparison is applicable to Virginia, one would expect an RMS error of approximately one-half the USGS contour interval, with a mean error less than 1/10 the contour interval. See VA_Elevation_Data_Quality.jpg, included in the zip file with which this data is distributed, for a graphic depicting the contour intervals for the USGS 7.5-minute quads in Virginia.

Jones also provided histograms showing the relationship between input contour intervals and the DEM values, for 11 USGS 7.5' topographical quadrangles in the study area from New York to North Carolina, including the Accomack and Irvington quads in Virginia (provided in the zip file with this document). The technical paper by Titus and Wang (2008, listed in the citation section above) analyzes the results of that comparison. Note that this comparison was conducted on the initial DEM generated with TOPOGRID. As a result of this analysis, the minimum and maximum elevation limits were constrained to ensure that the resulting elevations were in accordance with the input data. (See "First-contour truncating" in the process step on interpolation of Digital Elevation Model). This metadata only discusses the two quads in Virginia, plus two quads in Maryland that were particularly problematic.   

For the Accomack quad, the DEM under-estimates the low land by 18%. Examining an overlay of the DEM and the DLG's, the discrepancy appears to be explained by the failure of the TOPOGRID program to interpolate the narrow peninsulas, valleys, and small islands. This was corrected by setting the minimum and maximum values of midland and lowland (see process step #4 - "Interpolation of Digital Elevation Model", which provides a description of the processing of the three elevation areas). The DEM created a plateau at the 5-ft contour, with an area twice the size of the discrepancy. Thus, in effect, the DEM estimates the DLG's 5-ft contour to be between 5 and 5.1 feet. The discrepancy for lands between 5-10 and 10-15 feet are less than 0.5%, which suggests that part of the problem for the lowest land may be explained by areas where the dry land below 5ft is too narrow to take up an entire cell (see discussion of South River, Maryland, below). The DEM for the Irvington quad duplicated the area implied by the DLG within 0.1 hectares, the best of the 11 quads Jones examined. The discrepancies were more serious, however, for two quads in Maryland:  Broomes and South River respectively. For South River the DEM under estimates the amount of land below 5 ft by 50%.  However, it is within 5% and 1% for the areas between 5-10 and 10-15ft, respectively. This error appears to have resulted because the land is sufficiently steep that particular cells will have more than one contour crossing them. The DEM assigns an average elevation to the cell.  Assuming that the contours cross the centers of cells randomly, one would normally expect that the amount of higher and lower ground being "averaged in" would approximately offset each other, so that the DEM should find the same amount of land within a given elevation range as the input DLG's. Indeed, this appears to be the case for land at 10-15 ft.  For land below 5ft, however, there is higher ground but no lower ground to be "averaged in." Therefore, an upward bias is created for the lowest areas.  Such an upward bias in the lowest contour range could have been avoided with an algorithm that calculated elevations for points rather than cells, or using a much smaller cell size.  Doing so, however, would have increased the costs of this study several fold. The net impact is was that the DEM, in effect, estimated the 5-ft contour to be approximately 7.3 ft above the vertical datum for South River. The Broomes quad had a similar upward bias, effectively treating the 5-ft contour as a 5.8-ft contour.  

The experience with those two quads in Maryland should serve as a caution that in Virginia our results may be much less accurate in areas with slopes steep enough to have two contours within 30 meters (e.g. slopes greater than 6% with 5-ft contours, or 12% with 10ft contours), especially in the area above the lowest contour.  (Our first-contour truncating mitigates this upward bias below the first contour; for reasons explained in the metadata for the Maryland study (dem_MD_shw_cm). In Virginia, that caution is applicable to much of the land to the east of Chesapeake Bay, other than the immediate Hampton Roads area.  

The results of the "11 quadrangle" analysis are shown in DEM_Comparison_with_DLG_11_quads.xls., which is included in the zip file distributed with this dataset.

Quantitative_Vertical_Positional_Accuracy_Assessment:

Vertical_Positional_Accuracy_Explanation:

See vertical accuracy report.

