SIR2012_5290_ACAD_Inundationlines

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What does this data set describe?

Title: SIR2012_5290_ACAD_Inundationlines
Abstract:
The U.S. Geological Survey (USGS) investigated salt marshes in and around Acadia National Park (ANP) from Penobscot Bay to the Schoodic Peninsula to map the potential for landward migration of marshes using a static inundation model of a sea-level rise (SLR) scenario of 60 centimeters (cm) (2 ft). This data layer contains a set of four elevation contours (inundation lines) for each marsh in the study area: (a) the current (2010) highest elevation of the marsh surface (HME) for each salt marsh in the study area, (b) inundation contours for an elevation 60 cm above the salt marsh surface, and (c) 95-percent confidence interval contours, 26 cm above and (d) below the 60-cm inundation contours. The elevation contours were derived from LiDAR data (2-meter horizontal resolution) collected in 2010. The 95-percent confidence intervals on the 60-cm inundation contours illustrate how the uncertainty in the LiDAR data translates into uncertainty in the land area that would be inundated. The inundation lines are not meant as predictions of marsh migration, only as indications of where migration may occur if conditions permit.
Supplemental_Information:
Geodatabase product of a USGS study funded by National Park Service Climate Change Response funding, NPS PMIS # 161531, "Inventory and Protection of Salt Marshes from Risks of Sea Level Rise at Acadia National Park, Maine", 2012.
The database layers are collectively termed "appendix 1" of the USGS SIR report. Database layers included in appendix 1 include: Surveyed benchmarks used in surveying exercise (SIR2012_5290_ACAD_SurveyedBMs); Surveyed marsh points used for quality control for LiDAR data (SIR2012_5290_ACAD_Surveyedmarshpoints); Surveyed elevation reference marks for each surveyed marsh (SIR2012_5290_ACAD_SurveyedERMs); Salt marshes inventoried for this study (SIR2012_5290_ACAD_Saltmarshpolys); Inundation lines for each marsh under 60 cm of sea level rise (SIR2012_5290_ACAD_Inundationlines); Potential barriers to migration of salt marshes (SIR2012_5290_ACAD_Potentialbarriers).
The inundation lines presented are in no way a prediction of whether marsh migration will actually occur, only indications of where land will be inundated and would therefore be available for migration under 60 cm. of sea level rise.
  1. How should this data set be cited?

    U.S. Geological Survey, Maine Water Science Center, Augusta, Maine, 2012, SIR2012_5290_ACAD_Inundationlines: U.S. Geological Survey, Augusta, Maine.

    Online Links:

    This is part of the following larger work.

    Nielsen, Martha G., and Dudley, Robert W., 2012, Estimates of Future Inundation of Salt Marshes in Response to Sea Level Rise in and Around Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report SIR 2012-5290, U.S. Geological Survey, Reston, Virginia.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: -68.813014
    East_Bounding_Coordinate: -68.001536
    North_Bounding_Coordinate: 44.586468
    South_Bounding_Coordinate: 44.145271

  3. What does it look like?

  4. Does the data set describe conditions during a particular time period?

    Calendar_Date: 2010
    Currentness_Reference: Ground condition

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: Vector digital data

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the data set?

      This is a Vector data set. It contains the following vector data types (SDTS terminology):

      • String (382)

    2. What coordinate system is used to represent geographic features?

      The map projection used is NAD_1983_UTM_Zone_19N.

      Projection parameters:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -69.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0

      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.0001
      Ordinates (y-coordinates) are specified to the nearest 0.0001
      Planar coordinates are specified in meters

      The horizontal datum used is D North American 1983.
      The ellipsoid used is GRS 1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.

      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: North_American_Vertical_Datum_1988
      Altitude_Resolution: 1.0
      Altitude_Distance_Units: Meters
      Altitude_Encoding_Method: Attribute values

  7. How does the data set describe geographic features?

    SIR 2012-5290 ACAD Inundation Lines
    Polyline features (Source: Esri)

    OBJECTID
    Internal feature number (Source: Esri)

    Sequential unique whole numbers that are automatically generated.

