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TreeCanopy_V2_0
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287809.405845
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Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_StatePlane_Connecticut_FIPS_0600
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FGDC
ArcGIS Metadata
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TreeCanopy_V2_0
vector digital data
Onat, Y., Massidda, C., Duskin, L. (2023) [Layer Name], The Development of Connecticut Environmental Justice Screening Tool (v2.0) Dataset, University of Connecticut, Connecticut Institute for Resilience and Climate Adaptation, Retrieved from [Website link], Date Accessed: MM-DD-YYYY
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This indicator represents the decile rank of tree canopy percent estimates. The percentile and the rank were calculated. A percentile is a score indicating the value below which a given percentage of observations in a group of observations fall. It indicates the relative position of a particular value within a dataset. For example, the 20th percentile is the value below which 20% of the observations may be found. The rank refers to a process of arranging percentiles in descending order, starting from the highest percentile and ending with the lowest percentile. Once the percentiles are ranked, a normalization step is performed to rescale the rank values between 0 and 10. A rank value of 10 represents the highest percentile, while a rank value of 0 corresponds to the lowest percentile in the dataset. The normalized rank provides a relative assessment of the position of each percentile within the distribution, making it simpler to understand the relative magnitude of differences between percentiles. Normalization between 0 and 10 ensures that the rank values are standardized and uniformly distributed within the specified range. This normalization allows for easier interpretation and comparison of the rank values, as they are now on a consistent scale. For detailed methods, go to connecticut-environmental-justice.circa.uconn.edu. The MRLC Program offers geospatial data on tree canopy cover (NLCD) for the United States. It includes percent tree canopy estimates from 2011 to 2021 and will expand to include additional areas in 2023. Access the data here: [https://www.mrlc.gov/data/type/tree-canopy].</SPAN></P></DIV></DIV></DIV>
As a recommendation of the Governor's Council on Climate Change (GC3), and in partnership with and with CT Department of Energy and Environmental Protection (CT DEEP)'s Regional Greenhouse Gas Initiative funds funds, UConn CIRCA is developing the CT Environmental Justice Screening Tool. CT Environmental Justice Screening Tool is designed to help identify and analyze patterns of the disproportionate impact of pollution on vulnerable populations who are impacted by chronic health conditions and social stressors. The CT Environmental Justice Screening Tool intends to uphold a commitment to equity and environmental justice by informing the public and policymakers about the potential cumulative risks of environmental burdens, social vulnerabilities, and health vulnerabilities throughout communities in Connecticut. Learn more about the project here: connecticut-environmental-justice.circa.uconn.ed
Funding for this project is provided by the CT Department of Energy and Environmental Protection's Regional Greenhouse Gas Initiative (RGGI) funds.
Environmental Justice, ejscreen, Connecticut, Tree Canopy
Environmental JusticeejscreenConnecticutTree Canopy
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>If you acquire any data products from CIRCA, we ask that you acknowledge us in your use of the data by citing the dataset and/or publications in any documents or publications using these data. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data set freely available online in the future. Thank you.</SPAN></P></DIV></DIV></DIV>
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TreeCanopy_V2_0
Estimate percentage percentile and rank Tree Canopy
Feature Class
879
FID
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
FID
OID
4
0
0
Shape
Feature geometry.
Esri
Coordinates defining the features.
Shape
Geometry
0
0
0
GEOID20
GEOID20
String
11
0
0
2020 geographic id code
NAME20
NAME20
String
7
0
0
2020 census tract code
NAMELSAD20
NAMELSAD20
String
20
0
0
2020 name and code for census tract
TOWN_NAME
Name of Town
TOWN_NAME
String
16
0
0
councilofg
Regional Council of Governments
CouncilOfG
String
22
0
0
county
County name
County
String
10
0
0
Area_SqMil
Area measured in square miles
Area_SqMil
Double
10
9
6
Area_Sqft
Area_Sqft
Double
18
17
6
area in square feet
Area_SqM
Area_SqM
Double
17
16
6
area in square meters
CanopyPerc
CanopyPerc
Double
9
8
6
Canopy Percentage
Percentile
Percentile
Double
10
9
6
A percentile is a statistical measure that shows the relative position of a value within a data set. It represents the percentage of data points that are equal to or below that value. For example, the 70th percentile means 70% of data points are equal to or lower than that value. Percentiles help analyze data distribution and make comparisons within datasets.
Rank
The rank refers to a process of arranging percentiles in descending order, starting from the highest percentile and ending with the lowest percentile. Once the percentiles are ranked, a normalization step is performed to rescale the rank values between 0 and 10. A rank value of 10 represents the highest percentile, while a rank value of 0 corresponds to the lowest percentile in the dataset. The normalized rank provides a relative assessment of the position of each percentile within the distribution, making it simpler to understand the relative magnitude of differences between percentiles. Normalization between 0 and 10 ensures that the rank values are standardized and uniformly distributed within the specified range. This normalization allows for easier interpretation and comparison of the rank values, as they are now on a consistent scale.
Rank
Double
10
9
6
Shapefile
4.092
dataset
EPSG
4.5(3.0.1)
879
Simple
FALSE
879
FALSE
FALSE
20230814