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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014

Dates

Publication Date
Start Date
2014-01-01
End Date
2014-04-21

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.

CeI14_GeoSet.tif 2.38 MB
CeI14_GeoSet.tif.vat.dbf 556 Bytes
CeI14_SubType.tif 4.75 MB
CeI14_SubType.tif.vat.dbf 485 Bytes
CeI_SupClas_GeoSet_SubType_VegType_VegDen_browse.png
“Landcover classification, geomorphic setting, substrate type, vegetation dens...”
thumbnail 396 KB
Extension: CeI14_SupClas.zip
CeI14_SupClas.tif 2.38 MB
CeI14_SupClas.tif.vat.dbf 556 Bytes
CeI14_SupClas.tif-ColorRamp.SLD 2.07 KB
Extension: CeI14_VegDen.zip
CeI14_VegDen.tif 4.75 MB
CeI14_VegDen.tif.vat.dbf 414 Bytes
CeI14_VegDen.tif-ColorRamp.SLD 2.07 KB
Extension: CeI14_VegType.zip
CeI14_VegType.tif 4.75 MB
CeI14_VegType.tif.vat.dbf 485 Bytes
CeI14_VegType.tif-ColorRamp.SLD 2.07 KB

Purpose

These categorical raster files map 2014 substrate and vegetation characteristics in 5-m cells. The supervised classification raster (CeI14_SupClas.tif) depicts landcover attributes (for example, marsh, sand, water, herbaceous vegetation). It was created with a supervised classification of 2014 aerial imagery. Raster files CeI14_SubType.tif, CeI14_VegDen.tif, CeI14_VegType.tif were reclassified from the supervised classification raster with some manual modifications. CeI14_SubType.tif maps discrete substrate types; CeI14_VegDen.tif maps discrete categories of vegetation density; CeI14_VegType.tif maps discrete vegetation types. Raster file CeI14_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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nameCeI14_SupClas
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Raster Extension

boundingBox
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Raster Extension

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dateUploadedThu Jun 20 12:04:06 MDT 2019
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dateUploadedThu Jun 20 12:04:06 MDT 2019
nameCeI14_VegType
nativeCrsEPSG:26918
rasterTypeGeoTIFF

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