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2015 Incorporated Cities and Unincorporated Area Greenhouse Gas Inventory (GPC Compliant)
Created
September 3 2019
Views
42
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.
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.
Created
August 29 2019
Views
8
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.
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.
Created
August 29 2019
Views
11
PEV and HEV Registrations (provided by NREL/SCAG already aggregated by city): Data exclusively refers to 88 unincorporated areas.
Created
August 26 2019
Views
22
Data sourced from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015.
Data includes geocoded point data from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015 (the latest year available). The data set was narrowed to collisions in which bicyclists or pedestrians were the victims and for fatalities and severe injuries for two reasons. This best addresses the goals of the County’s Vision Zero Plan. Also, TIMS data is less reliable for minor injuries and does not represent frequently unreported collisions.
The TIMS data was loaded into GIS and overlaid it on a map of LA County. Transparent points were used to convey what areas have had the highest number of collisions between 2006-2015.
Data includes geocoded point data from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015 (the latest year available). The data set was narrowed to collisions in which bicyclists or pedestrians were the victims and for fatalities and severe injuries for two reasons. This best addresses the goals of the County’s Vision Zero Plan. Also, TIMS data is less reliable for minor injuries and does not represent frequently unreported collisions.
The TIMS data was loaded into GIS and overlaid it on a map of LA County. Transparent points were used to convey what areas have had the highest number of collisions between 2006-2015.
Created
August 8 2019
Views
50
Data sourced from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015.
Data includes geocoded point data from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015 (the latest year available). The data set was narrowed to collisions in which bicyclists or pedestrians were the victims and for fatalities and severe injuries for two reasons. This best addresses the goals of the County’s Vision Zero Plan. Also, TIMS data is less reliable for minor injuries and does not represent frequently unreported collisions.
The TIMS data was loaded into GIS and overlaid it on a map of LA County. Transparent points were used to convey what areas have had the highest number of collisions between 2006-2015.
Data includes geocoded point data from the Transportation Injury Mapping System (TIMS) for all collisions in LA County from 2006-2015 (the latest year available). The data set was narrowed to collisions in which bicyclists or pedestrians were the victims and for fatalities and severe injuries for two reasons. This best addresses the goals of the County’s Vision Zero Plan. Also, TIMS data is less reliable for minor injuries and does not represent frequently unreported collisions.
The TIMS data was loaded into GIS and overlaid it on a map of LA County. Transparent points were used to convey what areas have had the highest number of collisions between 2006-2015.
Created
August 8 2019
Views
34
Distribution of housing and transportation costs as a percentage of income for selected geographies (2017). Calculations are based on 2015 ACS data and 2014 Longitudinal Employer-Household Dynamics database. Data includes Los Angeles County, City of Los Angeles, Los Angeles Region, San Diego County and San Francisco Region.
Created
August 8 2019
Views
18
Data contains locations and CalEnviroScreen scores of EV charging stations throughout LA County.
Created
August 7 2019
Views
25
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