20200814
11145200
1.0
FALSE
LORA_Dikes
131.299
167389.764700
417762.610479
4778777.085383
4888825.438491
1
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_18N
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20210430
10113400
20210430
10113400
Chris A Sanocki
U.S. Geological Survey, MIDCONTINENT REGION
Geographer
763-783-3151
2280 Woodale Drive
Mounds View
MN
55112
US
sanocki@usgs.gov
20191017
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/P9X63D37
https://doi.10.5066/P9X63D37
131.299
Shapefile
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
Dunn, N.A., Hopkins, A.L., Dooley, K.M., Sanocki, C.A., 2021, Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Dikes: U.S. Geological Survey data release, https://doi.10.5066/P9X63D37.
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 data represents the location of dikes within the Lake Ontario Restoration Assessment (LORA) study area. 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.
The dike dataset was used to provide the extent and location of dikes within the study area, because they are an important factor in controlling water flow to coastal wetlands. For our purposes, a dike is any land feature with a significant slope and a great enough area to potentially divert the course of water. 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
environment
ISO 19115 Topic Category
lake
lakeshore
wetland
wetland restoration
stream
river
hydrology
water quality
resource management
Marine Realms Information Bank (MRIB) keywords
river reaches
hydrology
wetland ecosystems
natural resource management
water quality
remediation
USGS Thesaurus
Dike
Coastal and Marine Ecological Classification Standard
environment
lake
lakeshore
wetland
wetland restoration
stream
river
hydrology
water quality
resource management
river reaches
hydrology
wetland ecosystems
natural resource management
water quality
remediation
Dike
Great Lakes
Lake Ontario
New York
None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations.
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.: 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
Crossref10: 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
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
-79.1539
-76.0115
44.1480
43.0887
ground condition
2019
1
-79.153858
-76.011525
44.148003
43.088723
Not applicable.
A completeness report was not conducted. Data were compared against aerial imagery and false positives were removed.
Create a slope raster from the digital elevation modal (DEM) and extract the areas where slope is greater than 12 degrees. The resolution of the DEM is 10 square meters - see more information on this dataset under 'Source Inputs' below.
2019-08-02
Convert the extracted raster to a polygon layer.
2019-08-02
Create a 3-meter buffer around the polygon layer.
2019-08-02
Generalize polygon layer.
2019-08-02
Separate multipart polygon features into singlepart polygons.
2019-08-02
Extract the polygons larger than 500 square meters.
2019-08-02
Remove the false positives:
Compare the data with real word imagery and manually delete detections that appear to be false positives. There were 17,991 polygons identified within the study area after visual inspection. This analysis was completed with a script created by the New College of Florida. For the source code, go to the following GitHub page: https://github.com/newgaminfo/GLCWRA-Code
2019-08-02
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 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
US Geological Survey
https://doi.10.5066/P9WUCQDU
ground condition
2007-01-03
2017-04-17
17991
LORA_Dikes.shp Attribute Table
Table containing attribute information associated with the data set.
Producer Defined
Feature Class
17991
FID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
Shape
Feature geometry.
ESRI
This attribute is a description of the geometry of each feature: a polygon.
Shape_Leng
The perimeter of each polygon, measured in meters.
Producer Defined
82.8164693953
437308.171423
meters
Shape_Area
The area of each polygon, measured in square meters.
Producer Defined
500.005608906
6956169.2857
square meters
dataset
EPSG
6.13(3.0.1)
Simple
FALSE
17991
TRUE
FALSE