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator: US Geological Survey

Title:

Large Scale USGS Digital Line Graph (DLG)

Geospatial_Data_Presentation_Form: vector digital data

Online_Linkage: <http://edc.usgs.gov/geodata/dlg_large/states/VA.html>

Source_Scale_Denominator: 24,000

Type_of_Source_Media: Digital Vector Data

Source_Time_Period_of_Content:

Source_Currentness_Reference:

publication date

Source_Contribution:

Spatial data and attributes.  The DLGs provided were the single most important source of elevation data for the DEM creation. Source contours are 5 feet and 10 feet. The zip file distributed with this metadata includes a graphic defining the contour intervals of the input data: VA_Elevation_Data_Quality.jpg

Source_Information:

Source_Citation:

Citation_Information:

Originator: Henan Institute of Geography, China

Publication_Date: Unpublished Material

Publication_Time: Unknown

Title:

Coastal Digital Line Graphs (DLG) created from USGS Digital Raster Graphs

Geospatial_Data_Presentation_Form: vector digital data

Source_Scale_Denominator: 24,000

Type_of_Source_Media: Digital vector data

Source_Time_Period_of_Content:

Source_Currentness_Reference:

publication date

Source_Contribution:

Spatial data and attributes. Contours below 40 feet, for areas where USGS 1:24,000 DLG's were not available.  Source contours are 5 feet and 10 feet.  The attached zip file includes graphic a spreadsheet defining the contour intervals of the input data. VA_Elevation_Data_Quality.jpg

Contours digitized from USGS 7.5 minute Digital Raster Graphics (DRGs). See Institute_of_Geography_DLG.doc, included in the zip file with which this data is distributed, for a list of the 7.5-minute quads where we used the Institute of Geography DLG's.

Source_Information:

Source_Citation:

Citation_Information:

Originator: National Oceanic Service

Publication_Date: Unknown

Publication_Time: Unknown

Title:

NOS Tide Observation Data

Geospatial_Data_Presentation_Form: tabular digital data

Online_Linkage: <http://co-ops.nos.noaa.gov/bench.html>

Source_Scale_Denominator: 24,000

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Multiple_Dates/Times:

Single_Date/Time:

Calendar_Date: 1960

Time of Day: 1978

Source_Currentness_Reference:

Relative to the 1960-1978 Tidal Epoch

Source_Contribution:

Spatial coordinates and elevations of MTL relative to mean lower low water (MLLW), the elevation of MLLW relative to several benchmarks nearby, and the elevations of these benchmarks relative to NAVD88 for 26 tide gages in or around Virginia.

Source_Information:

Source_Citation:

Citation_Information:

Originator: Originator: National Oceanic Service

Publication_Date: 2000

Title:

NOS Tide Estimation Data. Tide Tables 2000, High and Low Water Predictions, East Coast of North and South America including Greenland

Geospatial_Data_Presentation_Form: document

Type_of_Source_Media: paper

Source_Contribution:

Horizontal location and spring high tide ranges for 152 tide gages in or around Virginia.

Source_Information:

Source_Citation:

Citation_Information:

Originator: U.S. Environmental Protection Agency

Publication_Date: 2006

Title:

Coastal Wetlands Data: Virginia

Source_Scale_Denominator: 24,000

Type_of_Source_Media: online

Source_Contribution:

Horizontal location of upper and lower limits of tidal wetlands. See Readme.doc (distributed in the zip file with this data set), for directions on how to download the Coastal Wetlands Data .  See also the technical report for this project J.G. Titus and J. Wang, 2008. Maps of lands close to sea level along the middle Atlantic coast of the United States: an elevation data set to use while waiting for LIDAR. In: Background Documents Supporting Climate Change Science Program Synthesis and Assessment Product 4.1: Coastal Elevations and Sensitivity to Sea Level Rise [J.G. Titus and E.M. Strange (eds.)]. EPA430R07004, U.S. Environmental Protection Agency, Washington, DC.