    SHAPE
    Feature geometry (Source: Esri)

    Coordinates defining the features

    Contour
    Elevation contour, in meters above the North American Vertical Datum of 1988 (NAVD88) (Source: User defined)

    Range of values
    Minimum:1.6
    Maximum:3.9
    Units:Meters above NGVD88
    Resolution:.02

    Line_Type
    Attribute defining the type of contour line in relation to sea level rise estimates at the individual salt marshes. (Source: User defined)

    ValueDefinition
    HighMarshELHighest elevation of the marsh surface, as represented in the "Contour" attribute.
    SLR_estLine representing the highest marsh surface plus 60 cm of sea level rise (otherwise referred to as the sea level rise esitmate) (Value represented in the "Contour" attribute).
    SLR_conf_upperUpper 95-percent confidence interval on the sea level rise estimate, defined as SLR_est + 26 cm. (Value represented in the "Contour" attribute)
    SLR_conf_lowerLower 95-percent confidence interval on the sea level rise estimate, defined as SLR_est - 26 cm. (Value represented in the "Contour" attribute)

    Marsh_ID
    ID number of marsh that each inundation contour lines applies to. Refers to the attribute "Marsh_ID" in the "SIR2012_5290_ACAD_Saltmarshpolygons" feature class. (Source: U.S. Geological Survey)

    Range of values
    Minimum:2
    Maximum:124
    Units:User-defined identification number.

    Marsh_ID_2nd
    ID of secondary set of marsh polygons associated with the inundation lines, if applicable. Used when several nearby marsh polygons have the same inundation elevation values. (Source: U.S. Geological Survey)

    Range of values
    Minimum:2
    Maximum:124
    Units:User-defined identification number.

    Marsh_ID_3rd
    ID of tertiary set of marsh polygons associated with the inundation lines, if applicable. Used when several nearby marsh polygons have the same inundation elevation values. (Source: U.S. Geological Survey)

    Range of values
    Minimum:2
    Maximum:124
    Units:User-defined identification number.

    Shape_Length
    Length of feature in internal units (meters). (Source: Esri)

    Positive real numbers that are automatically generated

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

  2. Who also contributed to the data set?

    Produced in cooperation with the National Park Service. LiDAR data for the Northeast funded largely by USGS American Reinvestment and Recovery Act funds, and provided by the Maine Office of GIS (MEGIS). These data are in the public domain unless otherwise stated; please credit the USGS and the National Park Service in products derived from these data.

  3. To whom should users address questions about the data?

    Martha G. Nielsen
    U.S. Geological Survey, Maine Water Science Office
    Hydrologist
    196 Whitten Rd.
    Augusta, ME 04330

    207-622-8201 x116 (voice)
    207-622-8204 (FAX)
    mnielsen@usgs.gov

Why was the data set created?

The purpose of this datalayer is to show lowland areas surrounding salt marshes in the study area that would be inundated after 60 cm of sea level rise, and would therefore provide potential areas for salt marshes to migrate into, if accretionary processes accompanying sea level rise permit. The 95-percent confidence intervals on the elevation data are also shown, to illustrate how the uncertainty in the LiDAR data translate into uncertainty in the land area that would be inundated.

How was the data set created?

  1. From what previous works were the data drawn?

    LiDAR data for the Northeast (source 1 of 4)
    Photo Science, Inc., Unpublished material, State of Maine (raster digital elevation model (DEM)): LIDAR for the North East – ARRA and LiDAR for the North East Part II. (USGS Contract: G10PC00026, ARRA LIDAR Task Order Numbers) USGS Contract: G10PC00026 Task Order Number: G10PD02143 Task Order Numbers: G10PD01027 (ARRA) and G10PD02143 (non-ARRA).

    Other_Citation_Details:
    The LiDAR data were the primary outside source information for the study. The LiDAR data have a grid cell size of 2 m. Individual data tiles are 751x751 grid cells (1.5 km x 1.5 km) in size. As of October 2012, the LiDAR data are still available only from state GIS offices. Final publication for public download has not been announced. The project area required LiDAR to be collected on 2.0-m ground sample distance (GSD) or better and processed to meet a bare earth vertical accuracy of 15 centimeters root mean squared error (RMSEz) or better. Raster DEMs were tested by Photo Science for both vertical and horizontal accuracy. All data are seamless from one tile to the next, no gaps or no data areas. The vertical unit of the data file is in decimal meters with two-decimal point precision. The reported RMSEz was 0.113 m. The USGS independently developed a RMSEz for saltmarsh land cover types to be 0.133 m.
    Type_of_Source_Media: External hard drive
    Source_Scale_Denominator: 2400
    Source_Contribution:
    The LiDAR data were the primary outside data used in the study. The main use was to create accurate contours showing areas of upland that would be inundated with 60 cm of sea level rise (SLR) adjacent to saltmarshes in and around Acadia National Park. The USGS conducted an independent accuracy assessment of the elevation data to create 95-percent confidence interval contours on the SLR inundation contours. The data tiles were joined together into larger mosaics, and shaded relief images were created to for visualization of the land surface and to identify location and shape of potential barriers to migration of salt marshes.

