This data document will provide further explanation and context for REVISION variables and data depictions on the Map, Trends, Area Report, and Property Report.

Looking for direct access to over 300 sources of data for Southern California? Visit the UCLA Lewis Center’s Southern California Regional Data Portal.

Citations

To cite U.S. Census Bureau data we suggest the following format:

State REVISION as researching organization
(Date)
[brief explanation of data type and form]
Project Name
Retrieval Information

Race and Ethnicity Chart. (2015). [Graph illustration of REVISION]. American Community Survey 2010-2014 Data Access from the U.S. Census Bureau. Retrieved from http://revision.lewis.ucla.edu.

Geographies

This web application uses the following geographies within its maps, charts and analyses:

Region

The Southern California Association of Governments (SCAG) region comprises of the following six counties: Los Angeles, Riverside, San Bernardino, Imperial, Ventura, and Orange County.

Census Block Group

A Census block group (BG) is a clustered block areas that contain between 600-3,000 people. Block groups can increase or decrease in size with population changes during each decennial census. The block group data sets currently comprise of 2000 and 2010 Census Geographies.

Census Tract

A census tract (CT) is a are areas that contain between 1,200-8,000 people. This geography is larger than a block group. And census tracts can increase or decrease in size with population changes during each decennial census. The CT data sets currently comprise of 2000 and 2010 Census Geographies.

Transportation Analysis Zone (TAZ) Tier 1 and 2

TAZs are groups of census blocks that have at least one major thoroughfare within it’s boundary, population, housing and employment data for transportation modeling. Tier 1 closely resembles census tracts. And Tier 2 closely resembles block groups.

NEIGHBORHOOD DEMOGRAPHICS - American Community Survey 5-Year

The American Community Survey 5-year data set contains the follow variables in block group, census tract, and county levels for the years 2005-2009, 2006-2010, 2007-2011, 2008-2012, 2009-2013, 2010-2014, and 2011-2015. This web application uses 19 variables in the Map, Trends and Area Report tools. See tables below for variable, Trend, Map, and Area Report context for additional information.

Dataset	Geography		Year	Tools			Update Date
Dataset	Block Group	Tract	Year	Area Report	Trends	Map Area	Update Date
ACS	X		2005 - 2009		X		12/18/2015
ACS	X		2006 - 2010		X		12/18/2015
ACS	X		2007 - 2011		X		12/18/2015
ACS	X		2008 - 2012		X		12/18/2015
ACS	X	X	2009 - 2013	X	X	X	12/18/2015
ACS	X	X	2010 - 2014	X	X		12/18/2015
ACS	X	X	2011 - 2015	X	X		12/16/2016

Code	Name	Geography			Tools
Code	Name	Block Group	Tract	County	Trends	Area Report
B01001	Age	X		X	X	X
B01003	Total Population	X		X	X
B03002	H/L Race	X		X	X	X
B07001	Geographical Mobility In The Past Year By Age For Current Residence In The U.S.		X	X		X
B07011	Median Income In The Past 12 Months By Geographical Mobility In The Past Year For Current Residence In The United States		X	X		X
B08101	Means of transportation to work by age		X	X		X
B08135	Aggregate Travel Time To Work (In Minutes) Of Workers By Travel Time To Work	X		X	X	X
B08301	Means of Transportation to Work	X		X	X	X
B08303	Travel Time To Work	X		X	X	X
B15002	Educational Attainment	X		X	X	X
B17001	Poverty Status In The Past 12 Months By Sex By Age		X	X		X
B17021	Poverty Status Of Individuals In The Past 12 Months By Living Arrangement	X		X	X	X
B19001	Household Income	X		X	X	X
B19081	Mean Household Income Of Quintiles		X	X		X
B19082	Shares of Aggregate Household Income by Quintile		X	X		X
B23001	Sex By Age By Employment Status For The Population 16 Years And Over		X	X		X
B23025	Employment Status For The Population 16 Years And Over	X		X	X
B25002	Occupancy Status	X		X	X	X
B25008	Total Population in Occupied Housing Units by Tenure	X		X	X	X
B25014	Tenure By Occupants Per Room	X		X	X	X
B25044	Tenure by Vehicles Available	X		X	X	X

Share Of Population By Age (B01001)

The age variable indicates age structure of the neighborhood—prevalence of young children, families, seniors, or millennials. The estimates and margins of error of this variable were combined to the following groups: Total, 0-17, 18-24, 25-39, 40-64, 65-79, and 80+. [Data Definition]

Total Population (B01003)

This single variable indicates the overall population in each block group.

