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August 23, 2016 AUV Survey - Dissolved Oxygen Surface

Dates

Publication Date
Time Period
2016-08-23

Citation

Tagliaferri, T.N., Welk, R.J., Starke, Adam, Bodkin, L.J., and Pistillo, Thomas, 2018, Geospatial datasets of AUV observations including bottom dissolved oxygen in Great South Bay, Long Island, New York, August 2016: U.S. Geological Survey data release, https://doi.org/10.5066/F7FX77Z2.

Summary

This data provides an estimated raster surface of dissolved oxygen values across a region covered by an August 23, 2016 AUV survey. The raster was generated by using a natural neighbors interplator within a GIS on the empirical data set. This interpolator was chosen due to the non-normal distribution observed among the data, and its ability to produce smoother approximations than alternative interpolation methods. There are three files available for download in the 'Attached Files' section below. There is a zip file which contains the interpolated dissolved oxygen surface, an xml file which contains metadata, and a layer file which can be used to import the layer's symbology.

Contacts

Originator :
Tristen N Tagliaferri
Metadata Contact :
Robert J Welk
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

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

DO_Surface_symbology_0823.lyr 13.5 KB
0823_DO_Surface.zip 154.39 KB

Purpose

These data were collected to provide support for decisions regarding coastal resource management. Hard clam restoration projects performed in Great South Bay have typically yielded unsuccessful results. It is thought that low dissolved oxygen levels in the bay could be a limiting factor in ecosystem development. Thus, a spatial survey of dissolved oxygen was necessary in this region to provide a baseline of DO availability and support the New York State Dept. of Environmental Conservation Waterbody Inventory and Priority Waterbodies List. This survey provides the spatial distribution of water quality parameters, and is meant to be used in conjunction with existing data that provides time related components.

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