    LT 2008 (source 2 of 4)
    of, Maine Office GIS, 2009, Low Tide Orthophotos 2008..

    Online Links:

    Type_of_Source_Media: Digital files
    Source_Scale_Denominator: 2400
    Source_Contribution:
    Low-tide orthophotos from 2008 were used to delineate the polygon boundaries of most of the saltmarsh polygons used in the study, by looking at the visible changes in vegetation. They also were used to help identify the potential barriers to migration and to identify the type of barrier (road or railroad grade).

    Bing maps imagery (source 3 of 4)
    USGS, 2010, Microsoft Bing bird's eye imagery: Microsoft Corporation, Redmond, Washington.

    Online Links:

    Other_Citation_Details:
    Copyright 2010 DigitalGlobe, Image courtesy of USGS Copyright 2012 Microsoft Corporation
    Type_of_Source_Media: Digital files
    Source_Scale_Denominator: 1200
    Source_Contribution:
    The Bing map server was used to fill in detailed aerial photo information in locations where the 2008 Low Tide photos were not available and other Maine aerial photos were not detailed enough to map the boundaries of salt marshes in the study area. Two salt marshes were digitized using the Bing maps imagery.

    Saltmarsh polygons (source 4 of 4)
    U.S. Geological Survey, 2012, SIR2012_5290_ACAD_Saltmarshpolygons: U.S. Geological Survey, Maine Water Science Center, Augusta, Maine.

    Online Links:

    This is part of the following larger work.

    U.S. Geological Survey, Maine Water Science Center, 2012, Appendix 1 of USGS SIR 2012-5290, Estimates of future inundation of salt marshes in response to sea level rise in and around Acadia National Park, Maine, by Martha Nielsen and Robert Dudley.: U.S. Geological Survey, Maine Water Science Center, Augusta, Maine.

    Online Links:

    Type_of_Source_Media: digital files
    Source_Scale_Denominator: 2400
    Source_Contribution:
    The saltmarsh polygons contain the elevation data used for each set of inundation lines. Each saltmarsh polygon has data for: the highest marsh elevation (HME), the HME plus 60 cm (SLR_est), and the upper 95-percent confidence interval and lower 95-percent confidence interval (SLR_est + 26 cm and SLR_est - 26 cm, respectively). The inundation lines were created one saltmarsh at a time, using the data in the saltmarsh polygon attribute table.

  2. How were the data generated, processed, and modified?

    Date: 2011 (process 1 of 7)
    The Saltmarsh polygon layer was checked and cleaned up in preparation for creating the contour lines. Elevation data in the saltmarsh polygon attribute table was checked.

    Date: 2011 (process 2 of 7)
    A tool was created in ArcGIS, with the help of Curtis Price (USGS, South Dakota Water Science Center), that combined a series of steps for creating the inundation contours into one process that could easily be repeated for each of the 110 salt marshes in the study area.
    The tool (called "Contour and Smooth") extracted data from a selected saltmarsh polygon (data containing the individual elevations to be contoured for each marsh), created a set of raw contours based on the LiDAR elevation data, smoothed the contours, and combined the smoothed contours into an output feature class for that particular marsh. This tool was run for most of the 110 salt marshes for which inundation contours were needed (some marshes were so close together that the tool could be run just once for both marshes).
    Specific steps for using the tool: 1. User selects a saltmarsh polygon feature and knows which dataset contains the lidar elevation data needed for extracting the contours. 2. Run the tool: (a) The row in the saltmarsh polygon attribute table containing the selected saltmarsh is copied to an internal table for the tool's use (b) Data are extracted from this internal table for the following contours: HighMarshEl, SLR_est, SLR_conf_upper, and SLR_conf_lower. (c) The user specifies an elevation grid (the lidar data) (d) The user specifies a processing extent (a window large enough to contain the expected inundation contours around the saltmarsh selected) (e) The "Contour List" spatial analyst tool is invoked to create one contour line for each of the elevations specified in the internal table, using as elevation input the elevation grid specified. (f) Each contour is smoothed using the "Smooth line" spatial analyst tool, using 5 meters as the smoothing tolerance and PAEK as the smoothing algorithm. (g) A field "Line_Type" is added to each contour, and the tool inputs which type of line the contour represents (see "b" above). (h) All four lines are combined into one output feature layer for each marsh. The user gives the output feature class a name specific to the marsh number. (i) Lines created by the contouring/smoothing steps that are less than 50 m long are eliminated from the output feature class.
    This tool can be used to create many smoothed contour feature classes containing the inundation contour lines.

