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Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_18N
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20210430
10142700
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10142700
Chris A Sanocki
U.S. Geological Survey, MIDCONTINENT REGION
Geographer
763-783-3151
2280 Woodale Drive
Mounds View
MN
55112
US
sanocki@usgs.gov
20191024
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.: 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: 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.: Parameter 2: Wetland Soils: U.S. Geological Survey data release, https://doi.10.5066/P9WUCQDU.
Great Lakes Coastal Wetland Restoration Assessment (GLCWRA)
This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. This dataset represents soils within the Lake Ontario Restoration Assessment (LORA) study area that support wetland habitats. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven 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 selection of wetland restoration sites. 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 wetland soils that are suitable for wetland restoration. 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
Great Lakes
Lake Ontario
New York
Common geographic areas
soil
wetland
wetland restoration
hydrology
resource management
water quality
lake
lakeshore
stream
river
Marine Realms Information Bank (MRIB) keywords
wetland ecosystems
aquatic ecosystems
freshwater ecosystems
land use and land cover
surface water (non-marine)
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
USGS Thesaurus
soil
wetland
wetland restoration
hydrology
resource management
water quality
lake
lakeshore
stream
river
wetland ecosystems
aquatic ecosystems
freshwater ecosystems
land use and land cover
surface water (non-marine)
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
Great Lakes
Lake Ontario
New York
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 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
Crossref5: 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
Crossref6: 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
Crossref7: 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
Crossref8: 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
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
-79.2019
-75.9579
44.5845
42.7053
ground condition
1977
2019
1
-79.201915
-75.957906
44.584461
42.705276
The data values were inspected and found to be within the expected range.
This dataset represents wetland soil types for the entire Lake Ontario Restoration Assessment (LORA) study area, as defined by the Coastal Change Analysis Program (C-CAP) National Wetland Inventory (NWI), and Soil Survey Geographic Database (SSURGO) datasets.
Project C-CAP data to North American Datum 1983 UTM Zone 18 and clip to study area extent. Reclassify the C-CAP raster so that the following values are changed to 1: Palustrine forested wetland, Palustrine scrub wetland, Palustrine emergent wetland, open water, and Palustrine aquatic. All other values should be reclassified to 0. Cell size is 30 meters.
2019-10-25
Project NWI data to North American Datum 1983 UTM Zone 18 and clip to study area extent. Features that are permanently flooded are set to a value of 0; all other features receive a value of 1. Convert features to a raster layer.
2019-10-25
SSURGO data is packaged by county. Clip all counties to study area. Join counties with their corresponding 'component' tables. Select all features with 'hydgrp' equal to 'D' or 'B/D' (soils with moderate to slow infiltration rates). Set selected features to a value of 1; all other features receive a value of 0. Convert vector layer to raster.
2019-10-25
Create a single raster where each pixel has a value of 0 or 1. When at least one layer (CCAP, NWI, or SSURGO) has a value of 1, the output raster also has a value of 1. All other cells receive a value of 0. Use LORA DEM as snap raster, and set cell size to 10 m.
2019-10-25
Identified the land cover of the assessment area.
C-CAP NY/PA 2011-Era Land Cover
C-CAP Land Cover
2013-05-13
National Oceanic and Atmospheric Administration (NOAA)
Department of Commerce (DOC)
Coastal Services Center (CSC)
National Ocean Service (NOS)
raster digital data
Data accessed: 10/24/2019
This classification is based on Landsat TM scenes (listed in order of mosaic)
p015r029 10/09/2011
p017r031 10/07/2011
p017r030 10/07/2011
p015r031 10/09/2011
p015r031 06/03/2011
p016r031 10/13/2010
p016r031 11/01/2011
p015r030 10/09/2011
p016r030 10/13/2010
p016r030 11/01/2011
p016r029 10/13/2010
p018r032 07/10/2011
p018r031 06/08/2011
p018r031 08/08/2010
p013r032 10/08/2010
p013r031 10/08/2010
p012r031 08/30/2010
p014r032 08/28/2010
p014r031 07/30/2011
p014r031 08/28/2010
p014r030 08/28/2010
p014r030 07/27/2010
p015r032 10/19/2009
p014r029 05/21/2009
p013r031 04/18/2011
https://coast.noaa.gov/ccapftp/#/
http://www.csc.noaa.gov/landcover
Date of Landsat scenes
2009-05-21
2011-11-01
This data set represents the extent, approximate location and type of wetlands and deepwater habitats
National Wetlands Inventory - Version 2 - Surface Waters and Wetlands Inventory
NWI
2019
U.S. Fish and Wildlife Service
vector digital data
Data accessed: 07/16/2019
https://fwsprimary.wim.usgs.gov/wetlands/apps/wetlands-mapper/
https://www.fws.gov/wetlands/Data/metadata/FWS_Wetlands.xml
ground condition
1977
2019
Identified the soil types of the assessment area
Soil Survey Geographic Database
SSURGO
2018-02-24
Natural Resources Conservation Service (NRCS)
tabular digital data
Data accessed: 07/22/2019
https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx
ground condition
2004-03-08
2018-02-24
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
3
20111
10.000000
25562
10.000000
1
1
0
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166016.736287 4937264.865387
421636.736287 4937264.865387
421636.736287 4736154.865387
293826.736287 4836709.865387
LORA_P2_Soils.tif
Raster geospatial data file.
Producer Defined
Table
2
OID
Internal object identifier.
Producer Defined
Sequential unique whole numbers that are automatically generated.
Value
The values of each raster cell are a binary representation indicating suitability for wetland habitat. Raster cells with a value of '1' represent soils with the correct type for wetland habitat, and raster cells with a value of '0' do not have the proper soil type.
Producer Defined
0
1
Count
Number of raster cells with this value.
Producer Defined
7765609.0
10988658.0
dataset
EPSG
6.13(3.0.1)
Band_1
1.000000
0.000000
8