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Chris A Sanocki
U.S. Geological Survey, MIDCONTINENT REGION
Geographer
763-783-3151
2280 Woodale Drive
Mounds View
MN
55112
US
sanocki@usgs.gov
20200114
ArcGIS Metadata
1.0
GS ScienceBase
U.S. Geological Survey
1-888-275-8747
Denver Federal Center, Building 810, Mail Stop 302
Denver
CO
80225
US
sciencebase@usgs.gov
None
Digital Data
https://doi.10.5066/P9WUCQDU
https://doi.10.5066/P9WUCQDU
Raster Dataset
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Index Composite
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data: GeoTiff
Hopkins, A.L., Dunn, N.A., Dooley, K.M., Sanocki, C.A., 2021, Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Index Composite: U.S. Geological Survey data release, https://doi.10.5066/P9WUCQDU.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA)
This dataset is the final result of the data model from the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Lake Ontario Restoration Assessment (LORA). The GLCWRA initiative identifies coastal wetland areas that have the greatest potential for habitat restoration. The data model uses the following seven primary parameters to identify and rank wetland restoration areas resulting in a composite index raster that can be used by ecological managers and planners to assist with the identification and selection of wetland restoration initiatives. The parameters are Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model which results in a composite restoration index of ranked restoration areas.
This dataset represents the wetland restoration Index Composite for the GLCWRA Lake Ontario Restoration Assessment study area. This dataset was created with methodology outlined at https://glcwra.wim.usgs.gov/.
Chris A Sanocki
U.S. Geological Survey, MIDCONTINENT REGION
Geographer
763-783-3151
2280 Woodale Drive
Mounds View
MN
55112
US
sanocki@usgs.gov
New York
Lake Ontario
Great Lakes
Common geographic areas
wetland
wetland restoration
hydrology
resource management
water quality
lake
lakeshore
stream
river
Marine Realms Information Bank (MRIB) keywords
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
wetland ecosystems
USGS Thesaurus
wetland
wetland restoration
hydrology
resource management
water quality
lake
lakeshore
stream
river
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
wetland ecosystems
New York
Lake Ontario
Great Lakes
None. Users should be aware of source data limitations and understand data processing procedures.
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
None. Please see 'Distribution Info' for details.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA)
2021
U.S. Geological Survey
U.S. Geological Survey
Reston, VA
GIS
withheld
Crossref1: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Digital Elevation Model
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref2: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 0: Mask
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref3: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 1: Hydroperiod
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref4: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 2: Wetland Soils
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref5: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 3: Flowlines
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref6: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 4: Conservation and Recreation Lands
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref7: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 5: Impervious Surfaces
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref8: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 6: Land Use
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
Crossref9: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Study Area
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
vector digital data
https://doi.10.5066/P9WUCQDU
Crossref10: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Dikes
2021
Dunn, Nicole A.
Hopkins, Anders L.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
vector digital data
https://doi.10.5066/P9X63D37
Crossref11: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Degree Flowlines
2021
Dooley, Kathy M.
Hopkins, Anders L.
Dunn, Nicole A.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
vector digital data
https://doi.10.5066/P97R96IS
Crossref12: Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Culverts
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
vector digital data
https://doi.10.5066/P9WUCQDU
true
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44.1514
43.0878
ground condition
2019
1
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44.151431
43.087839
The data values were inspected and found to be within the expected range.
The dataset covers the shoreline on the southern shore of Lake Ontario in the state of New York.
The Index Composite is the result of combining the source parameters (Parameters 0 - 6: Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use) through an ecological model. This ecological model weights each of the parameters individually and runs them through an equation to create the composite index. Parameters 1-4 contribute to the index, while 5 and 6 detract from it. Any areas covered by Parameter 0 are excluded from the Index Composite.
The Index Composite was created by staff at the USGS Upper Midwest Water Science Center in the following manner: The seven parameters (P0 - P6) were combined through a Python script to produce the raw Index Composite. This script treats each parameter like a variable in an equation, and by performing the equation the Index Composite in the form of a new raster is calculated. The raw Index Composite was then generalized to reduce the number of isolated pixels. The footprint of the raw Index Composite was run through the Boundary Clean tool. Then the resulting Footprint Boundary Clip raster was used to clip the raw Index Composite to produce the final Index Composite.
To better understand the ecological model and the see the source code, refer to New College of Florida's GitHub: https://github.com/newgaminfo/GLCWRA-Code
2020-08-01
Identified the elevation of the terrain
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Digital Elevation Model
DEM
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
2007-01-03
2017-04-17
Identified the assessment study area
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Study Area
Study Area
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
vector digital data
https://doi.10.5066/P9WUCQDU
ground condition
2019
Identified permanently flooded areas
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 0: Mask
P0: Mask
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
2020
Identified the likelihood of inundation
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 1: Hydroperiod
P1: Hydroperiod
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
1992-05-01
2019-12-31
Identified the soil types
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 2: Wetland Soils
P2: Wetland Soils
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
1977
2019
Identified areas adjacent to waterways
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Parameter 3: Flowlines
P3: Flowlines
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
1988
2012
Identified areas around and within conservation and recreation areas
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 4: Conservation and Recreation Lands
P4: Conservation and Recreation Lands
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
2005
2018
Identified the likelihood that the surface is impervious
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 5: Impervious Surface
P5: Impervious Surface
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
2001
2016
Identified land use of the area
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S. Parameter 6: Land Use (Developed Open Space, Cultivated Crops, and Pasture/Hay)
P6: Land Use
2021
Hopkins, Anders L.
Dunn, Nicole A.
Dooley, Kathy M.
Sanocki, Chris A.
U.S. Geological Survey
Reston, VA
raster digital data
https://doi.10.5066/P9WUCQDU
ground condition
2009-05-21
2011-11-01
3
11046
10.000000
25176
10.000000
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291886.736287 4833976.259922
LORA_Index_Composite.tif
The raster geospatial data are formatted as a GeoTiff.
Producer Defined
Value
The raster cell values are a range of index composite values with higher values indicating a greater restorability potential.
Producer Defined
-32.0
94.0
dataset
EPSG
6.13(3.0.1)
Band_1
94.000000
-32.000000
8