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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Myrtle Island, VA, 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–Sixteen sites on the U.S. Atlantic Coast, 2013–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P9V7F6UX.

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.

Myr14_GeoSet.tif 2.5 MB
Myr14_GeoSet.tif.vat.dbf 556 Bytes
Myr14_SubType.tif 2.5 MB
Myr14_SubType.tif.vat.dbf 343 Bytes
SupClas_rock_browse.png
“Examples of substrate type, vegetation type, and vegetation density raster la...”
thumbnail 476.07 KB
Extension: Myr14_SupClas.zip
Myr14_SupClas.tif 2.5 MB
Myr14_SupClas.tif.vat.dbf 414 Bytes
Myr14_SupClas.tif-ColorRamp.SLD 2.07 KB
Extension: Myr14_VegDen.zip
Myr14_VegDen.tif 2.5 MB
Myr14_VegDen.tif.vat.dbf 414 Bytes
Myr14_VegDen.tif-ColorRamp.SLD 2.07 KB
Extension: Myr14_VegType.zip
Myr14_VegType.tif 2.5 MB
Myr14_VegType.tif.vat.dbf 414 Bytes
Myr14_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 (Myr14_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 Myr14_SubType.tif, Myr14_VegDen.tif, Myr14_VegType.tif were reclassified from the supervised classification raster with some manual modifications. Myr14_SubType.tif maps discrete substrate types; Myr14_VegDen.tif maps discrete categories of vegetation density; Myr14_VegType.tif maps discrete vegetation types. Raster file Myr14_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

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minY37.15995888798925
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Raster Extension

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dateUploadedMon Oct 21 12:28:41 MDT 2019
nameMyr14_VegType
nativeCrsEPSG:26918
rasterTypeGeoTIFF

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