FLORIDA GEOGRAPHIC DATA LIBRARY DOCUMENTATION

TITLE: Smart Location Database of Census Block Groups in the State of Florida - 2013

Geodataset Name:       EPA_SLD_JUL13
Geodataset Type:       SHAPEFILE
Geodataset Feature:    Polygon
Feature Count:         11442
GENERAL DESCRIPTION:
The Smart Location Database is a consistent nationwide geographic data resource for measuring location efficiency. It includes more than 90 attributes summarizing characteristics such as housing density, diversity of land use, neighborhood design, destination accessibility, distance to transit, employment, and demographics. Most attributes are available for every census block group in the State of Florida. A census block group is a geographical unit used by the US Census that is smaller than a census tract but larger than a census block. Each block groups is a cluster of census blocks having the same first digit of their four-digit identifying numbers within a census tract. Version 2.0 of this data was first released in July 2013. See the user guide for a full description of data sources, data currency, and known limitations: https://edg.epa.gov/data/Public/OP/SLD/SLD_userguide.pdf
DATA SOURCE(S):                    U.S. Environmental Protection Agency
SCALE OF ORIGINAL SOURCE MAPS:     NA
GEODATASET EXTENT:                 State of Florida
PUBLICATION DATE: 20130709 TIME PERIOD OF CONTENT: 2010 DOWNLOAD LINK: http://www.fgdl.org/metadataexplorer/explorer.jsp

FEATURE ATTRIBUTE TABLES:

Datafile Name: EPA_SLD_JUL13.DBF
ITEM NAME WIDTH TYPE
OBJECTID
4 OID
Shape
4 Geometry
GEOID10
12 String
SFIPS
254 String
CFIPS
254 String
TRFIPS
254 String
CSA
254 String
CSA_Name
254 String
CBSA
8 Double
CBSA_Name
254 String
CBSA_EMP
8 Double
CBSA_POP
8 Double
CBSA_WRK
8 Double
COUNTHU10
8 Double
TOTPOP10
8 Double
HH
8 Double
P_WrkAge
8 Double
AutoOwn0
8 Double
Pct_AO0
8 Double
AutoOwn1
8 Double
Pct_AO1
8 Double
AutoOwn2p
8 Double
Pct_AO2p
8 Double
Workers
8 Double
R_LOWWAGEW
8 Double
R_MEDWAGEW
8 Double
R_HiWageWk
8 Double
R_PCTLOWWA
8 Double
EMPTOT
8 Double
E5_Ret10
8 Double
E5_Off10
8 Double
E5_Ind10
8 Double
E5_Svc10
8 Double
E5_Ent10
8 Double
E8_Ret10
8 Double
E8_Off10
8 Double
E8_Ind10
8 Double
E8_Svc10
8 Double
E8_Ent10
8 Double
E8_Ed10
8 Double
E8_Hlth10
8 Double
E8_Pub10
8 Double
E_FEDT10
8 Double
E_FEDRET10
8 Double
E_FEDOFF10
8 Double
E_FEDIND10
8 Double
E_FEDSVC10
8 Double
E_FEDENT10
8 Double
E_LOWWAGEW
8 Double
E_MEDWAGEW
8 Double
E_HiWageWk
8 Double
E_PCTLOWWA
8 Double
Ac_tot
8 Double
AC_WATER
8 Double
Ac_Unpr
8 Double
Ac_Land
8 Double
D1a
8 Double
D1b
8 Double
D1c
8 Double
D1C5_Ret10
8 Double
D1c5_Off10
8 Double
D1C5_Ind10
8 Double
D1c8_Off10
8 Double
D1C5_Ent10
8 Double
D1C8_Ret10
8 Double
D1c5_Svc10
8 Double
D1C8_Ind10
8 Double
D1c8_Svc10
8 Double
D1C8_Ent10
8 Double
D1c8_Ed10
8 Double
D1C8_Hlth1
8 Double
D1c8_Pub10
8 Double
D1d
8 Double
D1_flag
2 SmallInteger
D2a_JpHH
8 Double
D2b_E5Mix
8 Double
D2B_E5MIXA
8 Double
D2b_E8Mix
8 Double
D2b_E8MixA
8 Double
D2a_EpHHm
8 Double
D2c_TrpMx1
8 Double
D2c_TrpMx2
8 Double
D2c_TripEq
8 Double
D2r_JobPop
8 Double
D2a_WrkEmp
8 Double
D2r_WrkEmp
8 Double
D2c_WrEmix
8 Double
D3a
8 Double
D3aao
8 Double
D3amm
8 Double
D3apo
8 Double
D3b
8 Double
D3bao
8 Double
D3bmm3
8 Double
D3bmm4
8 Double
D3bpo3
8 Double
D3bpo4
8 Double
D4a
8 Double
D4b025
8 Double
D4b050
8 Double
D4c
8 Double
D4d
8 Double
D5ar
8 Double
D5ae
8 Double
D5br
8 Double
D5br_Flag
4 Integer
D5be
8 Double
D5be_Flag
4 Integer
D5cr
8 Double
D5cri
8 Double
D5ce
8 Double
D5cei
8 Double
D5dr
8 Double
D5dri
8 Double
D5de
8 Double
D5dei
8 Double
DESCRIPT
15 String
FGDLAQDATE
36 Date
AUTOID
4 Integer
SHAPE.AREA
0 Double
SHAPE.LEN
0 Double

