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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2012

Dates

Publication Date
Start Date
2012-10-31
End Date
2012-11-06

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 [...]

Contacts

Attached Files

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

EF12_GeoSet.tif 34.47 MB image/geotiff
EF12_GeoSet.tif.vat.dbf 556 Bytes application/unknown
EF12_SubType.tif 68.91 MB image/geotiff
EF12_SubType.tif.vat.dbf 485 Bytes application/unknown
EF_SupClas_GeoSet_SubType_VegDen_VegType_browse.png
“Landcover classification, geomorphic setting, substrate type, vegetation dens...”
thumbnail 307.54 KB image/png
Extension: EF12_SupClas.zip
EF12_SupClas.tif 34.47 MB
EF12_SupClas.tif.vat.dbf 679 Bytes
EF12_SupClas.tif-ColorRamp.SLD 2.07 KB
Extension: EF12_VegDen.zip
EF12_VegDen.tif 68.91 MB
EF12_VegDen.tif.vat.dbf 856 Bytes
EF12_VegDen.tif-ColorRamp.SLD 2.07 KB
Extension: EF12_VegType.zip
EF12_VegType.tif 68.91 MB
EF12_VegType.tif.vat.dbf 856 Bytes
EF12_VegType.tif-ColorRamp.SLD 2.07 KB

Purpose

These categorical raster files map 2012 substrate and vegetation characteristics in 5-m cells. The supervised classification raster (EF12_SupClas.tif) depicts landcover attributes (for example, marsh, sand, water, herbaceous vegetation). It was created with a supervised classification of 2012 aerial imagery. Raster files EF12_SubType.tif, EF12_VegDen.tif, EF12_VegType.tif were reclassified from the supervised classification raster with some manual modifications. EF12_SubType.tif maps discrete substrate types; EF12_VegDen.tif maps discrete categories of vegetation density; EF12_VegType.tif maps discrete vegetation types. Raster file EF12_GeoSet.tif maps discrete geomorphic settings (e.g. beach, dunes, washovers) and was digitized manually with reference to source datasets. 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 (Zeigler and others 2019).

Additional Information

Raster Extension

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Raster Extension

boundingBox
minY39.433941201364604
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files
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Raster Extension

boundingBox
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files
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contentTypeimage/geotiff
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size72257302
dateUploadedThu Jun 20 12:19:29 MDT 2019
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size2122
dateUploadedThu Jun 20 12:19:29 MDT 2019
nameEF12_VegType
nativeCrsEPSG:26918
rasterTypeGeoTIFF

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