Share of Population by Race and Ethnicity - Hispanic/Latino Race and Ethnicity (B03002)

The race and ethnicity variables were kept in their original form with: Total, White, African American, American Indian and Alaskan Native, Asian, Native Hawaiian and Other Pacific Islander, Some other Race, Two or More Races and Hispanic or Latino. [Data Definition]

The designation of race/ethnicity may provide insight into neighborhoods that have already gentrified (gentrifiers are typically associated with white households). This variable can be viewed from a variety of perspectives. It may provide indicate the "ethnic identity" of a neighborhood, or a “tightly-knit ethnic enclave,” which suggests low mobility rates and an obstacle to entrance by gentrifiers (Beauregard 1986; Helms 2003).

(-) Primarily white neighborhoods signify little “ethnic identity” and tend to be associated with already gentrified neighborhoods.
(+) A Hispanic presence in the neighborhood may signify “ethnic identity” that provides a cultural attraction to some in-movers.

Geographic Mobility In The Past Year By Age For Current Residence In The United States (B07001)

The geographic mobility for persons in relation to their time spent in residence. [Data Definition]

Median Income In The Past Year By Age For Current Residence In The United States (B07011)

Median Income bracketed by age groups. [Data Definition]

Means Of Transportation To Work By Age (B08101)

This variable provides insight into the proportion of each mode of transit by age group. [Data Definition]

A comparison between the Block Group and the County can indicate whether neighborhoods follow larger County trends, this is especially useful information around transit rich areas.

Average Travel Time to Work (B08135, B08303)

Average time to travel to work by block group is derived by dividing Aggregate Travel Time to Work (In Minutes) Of Workers By Travel Time To Work by Travel Time To Work.

Aggregate Travel Time to Work (In Minutes) Of Workers By Travel Time To Work (B08135)

Aggregate Travel Time to Work in Minutes of surveyed population. [Data Definition]

Travel Time To Work (B08303)

Aggregate of populations per travel time ranges. [Data Definition]

Means of Transportation To Work (B08301)

This variable indicated the various modes of transportation to work for the population. [Data Definition]

Highest Educational Attainment (B15002)

This variable indicates the highest educational attainment in the block group by: Total, Little To No School, High School, Graduate/GED, Some College, College, and Graduate School/Profession Degree. [Data Definition]

The variable is used as a fundamental measure for the potential for gentrification susceptibility and can proxy for income.

(-) As the percentage of those that have obtained a Bachelor Degree increase the potential for the area to gentrify decreases (and in fact may already be experiencing gentrification).

Poverty Status In The Past 12 Months By Sex By Age (B17001)

This variable indicates the population in poverty by age. [Data Definition]

Percent Population Below Poverty Level

This variable indicates the level of poverty in an area.
(+) As the percentage increases the potential for gentrification increases.

Poverty Status Of Individuals in The Past 12 Months by Living Arrangement (B17021)

This variable indicates the population in poverty by living arrangement. [Data Definition]

Household Income Distribution (B19001)

This variables indicates the household income distribution. [Data Definition]

This variable proxies for the socioeconomic status and low rents; it can be directed toward an indicator of wealth or poverty (Heidkamp and Lucas 2006).
(-) As the percentage of the Household Income increases, the neighborhood tends to be leaning toward upper incomes and becomes less susceptible to gentrification (the area may be already experienced gentrification to some degree).

Mean Household Income Of Quintiles (B19081)

This is the mean household income in quintiles. [Data Definition]

Mean Household Income of Quintiles

o Mean Household Income Quintiles create groups of lowest, second, third, fourth, and highest fifth percent of incomes within a Block Group.

o A comparison between the Block Group and County can provide insight into the wealth distribution of the neighborhood.