FEATURE ATTRIBUTE TABLES CODES AND VALUES:

Item
Item Description
OBJECTID Internal feature number.

Shape Feature geometry.

GEOID10 Unique 12-digit block group identification string (FIPS code)

SFIPS State 2-digit FIPS code

CFIPS County 3-digit FIPS code

TRFIPS Census tract FIPS code in which CBG resides

CSA FIPS for Combined Statistical Area in which CBG resides

CSA_Name Name of CSA in which CBG resides

CBSA FIPS for core based statistical area (CBSA) in which CBG resides

CBSA_Name Name of CBSA in which CBG resides

CBSA_EMP Total employment in CBSA

CBSA_POP Total population in CBSA

CBSA_WRK Total number of workers that live in CBSA

COUNTHU10 Housing units, 2010

TOTPOP10 Population, 2010

HH Households (occupied housing units), 2010

P_WrkAge Percent of population that is working-aged, 2010

AutoOwn0 Numer of households in CBG that own zero automobiles, 2010

Pct_AO0 Percent of households with zero automobiles, 2010.

AutoOwn1 Number of households in CBG that own one automobile, 2010.

Pct_AO1 Percentage of households with one automobile, 2010

AutoOwn2p Number of households that own 2 or more automobiles, 2010

Pct_AO2p Percentage of of households with 2 or more automobiles, 2010

Workers Number of workers in CBG (home location), 2010

R_LOWWAGEW Number of workers earning $1250/month or less (home location), 2010

R_MEDWAGEW Number of workers earning more than $1250/month but less than $3333/month (home location), 2010

R_HiWageWk Number of workers earning greater than $3333/month (home location), 2010

R_PCTLOWWA Percent of LowWageWk of total number workers in a CBG (home location), 2010

EMPTOT Total employment, 2010

E5_Ret10 Retail jobs within a 5-tier employment classification scheme (LEHD: CNS07)

E5_Off10 Office jobs within a 5-tier employment classification scheme (LEHD: CNS09 + CNS10 + CNS11 + CNS13 + CNS20)

E5_Ind10 Industrial jobs within a 5-tier employment classification scheme (LEHD: CNS01 + CNS02 + CNS03 + CNS04 + CNS05 + CNS06 + CNS08)

E5_Svc10 Service jobs within a 5-tier employment classification scheme (LEHD: CNS12 + CNS14 + CNS15 + CNS16 + CNS19)

E5_Ent10 Entertainment jobs within a 5-tier employment classification scheme (LEHD: CNS17 + CNS18)

E8_Ret10 Retail jobs within a 8-tier employment classification scheme (LEHD: CNS07)

E8_Off10 Office jobs within a 8-tier employment classification scheme (LEHD: CNS09 + CNS10 + CNS11 + CNS13)

E8_Ind10 Industrial jobs within a 8-tier employment classification scheme (LEHD: CNS01 + CNS02 + CNS03 + CNS04 + CNS05 + CNS06 + CNS08)

E8_Svc10 Service jobs within a 8-tier employment classification scheme (LEHD: CNS12 + CNS14 + CNS19)

E8_Ent10 Entertainment jobs within a 8-tier employment classification scheme (LEHD: CNS17 + CNS18)

E8_Ed10 Education jobs within a 8-tier employment classification scheme (LEHD: CNS15)

E8_Hlth10 Health care jobs within a 8-tier employment classification scheme (LEHD: CNS16)

E8_Pub10 Public administration jobs within a 8-tier employment classification scheme (LEHD: CNS20)

E_FEDT10 Federal employment (total).