Source_Information:

Source_Citation:

Citation_Information:

Originator: U.S. Fish and Wildlife Service

Publication_Date: Various

Title:

US Fish and Wildlife National Wetlands Inventory (NWI) Data

Geospatial_Data_Presentation_Form: vector digital data

Online_Linkage: <http://wetlands.fws.gov/downloads.htm>

Source_Scale_Denominator: 24000

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Source_Currentness_Reference:

publication date

Source_Contribution:

Horizontal location of upper and lower limits of tidal wetlands.  See metadata for Coastal Wetlands Data:  Virginia for additional details on the contribution of this data set to the analysis.

Source_Information:

Source_Citation:

Citation_Information:

Originator: Proudman Oceanographic Laboratory (POL)

Publication_Date: 2000

Title:

Permanent Service for Mean Sea Level (PSMSL) - Sea Level Rise Trend Data

Other_Citation_Details:

The PSMSL is a member of the Federation of Astronomical and Geophysical Data Analysis Services (FAGS) established by the International Council of Scientific Unions (ICSU).

Online_Linkage: <http://www.nbi.ac.uk/psmsl/datainfo/rlr.trends>

Source_Scale_Denominator: 24,000

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Source_Currentness_Reference:

publication date

Source_Contribution:

Spatial location and estimates of the rate of sea level rise.

Elevation contours were used to generate a surface of sea level rise rates.

Process_Step:

Process_Description:

Process of Input Elevation Data 

Input elevation contour lines were either 1:24,000 scale USGS or the Institute of Geography DLGs. They were appended and then projected into Albers projection.

Process_Date: Unknown

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Jue Wang

Contact_Organization: GIS Practice, ICF Consulting, Inc.

Contact_Position: GIS Analyst

Contact_Address:

Address_Type: mailing and physical address

Address:

9300 Lee Highway

City: Fairfax

State_or_Province: VA

Postal_Code: 22031

Country: U.S.A.

Contact_Voice_Telephone: 703-218-2766

Contact_Facsimile_Telephone: 703-934-3974

Contact_Electronic_Mail_Address: jwang@icfconsulting.com

Hours_of_Service: 9:30 - 5:30 EST

Process_Step:

Process_Description:

Process of Tidal Record

Calculating the Elevation of Spring High Water Supplemental Contour 

1) Creation of Mean Tide Level Surface. National Oceanic Service (NOS) tide observation data, i.e., the latitudes and longitudes, the elevations of mean tide level (MTL) above mean lower low water (MLLW), the elevations of MLLW relative to several benchmarks, and the elevations above NAVD88 of these benchmarks of 25 tide gages in Virginia were downloaded from the NOS website. The elevations of mean tide level relative to NAVD88 were calculated and then converted to a NGVD29 using the difference surface between NAVD88 and NGVD29. A point coverage was then created with such data and projected into Albers projection. Using the point coverage as a reference, artificial contour lines were created with consideration of shorelines via heads-up digitizing and then used to interpolate the mean tide level surface using TOPOGRID. As the tidal epoch used for the MTL data was 1960-1978, a separate sea level rise rate surface was created by interpolating actual sea level rise data (trend) from the Proudman Oceanographic Laboratory website and was used to adjust the mean tide level to years corresponding to other data sets, such as NWI data, so that the wetland boundary would represent spring high tide for the year the map imagery was taken.

2) Creation of Spring Tide Range Surface.

From Table 2 of "Tide Tables 2000, High and Low Water Predictions, East Coast of North and South America including Greenland", the latitudes, longitudes and spring high tide ranges of more than 150 tide gages were obtained and used to create a point coverage. Using the point coverage as a reference, artificial contour lines were created with consideration of shorelines and then used to interpolate the spring high tide range surface with TOPOGRID method.

3) Creation of a Spring High Water Level Surface. A spring high water level surface was created by adding half of spring tide range onto mean tide level surface.

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Jue Wang

Contact_Organization: GIS Practice, ICF Consulting, Inc.

