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landcover_10class_2017_Cuyahoga_SP83
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2113706.928619
2277086.928619
586584.059159
717521.059159
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GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Ohio_North_FIPS_3401_Feet
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20191016
15235400
20191016
15235400
FGDC
Jarlath O'Neil-Dunne
University of Vermont Spatial Analysis Laboratory
Director
802-656-3324
802-656-8683
81 Carrigan Drive
Aiken Center Room 205
Burlington
VT
05405
US
joneildu@uvm.edu
landcover_10class_2017_cuyahoga
University of Vermont Spatial Analysis Laboratory
remote-sensing image
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>High resolution land cover dataset for Cuyahoga County, Ohio. Ten land cover classes were mapped: (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads,(7) other paved surfaces, (8) tree canopy over vegetation or soil, (9) tree canopy over building, (10) tree canopy over road/railroad, and (11) tree canopy over other paved surfaces. The primary sources used to derive this land cover layer were 2017 LiDAR data, 2017 NAIP imagery and 2017 ortho imagery. Ancillary data sources included GIS data provided by Cuyahoga County, Ohio or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:4000 and all observable errors were corrected.</SPAN></P></DIV></DIV></DIV>
This dataset was developed as part of the Cuyahoga County 2017 Tree Canopy Assessment. As such, it represents a 'top down' mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area.
University of Vermont Spatial Analysis Laboratory in collaboration with Cuyahoga County 2017 Tree Canopy Assessment.
Jarlath O'Neil-Dunne
University of Vermont Spatial Analysis Laboratory
Director
802-656-3324
802-656-8683
Aiken Room 205
81 Carrigan Drive
Burlington
VT
05405
US
joneildu@uvm.edu
Cuyahoga
Ohio
2017
tree canopy
Urban
UTC
Land cover
Tree Canopy
Urban
UTC
Land Cover
Cuyahoga
2017
Ohio
Esri ArcGIS 10.4.0.5524
0
0
0
0
ground condition
This assessment was completed by the University of Vermont's Spatial Analysis Laboratory with funding the Cuyahoga County. The methods used were developed by the University of Vermont Spatial Analysis Laboratory with funding from the Cuyahoga County Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establishing tree canopy goals.
1
-81.971714
-81.371195
41.634866
41.271272
Valid raster dataset.
Complete coverage for the study area using the most recent boundary data.
No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control (QC). Accuracy assessments from previous UTC land cover datasets indicate that the use OBIA techniques in combination with a detailed QC yield an overall accuracy of 95% or better.
Object based image analysis (OBIA) using a rule-based expert system
Manual corrections to land cover classification
Vector
Planimetric data
Planimetric data
ground condition
12000
National Agricultural Imagery Program 4-band data
NAIP
ground condition
LiDAR
LiDAR
ground condition
2
0
1.000000
0
1.000000
1
0
2113706.928619 586584.059159
2113706.928619 717521.059159
2277086.928619 717521.059159
2277086.928619 586584.059159
2195396.928619 652052.559159
landcover_10class_2017_cuyahoga_v8.tif
UTC
Table
10
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Count
# pixels per land cover class
Internal
Count
Double
8
0
0
Value
Land cover code
UTC
2
Grass/Shrub
6
Road/Railroad
5
Building
4
Water
7
Other Paved Surfaces
3
Bare Soil
1
Tree Canopy
Value
Integer
4
0
0
Class
Class
String
50
0
0
STen land cover classes were mapped: (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads,(7) other paved surfaces, (8) tree canopy over vegetation or soil, (9) tree canopy over building, (10) tree canopy over road/railroad, and (11) tree canopy over other paved surfaces.
File Geodatabase Raster Dataset
dataset
EPSG
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Layer_1
11.000000
2.000000
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20191016
Pixel
130937
163380
1.000000
1.000000
4
1
Upper Left
FALSE
LZ77
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pixel codes
FGDBR
TRUE
row and column
1.000000
1.000000