E_FEDRET10 Federal retail employment

E_FEDOFF10 Federal office employment

E_FEDIND10 Federal Industrial Employment

E_FEDSVC10 Federal Service Employment

E_FEDENT10 Federal Entertainment Employment

E_LOWWAGEW Number of workers earning $1250/month or less (work location), 2010

E_MEDWAGEW Number of workers earning more than $1250/month but less than $3333/month (work location), 2010

E_HiWageWk Number of workers earning greater than $3333/month (work location), 2010

E_PCTLOWWA Percent of LowWageWk of total number workers in a CBG (work location), 2010

Ac_tot Total geometric area of the CBG (in acres)

AC_WATER Total water area in acres

Ac_Unpr Acres of land area that is not protected from development (i.e., not a park or conservation area)

Ac_Land Block group area that is land (in acres)

D1a Gross residential density (HU/acre) on unprotected land, 2010

D1b Gross population density (people/acre) on unprocted land, 2010

D1c Gross employment density (jobs/acre) on unprotected land, 2010

D1C5_Ret10 Gross retail (5-tier) employment density (jobs/acre) on unprotected land

D1c5_Off10 Gross office (5-tier) employment density (jobs/acre) on unprotected land, 2010

D1C5_Ind10 Gross industrial (5-tier) employment density (jobs/acre) on unprotected land

D1c8_Off10 Gross office (8-tier) employment density (jobs/acre) on unprotected land, 2010

D1C5_Ent10 Gross entertainment (5-tier) employment density (jobs/acre) on unprotected land

D1C8_Ret10 Gross retail (8-tier) employment density (jobs/acre) on unprotected land

D1c5_Svc10 Gross service (5-tier) employment density (jobs/acre) on unprotected land, 2010

D1C8_Ind10 Gross industrial (8-tier) employment density (jobs/acre) on unprotected land

D1c8_Svc10 Gross service (8-tier) employment density (jobs/acre) on unprotected land, 2010

D1C8_Ent10 Gross entertainment (8-tier) employment density (jobs/acre) on unprotected land

D1c8_Ed10 Gross education (8-tier) employment density (jobs/acre) on unprotected land, 2010

D1C8_Hlth1 Gross health care (8-tier) employment density (jobs/acre) on unprotected land

D1c8_Pub10 Gross public sector (8-tier) employment density (jobs/acre) on unprotected land, 2010

D1d Gross activity density (HU + employment / acre) on unprotected land, 2010

D1_flag Flag to indicate D1 density metrics use land area rather than unprotected land area in denominator.

D2a_JpHH Jobs per housing unit

D2b_E5Mix 5-tier employment entropy

D2B_E5MIXA 5-tier employment entropy (denominator set to the static 5 employment types in the CBG)

D2b_E8Mix 8-tier employment entropy

D2b_E8MixA 8-tier employment entropy, denominator set to the static 8 eployment types in the CBG

D2a_EpHHm 5-tier employment and household entropy

D2c_TrpMx1 5-tier employment and household entropy, based on vehicle trip production and trip attractions

D2c_TrpMx2 Employment and household entropy (excluding industrial jobs), based on trip production and attraction

D2c_TripEq Trip production and trip attractions equilibrium index (closer to 1 = more balance)

D2r_JobPop Deviation of CBG jobs/population ratio from regional average jobs/pop ratio

D2a_WrkEmp Household workers per job

D2r_WrkEmp Deviation of CBG ratio of household workers/job from regional average ratio of household workers/ob

D2c_WrEmix Household worker per job equilibrium index (closer to one = more balanced)

D3a Total road network density (facility-miles per square mile)