Share of Aggregate Household Income Of Quintiles (B19082)

This is the share aggregate household incomes in quintiles. [Data Definition]

Quintile Share of Aggregate Income

o While the Mean Household Income of Quintiles provides the Income Values/Ranges for each Quintile, the Quintile Share of Aggregate Income indicates the proportion of the population within each Quintile.

Sex By Age By Employment Status For The Population 16 Years And Over (B23001)

This variable indicated the employment status of populations in employed, unemployed, and not in labor force. [Data Definition]

Employment Status For The Population 16 Years And Over (B23025)

This variable indicated the employment status of populations in employed, unemployed, and not in labor force. [Data Definition]

Occupancy Status (B25002)

Proportion of Renter Occupied vs. Owner Occupied. [Data Definition]

The owner to renter rate of turnover may indicate social change, however mobility and the motivation behind the turnover can often be unclear. (Freeman and Braconi 2004).
(+) As the percentage increases so does the susceptibility to gentrification.

Total Population In Occupied Housing Units By Tenure (B25008)

Population Density in Relation to Existing Occupied Housing Units for Block Group. [Data Definition]

This variable indicates the density of available housing within a Block Group, (Total Population/Housing Units)

Tenure By Occupants Per Room (B25014)

Number of Occupants per Room. [Data Definition]

This variable indicates the housing density within a Block Group.
Higher income neighborhoods (Block Groups) tend to have lower numbers of occupants per room (lower density) than lower-income neighborhoods.

Tenure By Vehicles Available (B25044)

Number of Vehicles per Household by Tenure. [Data Definition]

This variable indicates the number of vehicles per household broken down by Owner vs. Renter households.
A comparison between Block Group and the County can provide useful insight into differences between renter and owner household preferences, particularly in relation to changing neighborhoods around transit lines or transit oriented districts.

Data Manipulation

Some of the variables above were manipulated by combining estimates and margins of error, or determining statistical significance.

Combining Estimates and Margins of Error

The following variables were manipulated to create new groups: Age, Education Attainment, Travel Time to Work, and Aggregate Travel Time To Work (In Minutes) Of Workers By Travel Time To Work using the ACS Census to combine estimates and margins or error.

The estimates and margins of error of Ages were combined to the following groups: Total, 0-17, 18-24, 25-39, 40-64, 65-79, and 80+. Educational Attainment variables were combined to the following groups: Total, Little to no school, High School Graduate/ GED, Some College, College, and Graduate School/ Professional Degree. And Aggregate Travel Time was derived by dividing Aggregate Travel Time To Work (In Minutes) Of Workers By Travel Time To Work and Travel Time to Work.

According to Appendix H of the ACS Researcher Manual, you must add estimates when combining. When combining margins of error you must add squared estimates and get the square root to derive the new margin of error. An ACS example is provided below.

Herfindahl-Hirschman Diversity Index

We calculate the HHI Diversity Index using the following formula:

H = Index

i = ethnicities

Si = ethnicities share

N = number of ethnicities in population

We need to derive an index between 0 - 1 using the formula above and the B03002 (Race and Ethnicity) variables.

This diversity index is utilized in various fields to measure the degree of concentration of human or biological populations, as well as organizations.

0 indicates most diverse in terms of racial composition, and 1 is the least diverse.
As with the Share of Population by Race variable, the diversity index can ring insight into neighborhood change.
Primarily white neighborhoods signify little “ethnic identity” and tend to be associated with already gentrified neighborhoods.
(+) A Hispanic presence in the neighborhood may signify “ethnic identity” that provides a cultural attraction to some in-mover

Trends

The Performance Monitoring tool depicts comparisons of key variables. Each variable was selected to provide the user with the opportunity to analyze change over time. See specific guidance on how to use the Trends Tool to monitor neighborhood change associated with gentrification.

