UCLA Energy Atlas

Data sourced from UCLA Energy Atlas. Includes building energy use by city and building type.

• Requested and received estimates of population by SPA from LA County Public Health for the purposes of normalizing counts of ED visits
• Requested and received counts of heat stress ED visits by Special Planning Area from LACDPH
• Normalized raw counts by population.
• Generated line graphs of county total heat stress ED visits per 100,000 residents.
• Generated line graphs of heat stress ED visits by SPA.
• Omitted SPA 5 and 6 for all years except 2008 because the counts were too small.

• Requested and received estimates of population by SPA from LA County Public Health for the purposes of normalizing counts of ED visits
• Requested and received counts of heat stress ED visits by Special Planning Area from LACDPH
• Normalized raw counts by population.
• Generated line graphs of county total heat stress ED visits per 100,000 residents.
• Generated line graphs of heat stress ED visits by SPA.
• Omitted SPA 5 and 6 for all years except 2008 because the counts were too small.

Data by Special Planning Area from LA County Public Health for the purposes of normalizing counts of ED visits. Data is normalized by population and includes counts of heat stress ED visits by Special Planning Area from LACDPH.
Omitted SPA 5 and 6 for all years except 2008 because the counts were too small.

Geospatial data of gentrified census tracts and proximty to high quality transit areas.
The proximity of gentrified census tracts to 2012 HQTAs was mapped. California Housing Partnership identified tracts that gentrified between 2000 and 2013, defining gentrification as socioeconomically disadvantaged neighborhoods that experienced faster changes in the following areas relative to County-level trends during the same period: 1) the percentage point increase in college educated population; 2) the percentage point increase non-Hispanic white population; 3) absolute value increase in median household income; and 4) the absolute value increase in gross rent. The gentrified census tract layer was added to a map of 2012 HQTAs within LA County.

• A gap analysis to determine the shortage or surplus of affordable housing by income group was done by CHPC for renter households for years 2014-2016.
• Income groups are defined as follows:
o Deeply Low Income (DLI) is 0-15% of Area Median Income (AMI)
o Extremely Low Income (ELI) is 16-30% of AMI
o Very Low Income (VLI) is 31-50% of AMI
o Low Income is 50-80% of AMI
o Moderate Income is 80-100% of AMI
• The CHPC data shows the gap between the need for affordable housing for renter households and the supply at different income levels. We used this data to create charts to present the data over time.
• The first chart shows the cumulative deficit of affordable housing for each income group for years 2014-2016. Note, there is a larger deficit of housing for low income households compared to very low income households because there are a greater number of low income households. For example, housing that is affordable for deeply low income households is also counted as affordable to other income groups.
• The second chart shows the percentage of low income households (excludes moderate income group) for which there is no available affordable housing (housing shortage). In this data presentation, a lower percentage is better.

Data describes housing affordability for selected geographies and determines the shortage or surplus of affordable housing by income group was done by CHPC for renter households for years 2014-2016.
Deeply Low Income (DLI) is defined as 0-15% of Area Median Income (AMI)
Extremely Low Income (ELI) is defined as 16-30% of AMI
Very Low Income (VLI) is defined as 31-50% of AMI
Low Income is defined as 50-80% of AMI
Moderate Income is defined as 80-100% of AMI

Percent of Total Regional Housing Needs Assessment Allocation Built by Jurisdiction Aggregated across all Income Levels (2018)

• Regional Housing Needs Assessment (RHNA) allocation sets goals for every jurisdiction to produce its share of regional housing needs at various income levels. LA County is currently in its 5th RHNA cycle. The allocation was set in 2012 with the goal of completing the required housing production by 2021.
• RHNA allocation and progress data was downloaded from the 5th Cycle Annual Progress Report Permit Summary published by the California Department of Housing and Community Development. The summary reports the RHNA allocation and the number of units permitted for Very Low Income, Low Income, Moderate Income, and Above Moderate Income levels for each city and the unincorporated area as of 12/4/2018. Using this data the percent of units built (completed) and the units remaining to be built at each income level and for the LA County was calculated, and the information is presented in tabular format.
• The percent of the total RHNA allocation (aggregated across all income groups) built for each jurisdiction was calculated. This data was joined with a shapefile of LA County jurisdiction using the field “city_name”, and the percentage of total RHNA allocation built for each jurisdiction was mapped.

See https://data.lacounty.gov/Transportation/County-Employee-Average-Vehicle-Ridership-AVR-2012/b92g-vuub for more detail.

• Average Vehicle Ridership (AVR) is the figure derived by dividing the employee population at a given worksite that reports to work weekdays between 6:00 a.m. and 10:00 a.m. by the number of vehicles driven by these employees commuting from home to the worksite during these hours. The AVR is calculated using a weekly averaging period. The applicable employee population is multiplied by the number of weekdays in the selected averaging period, then divided by the total number of vehicles driven by these employees to the worksite during the same period.
• The survey is administered to each county department by location. The calculated AVR for each responding location was included in the data from the CSO (who received the data from the Department of Human Resources) for years 2012-2018, except 2017. An AVR of “1” means that every employee drove alone; therefore a greater AVR is a better outcome. The target AVR is set for each county department, and targets range mostly from 1.5-1.75.
• For each year, a weighted average for the total AVR across county departments was calculated to account for the varied number of employees at each location and graphically presented the data.