D3aao Road network density in terms of facility miles of auto-oriented links per square mile

D3amm Road network density in terms of facility miles of multi-model links per square mile

D3apo Street network density in terms of facility miles of pedestrian oriented links per square mile

D3b Weighted intersection density per square mile (auto-oriented intersections excluded)

D3bao Intersection density in terms of auto-oriented intersections per square mile

D3bmm3 Intersection density in terms of multi-model intersections having three legs per square mile

D3bmm4 Intersection density in terms of multi-model intersections having four or more legs per square mile

D3bpo3 Intersection density in terms of pedestrian-oriented intersections having three legs per square mile

D3bpo4 Intersection density in terms of pedestrian-oriented intersections having four or more legs per square mile

D4a Distance from population weighted centroid to nearest transit stop, meters

D4b025 Proportion of CBG employment within 1/4 mile of fixed guideway transit stop

D4b050 Proportion of CBG employment within 1/2 mile of fixed guideway transit stop

D4c Aggregate frequency of transit service within 0.25 miles of block group boundary per hour during evening peak period

D4d Peak pm transit departure within 0.25 miles of CBG, per square mile

D5ar Jobs within a 45 minute drive (weighted)

D5ae Working-age population within 45 min. drive (weighted)

D5br Jobs within 45 min. transit commute (weighted)

D5br_Flag Transit accessibility score reflects reverse accessibility to account for direction transit service.

D5be Working-age population within 45 min. transit commute (weighted)

D5be_Flag Transit accessibility score reflects reverse accessibility to account for direction transit service

D5cr Job accessibility (D5ar) as proportion of total regional job accessibility

D5cri Regional centrality index (auto) - D5cr divided by max D5cr in metro region (CBSA)

D5ce Accessibility to working-age populatin (D5ae) as proportion of total regional accessibility

D5cei Regional centrality index (auto) - D5ce divided by max D5ce in metro region (CBSA)

D5dr Job accessibility by transit (D5br) as proportion of total regional job accessibility by transit

D5dri Regional centrality index (transit) - D5dr divided by max D5dr in metro region (CBSA)

D5de Accessibility to working-age populatin by transit (D5be) as proportion of total regional accessibility

D5dei Regional centrality index (transit) - D5de divided by max D5de in metro region (CBSA)

DESCRIPT Based on field GEOID10.

FGDLAQDATE The date FGDL acquired the data from the Source.

AUTOID Unique ID added by GeoPlan

SHAPE.AREA Area in meters

SHAPE.LEN Perimeter in meters

Attribute descriptions and data sources available in the SLD Guidebook.
https://edg.epa.gov/data/Public/OP/SLD/SLD_UserGuide.pdf
USER NOTES:
Attribute value ranges were tested for validity. 
See report for full discussion of corrective measures taken.
See report for full discussion of data completeness.
GeoPlan relied on the integrity of the attribute information within
the original data.
http://www.epa.gov/smartgrowth/smartlocationdatabase.htm

Sample Variables Included in the Smart Location Database
For full descriptions of the variables, see the Smart Location Database User Guide (PDF) 
(35 pp, 1.22MB, About PDF).

Category

Density	
Gross residential density (housing units per acre) on unprotected land
Gross population density (people per acre) on unprotected acre
Gross employment density (jobs per acre) on unprotected acre

Diversity of land use	
Jobs per housing unit
Employment entropy (a measure of employment diversity)
Employment and housing entropy

Urban design	
Street intersections per square mile
High-speed road network density

Transit service	
Aggregate transit service frequency, afternoon peak period
Transit service density, afternoon peak period
Distance to nearest transit stop

Destination accessibility by transit	
Jobs within a 45-minute transit commute
Working-age population within a 45-minute transit commute

Destination accessibility by car	
Jobs within a 45-minute drive
Working-age population within a 45-minute drive

Demographics	
Percentage of households with no car, 1 car, or 2 or more cars
Percentage of workers that are low, medium, or high wage (by home and work locations)

Employment	
Employment totals broken down by 5-tier classification scheme
Employment totals broken down by 8-tier classification scheme

------------------------------------

Uses of the Smart Location Database

Accessing and comparing neighborhood conditions
Users can browse a simple interactive map Link to EPA's External Link Disclaimer 
to assess and compare conditions across different neighborhoods in their 
communities.