We compared the 5-year ACS data sets to determine the statistical significance and understand the changes the variables above have undergone from 2005 - 2013 in terms of proportions. This change can be seen in our Trends Tool that conducts two- ACS 5 year data comparisons to show the statistically significant positive and negative change amongst the year's presented at 90%, 95%, and 99% two-tailed confidence interval levels. You can see the formula used to determine statistical significance amongst overlapping periods below. For additional information, please visit Appendix H of the ACS Research User Guide.

One-year Selection

This analysis derives the proportion of the block group population to map the existing population per variable for each American Community Survey level.

Significance Test for Comparing Overlapping Periods

Est1 is P hat for more recent year (see step 2 for p-hat)

Est2 is P hat for prior year (see step 2 for p-hat)

SE1 is for most recent year (see step 3 for SE calculation)

SE2 is for prior year (see step 3 for SE calculation)

LIVABILITY METRICS & DATA

Bicycle Count Data Clearinghouse

Last Update: Continuous automatic updates
The Bike Count Data Clearinghouse is a one-stop repository for bicycle count data throughout LA County and beyond. This tool allows users to easily view, query, and download bicycle count volumes. Bicycle count data collected in Los Angeles County prior to December 2012 is already loaded into the clearinghouse. Going forward, local agencies throughout the Southern California Association of Governments (SCAG) region and beyond can upload their count data to the clearinghouse website.

Employment Status

Last Update: 2/12/2016

This layer uses ACS 2009 - 2013 Sex By Age By Employment Status For The Population 16 Years And Over (B23001) variables: Employed, Unemployed, and In Labor Force.

Employment Sector

Last Update: 2/17/2016

The dot density map depicts the Longitudinal Employer- Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES) data on All Jobs under Work Area Characteristic (WAC). This data is available for the 2013 period at the 2010 census block level. We grouped the 20 available subsectors into three sectors: Service, Working and Creative. We have provided the breakdown below.

Variable	Explanation	New Sector
CNS01	# of jobs in NAICS sector 11 (Agriculture, Forestry, Fishing & Hunting)	Working
CNS02	# of jobs in NAICS sector 21 (Mining, Quarrying, & Oil & Gas Extraction)	Working
CNS03	# of jobs in NAICS sector 22 (Utilities)	Working
CNS04	# of jobs in NAICS sector 23 (Construction)	Working
CNS05	# of jobs in NAICS sector 31-33 (Manufacturing)	Working
CNS06	# of jobs in NAICS sector 42 (Wholesale Trade)	Working
CNS07	# of jobs in NAICS sector 44-45 (Retail Trade)	Service
CNS08	# of jobs in NAICS sector 48-49 (Transportation & Warehousing)	Working
CNS09	# of jobs in NAICS sector 51 (Information)	Creative
CNS10	# of jobs in NAICS sector 52 (Finance & Insurance)	Creative
CNS11	# of jobs in NAICS sector 53 (Real Estate & Rental & Leasing)	Creative
CNS12	# of jobs in NAICS sector 54 (Professional, Scientific, & Technical Services)	Creative
CNS13	# of jobs in NAICS sector 55 (Management of Companies & Enterprises)	Creative
CNS14	# of jobs in NAICS sector 56 (Administrative & Support & Waste Management & Remediation Services)	Creative
CNS15	# of jobs in NAICS sector 61 (Educational Services)	Creative
CNS16	# of jobs in NAICS sector 62 (Health Care and Social Assistance)	Creative
CNS17	# of jobs in NAICS sector 71 (Arts, Entertainment, and Recreation)	Creative
CNS18	# of jobs in NAICS sector 72 (Accommodation and Food Services)	Creative
CNS19	# of jobs in NAICS sector 81 (Other Services [except Public Administration])	Service
CNS20	# of jobs in NAICS sector 92 (Public Administration)	Service

Location Affordability Index (LAI/LAP)

Last Update: 4/17/2015

The Location Affordability Index (LAI) was created by Sustainable Communities partnership between the U.S. Department of Housing and Urban Development (HUD) and the U.S. Department of Transportation (DOT). This data gives estimates and percentages of transportation and housing cost for families by location (block group and tract). We have drawn housing + transportation percentages, employment access index, job density, median commute distance, and CO2 at the block group level with the ACS 5-year 2008-2012 dataset.

