Land-water classification for selected sites in McFaddin NWR and J.D. Murphree WMA

Dates

Publication Date: 2018-04-03
Start Date: 2017-11-06
End Date: 2017-11-08

Citation

Jones, W.R., Hartley, S.B., Stagg, C.L., and Osland, M.J., 2018, Land-water classification for selected sites in McFaddin NWR and J.D. Murphree WMA: U.S. Geological Survey data release, https://doi.org/10.5066/F7736Q51.

Summary

Land-water data was derived from imagery acquired at 350 feet using unmanned aerial systems (UAS) for 6 separate study locations using the Ricoh GR II camera. Three sites are healthy marsh and three sites are degraded marshes. For each study site, ground control markers were established and surveyed in using Real Time Kinematic (RTK) survey equipment. The imagery collected has been processed to produce a land-water classification dataset for scientific research. The land-water data will not only quantify how much marsh is being affected, but the data will also provide a spatial aspect as to where these degrading marsh fragmentations are occurring. The land-water data will be correlated with other data such as salinity, prescribed burns, [...]

Summary

Land-water data was derived from imagery acquired at 350 feet using unmanned aerial systems (UAS) for 6 separate study locations using the Ricoh GR II camera. Three sites are healthy marsh and three sites are degraded marshes. For each study site, ground control markers were established and surveyed in using Real Time Kinematic (RTK) survey equipment. The imagery collected has been processed to produce a land-water classification dataset for scientific research. The land-water data will not only quantify how much marsh is being affected, but the data will also provide a spatial aspect as to where these degrading marsh fragmentations are occurring. The land-water data will be correlated with other data such as salinity, prescribed burns, flooding frequency and flooding duration data to better understand what events may be causing marsh deterioration. With low resolution, vegetation types do not cause any troubling issues with classification but due to the high resolution of the imagery (1.18 inches/0.03 meters) there will be inherent “noise” that causes speckling throughout the classified image. With the image resolution at such a small Ground Sample Distance (GSD), the smallest of information will be visible. These small pieces of information that we call “noise” will be introduced into our image classification and will mostly come from vegetation shadows and some water saturation. In this study, we are attempting to identify hollows which are low areas or holes in the vegetation which may suggest a degradation of adjacent marsh. For our study analysis, a hollow is defined as an area that is .25m * .25m = 0.0625m2 (69 pixels) or greater. Any cluster of cells smaller than 69 pixels will be absorbed into the surrounding vegetation type. This method will help reduce noise and maintain confidence in the hollow identification.

Contacts

Point of Contact :: William R Jones
Process Contact :: William R Jones
Originator :: William R Jones, Stephen B Hartley, Camille L Stagg, Michael J Osland
Metadata Contact :: William R Jones
Distributor :: U.S. Geological Survey - ScienceBase
SDC Data Owner :: Wetland and Aquatic Research Center
USGS Mission Area :: Ecosystems

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metadata.xml Original FGDC Metadata	View	12.66 KB	application/fgdc+xml
D1_Land_Water.zip		5.97 MB	application/zip
D2_Land_Water.zip		4.73 MB	application/zip
D3_Land_Water.zip		5.14 MB	application/zip
H1_Land_Water.zip		2.39 MB	application/zip
H2_Land_Water.zip		2.02 MB	application/zip
H3_Land_Water.zip		1.72 MB	application/zip

Related External Resources

Type: Related Primary Publication

Stagg, C.L., Osland, M.J., Moon, J.A., Hall, C.T., Feher, L.C., Jones, W.R., Couvillion, B.R., Hartley, S.B., and Vervaeke, W.C., 2019, Quantifying hydrologic controls on local- and landscape-scale indicators of coastal wetland loss: Annals of Botany, Accepted Online, https://doi.org/10.1093/aob/mcz144.	https://doi.org/10.1093/aob/mcz144

Purpose

This data was acquired to help identify hammocks and hollows in marsh vegetation that are used by wintering waterfowl. This is a coastal marsh that is affected by tide and wind driven waters that causes stress on this vital landscape. Products from this imagery will help to locate where the marsh is deteriorating and along with other datasets (elevation and salinity) hope to explain why.

Land-water classification for selected sites in McFaddin NWR and J.D. Murphree WMA

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