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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014

Dates

Publication Date
Start Date
2013-11
End Date
2014-06

Citation

Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics–Four sites in New York, New Jersey, and Virginia, 2010–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P944FPA4.

Summary

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive [...]

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Attached Files

Click on title to download individual files attached to this item.

EF_ElevMHW_browse.png
“Example of elevation GeoTIFF raster for Edwin B. Forsythe NWR, New Jersey.”
thumbnail 434.82 KB
Extension: EF14_ElevMHW.zip
EF14_ElevMHW.tif 137.8 MB
EF14_ElevMHW.tif.ovr 2.57 MB
EF14_ElevMHW.tif-ColorRamp.SLD 2.07 KB

Purpose

This dataset indicates the elevation (adjusted for mean high water tidal datum) for each 5x5 m cell within the boundaries of the Edwin B. Forsythe NWR, New Jersey study area according to lidar captured in 2014. See Zeigler and others (2019) for additional details. This dataset is part of a series of spatial datasets used to describe characteristics of barrier islands found along the North American Atlantic coast in order to identify habitat for the federally protected piping plover (Charadrius melodus). Information contained in these spatial datasets was used within a Bayesian network to model the probability that a specific set of landscape characteristics would be associated with piping plover habitat.

Additional Information

Raster Extension

boundingBox
minY39.433941201364604
minX-74.37310411599191
maxY39.76864296308505
maxX-74.09060549074837
files
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contentTypeimage/geotiff
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size144496394
dateUploadedThu Jun 20 12:21:39 MDT 2019
nameEF14_ElevMHW.tif.ovr
contentTypeimage/tiff
pathOnDisk__disk__8f/cf/77/8fcf77a262e4d46c0a2b8bd96218ad4af6e55090
size2697250
dateUploadedThu Jun 20 12:21:39 MDT 2019
nameEF14_ElevMHW.tif-ColorRamp.SLD
contentTypeapplication/sld+xml
pathOnDisk__disk__5a/4f/84/5a4f84b0f9615deb59f0c493ff86ec5c5e9558af
size2124
dateUploadedThu Jun 20 12:21:39 MDT 2019
nameEF14_ElevMHW
nativeCrsEPSG:26918
rasterTypeGeoTIFF

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