Contact_Position: GIS Analyst

Contact_Address:

Address_Type: mailing and physical address

Address:

9300 Lee Highway

City: Fairfax

State_or_Province: VA

Postal_Code: 22031

Country: U.S.A.

Contact_Voice_Telephone: 703-218-2766

Contact_Facsimile_Telephone: 703-934-3974

Contact_Electronic_Mail_Address: jwang@icfconsulting.com

Hours_of_Service: 9:30 - 5:30 EST

Process_Step:

Process_Description:

Processing of Tidal Wetland Data: Calculating the Horizontal Position of Spring High Water Supplemental Contour. 

1) NWI data were imported into ArcInfo coverage format and projected into Albers projection. A data set representing tidal wetlands was generated using the subtidal and intertidal subsystems for marine and estuarine categories, tidal subsystem for riverine category, and the tidal or non-tidal water regimes for lacustrine and palustrine categories. The upper and lower limits of tidal wetlands were then extracted from this tidal wetland data set.

For the marine and estuary categories, the boundaries between M1 (subtidal) and M2 (intertidal),  E1 (subtidal) and E2 (intertidal) determined the lower boundaries of tidal wetland, and the boundaries of M2 and E2 with upland and other non-tidal wetland or non-tidal open water, determined the upper boundaries of tidal wetland.  For the riverine category, the boundaries between R1 (tidal) and upland as well as other non-tidal wetland or non-tidal open water determined the upper limit. For Lacustrine and Palustrine categories, tidal or non-tidal water regimes determined the upper boundaries of tidal wetland.

2) The upper and lower limits of tidal wetlands extracted from the US FWS NWI wetland data was used to generate supplemental contours. Elevations assigned to these contours were derived from spring high tide level and mean tide level surface grids respectively. However, while the upper wetland boundary was used as a supplemental contour for input into the DEM, the lower boundary was used for reporting the area of wetlands but not for elevations, because the project manager decided not to report wetland elevations. 

See the larger report on specific USGS 7.5' quadrangles used: J.G. Titus and J. Wang, 2008. Maps of lands close to sea level along the middle Atlantic coast of the United States: an elevation data set to use while waiting for LIDAR. In: Background Documents Supporting Climate Change Science Program Synthesis and Assessment Product 4.1: Coastal Elevations and Sensitivity to Sea Level Rise [J.G. Titus and E.M. Strange (eds.)]. EPA430R07004, U.S. Environmental Protection Agency, Washington, DC.   See also the metadata accompanying the Virginia Wetland polygon dataset used in this study.

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Jue Wang

Contact_Organization: GIS Practice, ICF Consulting, Inc.

Contact_Position: Senior GIS Analyst

Contact_Address:

Address_Type: mailing and physical address

Address:

9300 Lee Highway

City: Fairfax

State_or_Province: VA

Postal_Code: 22031

Country: U.S.A.

Contact_Voice_Telephone: 703-218-2766

Contact_Facsimile_Telephone: 703-934-3974

Contact_Electronic_Mail_Address: jwang@icfconsulting.com

Hours_of_Service: 9:30 - 5:30 EST

Process_Step:

Process_Description:

Interpolation of Digital Elevation Model 

1) The study area was divided into four parts: tidal wetlands, lowland, midland, and upland. 

"Tidal Wetlands" represents the tidal wetlands as classified from the wetland layer.

Lowland represents the area between the tidal wetlands and the lowest topographic contour available that is generally above the tidal wetlands. Depending on the contour interval of the input data, this lowest contour may have been 5 feet or 10 feet  relative to NGVD29.  

Midland represents the area above the lowest contour we used and below the highest USGS contour lines (40 foot or 12 meters NGVD29) used. 

Upland represents land above the midland contour (i.e., above the 40 foot or 12 meter NGVD29 contour). 