Developing indicators of location efficiency
EPA is using the Smart Location Database to develop simple indicators of location 
efficiency. For instance, EPA is working with the U.S. General Services 
Administration to develop a Smart Location Index that scores census block groups 
based on their built environment and accessibility characteristics. Block groups 
that are associated with reduced vehicle miles traveled receive higher scores 
compared to other block groups within the same metropolitan region. Advanced 
users could create similar composite indicators to compare walk ability, compact 
design, or other built environment characteristics. EPA hopes to include additional 
indicators of location efficiency in forthcoming updates to the Smart Location 
Database.

Scenario planning and travel demand modeling
Planners can use the Smart Location Database as baseline data in scenario 
planning, sketch planning, and travel demand studies when more detailed or 
consistent local data are unavailable. Analysts can also use elasticities found in 
the research literature6 to adjust outputs of travel or activity models that are 
otherwise insensitive to variation in the built environment.

Conducting nationwide research studies and developing tools
Building on previous research, EPA is conducting a nationwide modeling study to 
predict employee commute travel (e.g., average trip distances, mode share, 
vehicle miles traveled, etc.) based on workplace neighborhood characteristics. If 
successful, this study will produce equations for refining travel demand models. 
This study and others like it also make it possible to create simple online tools to 
help more communities analyze the potential outcomes of proposed land use 
development.

Comparing urban form among metropolitan regions
Researchers can use the Smart Location Database in nationwide studies that 
compare metropolitan regions based on urban form characteristics. For instance, 
analysts could determine the percentage of residents that live in walkable or 
transit-rich neighborhoods. EPA s 2012 study Residential Construction Trends in 
America s Metropolitan Regions used the Smart Location Database in conjunction 
with data from the National Land Cover Database and the American Community 
Survey to measure and compare infill housing development.

Modeling impervious surface growth
EPA analyzed variables in a previous version of the Smart Location Database and
the National Land Cover Database to create a model and simple spreadsheet tool 
for estimating new impervious surface growth associated with land use 
development scenarios. This model is sensitive not only to density of development 
but also to its relative centrality within the surrounding metropolitan region. For 
details, see EPA s Impervious Surface Growth Model.

For questions about the Smart Location Database and associated projects, please 
contact Kevin Ramsey (202-566-1153, ramsey.kevin@epa.gov).

The Smart Location Database (SLD) enables the consistent comparison of 
different locations across the U.S. in terms of their land use characteristics, 
infrastructure, and accessibility to nearby destinations. SLD attributes were 
selected for their utility in travel demand modeling studies. However they may also 
be relevant to land use scenario planning, community development, and public 
health studies   particularly when obtaining local data is not possible or practical. 
Planned updates to the SLD will summarize these environment and accessibility 
characteristics in the form of a Smart Location Index that represents a block 
group s relative location efficiency when compared to other block groups within 
the same metropolitan region.

Data were collected using methods that have unknown accuracy 
(EPA National Geospatial Data Policy [NGDP] Accuracy Tier 10). 
For more information, please see EPA's NGDP at http://epa.gov/geospatial/policies.html

This data is provided 'as is' and its vertical positional accuracy
has not been verified by GeoPlan

None. 
Please check sources, scale, accuracy, currentness and other available information. 
Please confirm that you are using the most recent copy of both data and metadata.  
Acknowledgement of the EPA would be appreciated.

The Florida Geographic Data Library is a collection of Geospatial Data
compiled by the University of Florida GeoPlan Center with support from
the Florida Department of Transportation. GIS data available in FGDL is
collected from various state, federal, and other agencies (data sources)
who are data stewards, producers, or publishers. The data available in
FGDL may not be the most current version of the data offered by the
data source. University of Florida GeoPlan Center makes no guarantees
about the currentness of the data and suggests that data users check
with the data source to see if more recent versions of the data exist.