The map layer provides a look at the Housing + Transportation percentage costs as a percent of a 3 person median family income.

Percent of Income Spent on Housing + Transportation & Neighborhood Change

This variable indicates the cost burden of living in the Block Group area.
A lower percentage of Income spent on Housing and Transportation indicates that an area is affordable. However, the additional layer of information that reveals the household income quintiles indicates whether it is affordable for higher or lower-income neighborhoods.

Employment Access Index

Last Update: 11/17/2015

This layer depicts the 2008-2012 Location Affordability Index employment access by the block group level at a 0-100 index.

Job Density

Last Update: 1/25/2016

This layer depicts the 2008-2012 Location Affordability Index job density by the block group level at a normalized 0-100 index. Job Density is defined by the total number of jobs divided by the block group land area in acres.

Median Commute Distance Layer

Last Update: 9/21/2015

This layer depicts the 2008-2012 Location Affordability Index median commute distance from 0 - 200 miles at the block group level using the median commute distance layer from the 2008-2012 Location Affordability Index.

Regional Efficiency Index Layer

Last Update: 11/17/2015

The Regional Efficiency Index (REI) combines 2014 Walk Score data and the depicts the 2008-2012 Location Affordability Index Employment Access Index to derive a 0-100 scoring in terms of block groups.

Employment Access Index (Normalize) + Walk Score (Normalize) / 2

CNT Housing + Transportation Index

The Center for Neighborhood Technology created the 2009-2013 Housing + Transportation (H+T) Affordability Index tool that measures how affordable a block group is in terms of not only housing cost but transportation costs. This data set also calculates additional attributes such as the Greenhouse Gas (GHG) Auto-use Emission per household.

Greenhouse Gas (GHG) Auto-Use Emissions Layer

Last Update: 1/25/2016

We used the 2009-2013 Greenhouse Gas Emissions data from the The Center for Neighborhood Technology auto-use per household dataset in tonnes.

Intersection Density Layer

Last Update: 11/17/2015

This layer is also derived from the 2014 Walk Score data and presents the number of intersections divided by total land area to determine intersections by acre and can serve as a measure of local walkability and density of the area.

Housing/Rental Market Performance Index - Zillow

Zillow Rental Value Index Layer

Last Update: 11/15/2016

The Zillow Rent Index (ZRI) tracks the monthly median rent in particular by zip code. We use Zillow data that looks at how the most recent month’s Home Value Index compared with the Rental Value Index for a year ago. This gives us a year-over-year change in the Rental Value Index. This map depicts number of standard deviations from the regional average change in Rental Value Index for the SCAG region.

When the regional average rental value index is increasing, the zip codes with positive standard deviation values are experiencing higher rent increases than the region as a whole, with a greater number of standard deviations indicating a higher increase in rent. Zip codes with negative standard deviation values are experiencing changes in rent that are less than the regional average.

If the regional average is decreasing, then zip codes with a positive standard deviation might be experiencing decreases in rents, just at a lesser rate than the regional average.

Zillow Home Value Index Layer

Last Update: 11/15/2016

The Zillow Home Value Index (ZHVI) tracks the monthly median sale price by zip code. We use Zillow data that looks at how the most recent month’s Home Value Index compared with the Home Value Index for a year ago. This gives us a year-over-year change in the Home Value Index. The map depicts the number of standard deviations from the regional average change in Home Value Index for the SCAG region.

When the regional average is increasing, the zip codes with positive standard deviation values are experiencing higher rates home value increases than the region as a whole, with a greater number of standard deviations indicating a higher increase in the percentage change of home value. Zip codes with negative standard deviation values are experiencing changes in home value that are less than the regional average.

When the regional average is decreasing, then zip codes with a positive standard deviation might be experiencing decreases in home values, just at a lesser rate than the regional average.

