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LORA_P6_Landuse.tif
160468.001000
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4771054.000000
4897204.000000
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Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_18N
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20210430
10162900
20210430
10162900
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 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: 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 6: Land Use: 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. The land use data were used to identify developed areas such as parks, golf courses and agricultural land within the Lake Ontario Restoration Assessment (LORA) study area because these areas are less likely to be restored. 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 includes areas with permeable surfaces that are developed and have a high societal value, such as agricultural land, parks, and golf courses. These areas are less likely to be restored. 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 ecosystems
land use and land cover
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
USGS Thesaurus
wetland restoration
wetland
hydrology
resource management
water quality
lake
lakeshore
stream
river
Marine Realms Information Bank (MRIB) keywords
wetland ecosystems
land use and land cover
USGS-EMA-LOW-MR Coastal Wetlands
hydrology
natural resource management
water quality
remediation
wetland restoration
wetland
hydrology
resource management
water quality
lake
lakeshore
stream
river
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.: 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
-79.2455
-75.9932
44.2236
43.0163
ground condition
2013-05-13
1
-79.245461
-75.993238
44.223581
43.016295
The data values were inspected and found to be within the expected range.
This dataset represents specific land use types and is continuous for the entire Lake Ontario Restoration Assessment (LORA) study area.
Project C-Cap raster to North American Datum 1983 UTM Zone 18N. Clip raster to Study area and snap to LORA DEM.
2019-10-28
Reclassify the clipped C-CAP raster values to 0 and 1. A value of 1 could identify parks, golf courses, or agriculture lands. Three classification codes were identified using National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (CCAP) 2010 data: Developed, Open Space (value/code 5), Cultivated Crops (value/code 6), and Pasture/Hay (value/code 7). These three codes were reclassified to a new raster with a value equal to 1, all other cells were given a value of 0.
2019-10-28
Identified the landuse types
C-CAP NY/PA 2011-Era Land Cover
C-CAP Land Cover
2013-05-13
Department of Commerce (DOC)
Coastal Services Center (CSC)
National Ocean Service (NOS)
National Oceanic and Atmospheric Administration (NOAA)
remote-sensing image
Data access 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
http://www.csc.noaa.gov/landcover
Date of the Landsat scenes
2009-05-21
2011-11-01
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
4205
30.000000
8623
30.000000
1
1
0
160468.001000 4771054.000000
160468.001000 4897204.000000
419158.001000 4897204.000000
419158.001000 4771054.000000
289813.001000 4834129.000000
LORA_P6_Landuse.tif
The raster geospatial data are formatted as a GeoTiff.
Producer Defined
Table
2
OID
Internal object identifier.
Producer Defined
Sequential unique whole numbers that are automatically generated.
Value
Unique numeric values contained in each raster cell. 0 is not suitable for restoration and 1 is suitable for restoration.
Producer Defined
0
1
Count
Number of raster cells with this value.
Producer Defined
456297.0
1624098.0
dataset
EPSG
6.13(3.0.1)
Band_1
1.000000
0.000000
2