Boundary coverages were created for tidal wetlands, lowland, and midland using appropriate elevation contours or upper and lower limits of tidal wetland. However, we are not making the tidal wetland interpolations available in this dataset due to the lack of a theoretical justification for believing that interpolation to have any information content. (At best, the wetland elevation interpolations might be used for graphical representations of the impact of sea level rise.) We will retain a companion dataset with elevations stored as floating point double precision, which may be made available for the sole purpose of evaluating any graphical representations that use wetland elevations.  We provide a wetland dataset (in both raster and vector formats) so that the user can distinguish tidal wetlands from open water for cells with no data.  

2) Using the TOPOGRID function, the DEMs were interpolated with a predetermined cell size of 30 meters for the lowland, midland, and upland areas using contour lines described in the section "Process of Input Elevation Data" and supplemental contours from the combination of NWI wetland data and NOAA tidal record contours. A common starting coordinate was set for all three areas to ensure alignment of the separate layers after processing. The minimum and maximum limits were set for each process according to the input elevation data to ensure the resulting elevations were in accordance with the input data.  See "first-contour truncating" (#4) below.  The iteration was set to 40, the horizontal standard error tolerance was set to 2 to minimize the depression caused by inappropriate tend calculation, and the drainage enforcement option was turned on to remove isolated depressions. 

The following represents the options used in TOPOGRID: 

topogrid dem_mid_ft 30 

contour topo_cntr elevation 

xyzlimits 1602000 # 1833000 # 5.0001 

boundary topo_bnd_up 

iterations 40 

tolerances # 2 

enforce on 

end 

3) The interpolated DEMs were displayed against input elevation data and visually checked. These visual checks would show gross errors, but not necessarily errors in which the amount of low land is over- or underestimated by 10-40 percent (additionally, see Data Quality, Positional Accuracy section). If obvious errors such as artificial depressions occurred, supplemental elevation lines were added by heads-up digitizing to the input contour lines and the interpolation was repeated. 

4) First-contour truncating. 

As a result of the comparison between the initial DEM and the source contours for 11 USGS quadrangles (see vertical accuracy report), we decided to reset the DEM values to coincide with source contours. Whenever TOPOGRID calculated a value greater than the first contour within the "lowland", we reset the value to 0.001 less than the first contour. Whenever TOPOGRID calculated a midland value less than the first contour, we reset the value to 0.001 greater than the first contour. Given the rounding of this integer dataset, all such values are effectively rounded to the bounding contour value between midland and lowland (e.g. 5 feet). Although this approach leaves us with some plateaus, we have fewer plateaus than we had when we did not divide the data; and dividing the data left us with fewer cases of midland and lowland values being outside of their appropriate ranges. 

5) The DEMs of each separate part were eventually merged into the final DEM with the MERGE function within the ESRI GRID module.

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Jue Wang

Contact_Organization: GIS Practice, ICF Consulting, Inc.

Contact_Position: Senior GIS Analyst

Contact_Address:

Address_Type: mailing and physical address

Address:

9300 Lee Highway

City: Fairfax

State_or_Province: VA

Postal_Code: 22031

Contact_Voice_Telephone: 703-218-2766

Contact_Facsimile_Telephone: 703-934-3974

Contact_Electronic_Mail_Address: jwang@icfconsulting.com

Hours_of_Service: 9:30 - 5:30 EST

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Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Raster

Raster_Object_Information:

Raster_Object_Type: Grid Cell

Row_Count: 9796

Column_Count: 7149

Vertical_Count: 1

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Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Map_Projection:

Map_Projection_Name: Albers Conical Equal Area

Albers_Conical_Equal_Area:

Standard_Parallel: 29.500000

Standard_Parallel: 45.500000

Longitude_of_Central_Meridian: -96.000000

Latitude_of_Projection_Origin: 23.000000

False_Easting: 0.000000

False_Northing: 0.000000

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: row and column

Coordinate_Representation:

Abscissa_Resolution: 30.000000

Ordinate_Resolution: 30.000000

Planar_Distance_Units: meters

Geodetic_Model:

Horizontal_Datum_Name: North American Datum of 1983

Ellipsoid_Name: Geodetic Reference System 80

Semi-major_Axis: 6378137.000000

Denominator_of_Flattening_Ratio: 298.257222

Vertical_Coordinate_System_Definition:

Altitude_System_Definition:

Altitude_Datum_Name: SHW (year 1980)

Altitude_Resolution: 1

Altitude_Distance_Units: cm

Altitude_Encoding_Method: Explicit elevation coordinate included with horizontal coordinates

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Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: dem_va_shw_cm.vat

Entity_Type_Definition:

DEM

Entity_Type_Definition_Source:

ICF Consulting Inc.