    Date: 2011 (process 3 of 7)
    The "Contour and Smooth" tool was used to create one set of contours for each marsh in the study area (some marshes were processed together if their elevation data were the same and if they were close together). Each set of contours was saved in an individual feature class, named based on the marsh number (for example "contour34_smooth" for the contours from marsh number 34).
    Each set of contours was checked to make sure that the processing extent was sufficient to contain the full extent of the highest inundation contour. If any of the contours were cut off because the extent was insufficient, the tool was run again with an expanded extent.

    Date: 2011 (process 4 of 7)
    Each set of smoothed contours was trimmed so that the contours started and ended near the appropriate saltmarsh. This was done to eliminate contours that either conflicted with contours from neighboring saltmarshes with differing elevations, and to cut the contours off so that they did not continue along the shoreline well past the saltmarsh in question.
    Small closed contours above or below the inundation lines were eliminated to simplify and clarify where the extent of inundation would lie on the land surface.

    Date: 2011 (process 5 of 7)
    A new feature dataset was created to hold all the edited saltmarsh inundation lines together, organized by the marsh number and line type. The line types were: HighMarshEl (highest marsh elevation, in meters), SLR_est (sea level rise contour for the high marsh elevation + 60 cm), SLR_conf_upper (upper 95-percent confidence interval on the SLR_est), and SLR_conf_lower (lower 95-percent confidence interval on the SLR_est). The contour elevation was retained for each individual contour ("contour" field, as was the marsh number ("marsh_num" field).
    All the "contourXX_smooth" features were copied into this combined feature dataset (inundation_lines).
    The resulting inundation lines dataset was checked against the saltmarsh polygons to ensure that none of the saltmarsh polygons were skipped (except those less than 0.5 ha in size that were on private property - 4 marshes).

    Date: 2012 (process 6 of 7)
    Two fields were addd to the Inundation_Lines feature class: "marsh_num2" and "marsh_num3". These fields were populated with the marsh number of any adjacent marshes with the same elevation data that were covered by this set of lines.

    Date: 2012 (process 7 of 7)
    The inundation lines were edited to create multipart features. For each unique "marsh_num" in the inundation lines features, all the contour lines representing each type of contour were combined, so that each marsh had one multipart feature for each line type, greatly simplifying the final dataset.

  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?

    All attributes in the accompanying data layers have been checked.

  2. How accurate are the geographic locations?

    The locations are based on very-high-resolution aerial photographs and topographic data. Most positions are accurate to within 1.5 meters (m).

  3. How accurate are the heights or depths?

    Where elevations are included in the datasets, the data are accurate to within +/- 26 cm at a 95-percent confidence level.

  4. Where are the gaps in the data? What is missing?

    The inundation lines were produced for all salt marshes in ANP larger than 0.5 hectares (ha). There are inundation contours that cover 110 of the 114 salt marshes in the overall study. Some of the marshes are near one another and there may be only one set of inundation lines for both marshes. The "Marsh_num" ID for the contours represents the primary marsh, and secondary, nearby smaller marshes or other marshes covered by that particular set of contours is represened by the "marsh_num2" or "marsh_num3" items in the attribute table.

  5. How consistent are the relationships among the observations, including topology?

    The contours are derived from the LiDAR data, and although every effort has been made to quantify the random errors inherent in the LiDAR data, any site-specific systematic errors in the LiDAR data tiles would also translate into the inundation contours.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: None.
Use_Constraints: No legal use constraints.

  1. Who distributes the data set? (Distributor 1 of 1)

    U.S. Geological Survey
    Ask USGS -- Water Webserver Team
    445 National Center
    Reston, VA 20192
    USA

    1-888-275-8747 (1-888-ASK-USGS) (voice)
    <http://water.usgs.gov/user_feedback_form.html>

  2. What's the catalog number I need to order this data set?

    Downloadable Data

  3. What legal disclaimers am I supposed to read?

    This database, identified as “SIR2012_5290_ACAD_Inundationlines”, has been approved for release and publication by the U.S. Geological Survey (USGS). Although this database has been subjected to rigorous review and is substantially complete, the USGS reserves the right to revise the data pursuant to further analysis and review. Furthermore, it is released on condition that neither the USGS nor the U.S. Government may be held liable for any damages resulting from its authorized or unauthorized use. The use of firm, trade, or brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey. The names mentioned in this document may be trademarks or registered trademarks of their respective trademark owners.

  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 20-Dec-2012
Metadata author:
U.S. Geological Survey, New England Water Science Center, Maine Office
Hydrologist
196 Whitten Rd.
Augusta, ME 04330
USA

207-622-8201 (voice)
mnielsen@usgs.gov

Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

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