Furthermore, the GIS data available in the FGDL are provided 'as is'.
The University of Florida GeoPlan Center makes no warranties, guaranties
or representations as to the truth, accuracy or completeness of the data
provided by the data sources. The University of Florida GeoPlan Center
makes no representations or warranties about the quality or suitability
of the materials, either expressly or implied, including but not limited
to any implied warranties of merchantability, fitness for a particular
purpose, or non-infringement. The University of Florida GeoPlan Center
shall not be liable for any damages suffered as a result of using,
modifying, contributing or distributing the materials.

A note about data scale: 

Scale is an important factor in data usage.  Certain scale datasets
are not suitable for some project, analysis, or modeling purposes.
Please be sure you are using the best available data. 

1:24000 scale datasets are recommended for projects that are at the
county level.
1:24000 data should NOT be used for high accuracy base mapping such
as property parcel boundaries.
1:100000 scale datasets are recommended for projects that are at the
multi-county or regional level.
1:125000 scale datasets are recommended for projects that are at the
regional or state level or larger.

Vector datasets with no defined scale or accuracy should be
considered suspect. Make sure you are familiar with your data
before using it for projects or analysis. Every effort has been
made to supply the user with data documentation. For additional
information, see the References section and the Data Source Contact
section of this documentation. For more information regarding
scale and accuracy, see our webpage at:
http://geoplan.ufl.edu/education.html

REFERENCES:
Smart Location Database
http://www.epa.gov/dced/smartlocationdatabase.htm

SLD Version 2.0 User Guide
https://edg.epa.gov/data/Public/OP/SLD/SLD_UserGuide.pdf

DATA LINEAGE SUMMARY:
See report for full description of processing steps.

Smart Location Database 
Version 2.0 User Guide
https://edg.epa.gov/data/Public/OP/SLD/SLD_UserGuide.pdf
Process Date: July 2013

The GeoPlan Center downloaded the Smart Location Database from the following US EPA Website on November 21st, 2013. http://www.epa.gov/dced/smartlocationdatabase.htm Download data for the entire nation: Shapefile (ZIP) (800 MB) https://edg.epa.gov/data/Public/OP/SLD/SLD_shapefile.zip The nationwide file was originally named: SmartLocationDb.shp and it was in the following projection: GCS_WGS_1984 GeoPlan ran a select by attribute on the field SFIPS = '12' Next GeoPlan Reprojected the selected data to the FGDL Albers NAD 83 Harn projection. Next GeoPlan renamed the dataset to EPA_SLD_JUL13.shp Next GeoPlan Added and populated the following fields. DESCRIPT FGDLAQDATE Finally GeoPlan updated the metadata. Online Metadata can be viewed at the following website: https://edg.epa.gov/metadata/rest/document?id={BCE98875-BED3-4911-8BEA-32220B3E15E7}&xsl=metadata_to_html_full Process Date: 20131121
MAP PROJECTION PARAMETERS:

Projection                          ALBERS
Datum                               HPGN
Units                               METERS
Spheroid                            GRS1980
1st Standard Parallel               24  0  0.000
2nd Standard Parallel               31 30  0.000
Central Meridian                   -84 00  0.000
Latitude of Projection's Origin     24  0  0.000
False Easting (meters)              400000.00000
False Northing (meters)             0.00000

DATA SOURCE CONTACT (S):

Name:
Abbr. Name:
Address:


Phone:

Web site:
E-mail:
Contact Person:
         Phone:
        E-mail:
U.S. Environmental Protection Agency, Office of Policy, Office of Sustainable Communities
USEPA
1200 Pennsylvania Avenue, NW (MC 1807T)
Washington, DC
20460
(202) 566-1153

https://edg.epa.gov/data/Public/OP/SLD/SmartLocationDb.zip ramsey.kevin@epa.gov Kevin Ramsey

FGDL CONTACT:
Name:                   FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name:             FGDL
Address:                Florida Geographic Data Library
                        431 Architecture Building
                        PO Box 115706
                        Gainesville, FL  32611-5706
Web site:               http://www.fgdl.org

Contact FGDL: 

      Technical Support:	        http://www.fgdl.org/fgdlfeed.html
      FGDL Frequently Asked Questions:  http://www.fgdl.org/fgdlfaq.html
      FGDL Mailing Lists:		http://www.fgdl.org/fgdl-l.html
      For FGDL Software:                http://www.fgdl.org/software.html