Attribute:

Attribute_Label: Rowid

Attribute_Definition:

Internal feature number.

Attribute_Definition_Source:

ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:

Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: VALUE

Attribute:

Attribute_Label: Value

Attribute_Definition:

Elevation in cm relative to SHW (2000)

Attribute_Definition_Source:

Derived from multiple input sources

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 1

Range_Domain_Maximum: 2000

Attribute_Units_of_Measure: cm

Attribute_Measurement_Resolution: 1

Beginning_Date_of_Attribute_Values: 2000

Ending_Date_of_Attribute_Values: 2000

Attribute_Value_Accuracy_Information:

Attribute_Value_Accuracy: 1 cm

Attribute_Value_Accuracy_Explanation:

See vertical and horizontal accuracy reports

Attribute_Measurement_Frequency:

As needed

Attribute:

Attribute_Label: COUNT

Attribute_Definition:

Number of cells of corresponding value

Attribute_Definition_Source:

ESRI

Overview_Description:

Entity_and_Attribute_Overview:

Values expressed in cm above SHW

Entity_and_Attribute_Detail_Citation:

ICF Consulting Inc.

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Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: US Environmental Protection Agency, Climate Change Division

Contact_Address:

Address_Type: mailing address

Address:

USEPA (6207-J)

Address:

1200 Pennsylvania Ave. NW

City: Washington

State_or_Province: DC

Postal_Code: 20460

Country: U.S.A.

Contact_Voice_Telephone: 202-343-9990

Contact_Facsimile_Telephone: 202-343-2338

Contact_Electronic_Mail_Address: climatechange@epa.gov

Resource_Description: The dataset is being distributed by the US Environmental Protection Agency.

Distribution_Liability:

Although this data was created under the direction of the EPA, no warranty expressed or implied is made regarding the accuracy or utility of the data.  Neither EPA nor the data developers shall be held liable for any use of the data and information described and/or contained herein.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Transfer_Size: 13.628

Custom_Order_Process:

Data available from Alan Cohn at 202-343-9814.

Technical_Prerequisites:

Requires software capable of displaying raster data.

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Metadata_Reference_Information:

Metadata_Date: 20080902

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: Stratus Consulting Inc. (Jones)

Contact_Person: Russ Jones, Jim Titus, and Jue Wang

Contact_Position: Managing Analyst (Jones)

Contact_Address:

Address_Type: mailing and physical address

Address:

1881 9th St. Suite 201 (Jones)

City: Boulder

State_or_Province: CO

Postal_Code: 80306

Country: U.S.A.

Contact_Voice_Telephone: 303-381-8000 (Jones)

Contact_Voice_Telephone: 202-343-9307 (Titus)

Contact_Facsimile_Telephone: 303-381-8200 (Jones)

Contact_Electronic_Mail_Address: rjones@stratusconsulting.com

Contact_Electronic_Mail_Address: Titus.Jim@epamail.epa.gov

Hours_of_Service: 9:00 - 5:00 MST

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998

Metadata_Time_Convention: local time

Metadata_Security_Information:

Metadata_Security_Classification: Unclassified

Metadata_Extensions:

Online_Linkage: http://www.esri.com/metadata/esriprof80.html

Profile_Name: ESRI Metadata Profile

Metadata_Extensions:

Online_Linkage: http://www.esri.com/metadata/esriprof80.html

Profile_Name: ESRI Metadata Profile

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