Housing Costs & Neighborhood Change

Housing values and rent costs suggest the cost of living in a particular area. These variables can indicate low capitalized rents and/or the existence of overvalued homes that is consistent with trends in gentrified neighborhoods (Bradway Laska, Seaman, and McSeveney 1982: 158; Smith 1986: 24; Chapple 2009: 6).
(-) As the percentage of area median owner occupied housing value increases, the potential for gentrification susceptibility decreases (the area may be already experienced gentrification to some degree).
(-) As the percentage of area gross median rent increases, the potential for gentrification susceptibility decreases (the area may be already experienced gentrification to some degree).

Food Environment Index

Last Update: 6/17/2015

The 2011 modified Retail Food Environment Index (mRFEI) was created by the Center for Disease Control and Prevention (CDC). mRFEI measures the number of healthy and less healthy food retailers in regions by 2000 census tracts and scores the regions a 0 (no healthy food) - 100. mFREI uses establishment-level data with 6-digit NAICS codes to classify food retail outlets into in 3 categories: supermarkets, convenience stores, and fast food restaurants. The CDC makes mRFEI scores for each census tract available for download.

Open Space

Last Update: 2/23/2016

The Open Space data was created by Open Street Map extracted via Geofabrik in 2015. This data provides all available data on water and open space within the SCAG region. It can be downloaded here. See something that doesn’t look right? Open Street Map is the Wikipedia of maps. You can register for an account and start making changes. We’ll incorporate those changes the next time we download open space data from Open Street Map.

Open Space

We queried the following fields as open space from the land use, building, natural and land use Open Street Map shapefiles: recreational, meadow, grass, garden, community garden, conservation, cemetery, beach, nature reserve, greenfield, park, community center, picnic site, ski school, sports, forest, and park.

Disadvantaged Communities Metric

Last Update: 4/11/2017

The California Environmental Protection Agency (CalEPA) developed an index called CalEnviroScreen 3.0 that identifies communities disproportionately burdened by pollution at the census tract level in 2016. CalEnviroScreen combines various sources of pollution data (e.g. superfund sites, air pollution by particle type, vehicle volumes) with indicators of sensitive populations, such as children, the poor, and the language-isolated. They derive deciles that can determine funding eligibility for sources like the Strategic Growth Council (SGC).

This layer depicts the top 25% Disadvantages Communities that score high in many of the variables listed below.

Variables	Indicator	Descriptions
CalEnviroScreen Decile		The cumulative scores of pollution burden and population characteristics.
CalEnviroScreen Percentile		Percentile of the CalEnviroScreen score
Pollution Burden	Pollution	The cumulative scores of pollution such as ozone, pm 2.5, diesel, pesticide, and traffic.
Air Quality: Ozone	Exposure	This is the amount of the daily maximum 8 hours ozone concentration.
Air Quality: pm 2.5	Exposure	Annual mean concentration of PM2.5 over three years (2009-2011).
Diesel Particulate Matter	Exposure	Spatial distribution of gridded diesel PM emissions from on-road and nonroad sources in kg/day.
Pesticide Use	Exposure	Total pounds of selected active pesticide ingredients used in production-agriculture per square mile.
Toxic Releases from Facilities	Exposure	Toxicity-weighted concentrations of modeled chemical releases to air from facility emissions and off-site incineration.
Traffic Density	Exposure	Traffic density – Sum of traffic volumes adjusted by road segment length (vehicle-kilometers per hour) divided by total road length (kilometers) within 150 meters of the census tract boundary.
Drinking Water Contaminants	Exposure	Drinking water contaminant index for selected contaminants.
Cleanup Sites	Environmental Effects	Sum of weighted sites within each census tract.
Groundwater Threats	Environmental Effects	Sum of weighted scores for sites within each census tract.
Hazardous Waste Sites and Facilities	Environmental Effects	Sum of weighted permitted hazardous waste facilities and hazardous waste generators within each census tract.
Impaired Water Bodies	Environmental Effects	Summed number of pollutants across all water bodies designated as impaired within the area.
Solid Waste Sites and Facilities	Environmental Effects	Sum of weighted solid waste sites and facilities.
Population Characteristics	Sensitive Populations	Population Characteristics scores for each census tract are derived from the average percentiles for the three Sensitive Populations indicators and the three Socioeconomic Factors indicators.
Low Birth Weight	Sensitive Populations	Percent low birth weight, spatially modeled (averaged over 2006-2009).
Asthma Emergency Department Visits	Sensitive Populations	Spatially modeled, age-adjusted rate of emergency department (ED) visits for asthma per 10,000 (averaged over 2007-2009).
Age (Children and Elderly)	Sensitive Populations	Percent of population under age 10 or over age 65.
Low Educational Attainment	Socioeconomic Factors	Percent of the population over age 25 with less than a high school education (5-year estimate, 2008-2012).
Linguistic Isolation	Socioeconomic Factors	Percentage of households in which no one age 14 and over speaks English "very well" or speaks English only.
Poverty	Socioeconomic Factors	Percent of the population living below two times the federal poverty level (5-year estimate, 2008-2012).
Unemployment	Socioeconomic Factors	Percent of the population over the age of 16 that is unemployed and eligible for the labor force. Excludes retirees, students, homemakers, institutionalized persons except prisoners, those not looking for work, and military personnel on active duty (5-year estimate, 2008-2012).

