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1
Projected
GCS_NAD_1983_2011
Linear Unit: Foot_US (0.304801)
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NAD_1983_2011_StatePlane_California_VI_FIPS_0406_Ft_US
20240206
08202900
20240207
13044200
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ItemDescription
ISO 19139 Metadata Implementation Specification
Esri ArcGIS 12.8.3.29751
URBAN_HEAT_INDEX / Heat Risk
Spring 2021 San Diego Urban Development NASA DEVELOP Team
San Diego
NASA DEVELOP
Urban Heat
Heat Vulnerability
Heat Risk
Heat Exposure
Urban Planning
Climate Change
Remote Sensing
Landsat 8
ECOSTRESS
Health Indicators
Socioeconomic Indicators
Extreme Heat
Climate Adaptation
Urban Heat Island Effect
Land Surface Temperature (LST)
Daytime Temperature
Nighttime Temperature
American Community Survey
CDC 500 Cities
SanGIS
SANDAG
The Heat Risk layer in the Urban Heat Index synthesizes heat exposure and vulnerability data to assess overall heat-related risks in San Diego. This layer is crucial for identifying high-risk areas, guiding targeted interventions, and informing urban resilience strategies.
<DIV STYLE="text-align:Left;font-size:12pt"><DIV><DIV><P><SPAN>The Heat Risk layer combines data from the Heat Vulnerability and Heat Exposure layers to provide a comprehensive assessment of areas in San Diego most susceptible to the adverse effects of urban heat. By integrating socio-demographic indicators with land surface temperature data, this layer offers a nuanced view of heat risk across the city, serving as an essential tool for prioritizing public health measures and urban planning initiatives aimed at mitigating heat-related impacts.</SPAN></P><P><SPAN /></P><P><SPAN>The Heat Risk layer utilizes the "Heat_Risk" field and is symbolized using quantile breaks to categorize and visually represent different levels of heat risk throughout San Diego. This method allows for a clear distinction between areas of varying risk, aiding in the identification of regions requiring immediate attention and intervention.</SPAN></P><P /><P><SPAN>Urban Heat Index Fields:</SPAN></P><P><SPAN>- GEOID: Census block group identifier.</SPAN></P><P><SPAN>- Heat_Vulnerability: Score indicating social vulnerability to heat.</SPAN></P><P><SPAN>- Heat_Exposure: Score representing heat magnitude based on surface temperatures.</SPAN></P><P><SPAN>- Heat_Risk: Combined score of heat exposure and vulnerability.</SPAN></P><P><SPAN>- Census_Tract: The census tract number.</SPAN></P><P><SPAN /></P><P><SPAN>Geographical Coverage: City of San Diego, California</SPAN></P><P><SPAN>Temporal Coverage: 2015-2020</SPAN></P><P /><P><SPAN><SPAN>Contact:</SPAN></SPAN></P><P><SPAN>City Planning Department </SPAN></P><P><SPAN>619-235-5200</SPAN></P><P><SPAN>planning@sandiego.gov</SPAN></P><P><SPAN>202 C Street, M.S. 413</SPAN></P><P><SPAN>San Diego, CA 92101</SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
1
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32.533640
File Geodatabase Feature Class
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dataset
EPSG
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0
Simple
FALSE
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TRUE
FALSE
URBAN_HEAT_INDEX
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
GEOID
GEOID
String
11
0
0
HVI_SCORE
Heat_Vulnerability
Double
8
0
0
exp
Heat_Exposure
Double
8
0
0
HVI_NORM
Heat_Vulnerability_Normalized
Double
8
0
0
Risk_NORM
Heat_Risk
Double
8
0
0
Exp_Norm
Heat_Exposure_Normalized
Double
8
0
0
TRACT
Census_Tract
Double
8
0
0
GlobalID
GlobalID
GlobalID
38
0
0
created_user
created_user
String
255
0
0
created_date
created_date
Date
8
0
0
last_edited_user
last_edited_user
String
255
0
0
last_edited_date
last_edited_date
Date
8
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20240207
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