Bike and Pedestrian Collisions

Last Update: 1/22/2016

This is a Statewide Integrated Transportation System (SWITRS) data set that contains bicycle and pedestrian collisions from 2003 - 2011. This dataset was geocoded and prepared by the Transportation Injury Mapping System (TIMS). We have spatially joined the geocoded pedestrian and bicycle collisions to 2010 US Census block groups. If you would like to analyze other crash data, please consider looking at TIMS other mapping and analysis tools.

LANDUSE

Employment and Population Change (2008-2035)

Last Update: 12/18/2014

This layer depicts the change in employment and population density from 2008-2035 according to the 2012-2035 SCAG Regional Transportation Plan. In this dot density map, each dot represents 4,000 jobs/persons.

Integrated Growth Forecast - Housing

Last Update: 3/9/2015

This layer depicts change in housing density from 2008-2035 according to the 2012-2035 SCAG Regional Transportation Plan.

General Plan

Last Update: 1/25/2015

This layer depicts the zoning according to the 2012-2035 SCAG Regional Transportation Plan for each county in two levels: simplified (zoomed out) and complex (zoomed in).

Land Use

Last Update: 1/25/2015

This layer depicts the existing land use according to the 2012-2035 SCAG Regional Transportation Plan for each county in two levels: simplified (zoomed out) and complex (zoomed in).

Parking

Last Update: 1/22/2016

This layer shows the 2015 existing parking derived from Open Street Map data extracted from Map Zen. The following shapefiles were used: Landusages and Buildings. Buildings was queried for garage, garages, and parking structures. And Landusages was queried for parking. The parking tables also include Open Street Map Parking Amenities. See table below for further information.

Estimated parking values were derived using the Methodology of the 2015 Journal of the American Planning Association, “Parking Infrastructure: A Constraint on or Opportunity for Urban Redevelopment? A Study of Los Angeles County Parking Supply and Growth”. This methodology derives historic land use changes from the 2012 assessor databases and historical decadal censuses to determine parking within residential and commercial parcels. And a separate street network analysis to determine estimated street parking.

REVISION Key	OSM Key	Default	Type	Value (Drop down)	OSM Comment
APN			string	APN
amenity	amenity	N/A	string	parking	Tag either an area or a central node, but not both.
Name	name	None	string	text	The name of the car park.
parking	parking	None	string	surface	One level of parking on the ground.
				multi-storey	Two or more levels of parking decks in a building structure.
				underground	One level of parking in the basement.
				rooftop	One level of a parking deck on top of the building.
				sheds	Private hangars for vehicles, located close to owner's home. Usually constructed of profiled metal.
				carports	Structure used to offer limited protection to vehicles, primarily cars, from the elements ( Carports on Wikipedia).
				garage_boxes	One level buildings with individual boxes for one car, each, usually made of brick and metal. Usually, this area belong to garage cooperative with own name, chairman, budget, rules, security, etc.
Accessibility	access	N/A	short integer	yes; customers; permissive; private	Distinction between public parking lots, customers parking lots (such as at cinemas, etc.), and private parking lots (such as for staff in a business park). In this case, yes denotes a public parking lot.
Park and Ride	park_ride	None	string	yes; no; bus; train; tram; metro; ferry	Park and ride. Values of the key define connected means of transport. If unsure, use yes. (see Proposal)
Fee	fee	no	short integer	interval	Whether you have to pay a parking fee or not. If the fee must be paid only on certain hours, the same syntax can be used as for opening hours. (See the discussion page.)
Supervised	supervised	no	short integer	interval	Whether the cars are guarded to prevent car theft and vandalism. If a guard is only present on certain hours, the same syntax can be used as for opening hours.
Status			text	estimated; observed	Estimated values come from a recent study and observed values are inputted by users.
Capacity	capacity	None	short integer	number	The amount of available parking spaces, including all special parking spaces (e.g., disabled). Read talk page on this.
Disabled	capacity:disabled	None	short integer	number	Defines whether or not dedicated disabled parking spaces are available, usually reserved only for holders of a disabled parking permit ('blue badge' in the UK). If known, the number of spaces can be specified. (replaces the key disabled_spaces=* see proposal).
Charging	capacity:charging	None	short integer	number	Defines whether or not dedicated parking spaces with charging infrastructure for electric vehicles are available. If known, the number of spaces can be specified.
Maximum Stay	maxstay	None	string	<1 hr, 1hr, 2hr, 3hr, >3hr	Time limit for parking (e.g., customer parking for 2 hours)
Opening Hours	opening_hours	None	string	Checkbox (days of week) and Fill in (hours right next to it):	Opening hours of this parking lot.

Estimated Floor Area Ratio (FAR)

Last Update: 1/22/2016

This layer shows the estimated floor area ratio (FAR) at the parcel level in Los Angeles, Riverside, and San Bernardino SCAG Counties. FAR is a standard that some cities use for measuring the allowed buildable area in terms of floors or building area size. These standards range in each city and their distinct neighborhoods. The estimated FAR derives a value from existing 2012 Assessor’s parcel data on gross building area, number of buildings, stories and lot area. Estimated FAR is calculated by dividing gross building area by lot area.

MOBILITY/ACCESSIBILITY

Bikeway Network

Last Update: 1/25/2016

This layer depicts the 2012-2035 SCAG Regional Transportation Plan bikeway network of existing and proposed bike class levels I (Bike Path), II (Bike Lane), and III (Bike Route).

Bicycle Counts - UCLA Bike Count Clearinghouse

Last Update: Continuous automated updates
The Bike Count Data Clearinghouse is a one-stop repository for bicycle count data throughout LA County and beyond. This tool allows users to easily view, query, and download bicycle count volumes. Bicycle count data collected in Los Angeles County prior to December 2012 is already loaded into the clearinghouse. Going forward, local agencies throughout the Southern California Association of Governments (SCAG) region and beyond can upload their count data to the clearinghouse website.

Walk Score

Last Update: 11/16/2015

Walk Score measures the walkability of locations with points given to amenities based on distance in a 0-100 index for the year 2014. The lowest score is deemed Very Car-Dependent and the highest scoring areas are Walker’s Paradise. This scoring is determined via the Walk Score system that measures the walkability of any location (x,y) via walking routes to nearby amenities. Within our map, there are over 13,000 Walk Score locations that were selected via Weighted Population Block Group Centroids, Top 5% LEHD Jobs regions and SCAG HQTA areas.

High Quality Transit and Transit Priority Areas Layer

Last Update: 1/25/2015

High Quality Transit Areas (HQTA) are half-mile buffers along transit lines (rail, bus, and flexible transit service) that come every 15 minutes during peak hours. Transit Priority Areas (TPA) are half-mile buffer areas along existing or planned major transit. Both HQTA and TPA layers are planned areas for 2035 and come from the 2012-2035 SCAG Regional Transportation Plan.

Public Transit

Last Update: 12/10/2015

This layer depicts Fall 2015 bus, rapid, and rail transit routes in the SCAG region. The data was extracted from the General Transit Feed Specification (GTFS) and directly from municipalities that do not have their routes available on GTFS.