Upload
others
View
1
Download
0
Embed Size (px)
Citation preview
Job Accessibility Analysis An Integration of GIS and SAS Applications
Southern California Association of GovernmentsDivision of Land Use and Environmental Planning
Department of Research and Analysis
2016 ESRI User ConferenceSan Diego Convention Center
Tom VoJung SeoFrank Wen, PhDSimon Choi, PhD
Content
Introduction of SCAG
Research Intention
Theoretical Background
Methodology
Results and Conclusions
Future Improvements
SCAG Overview
Research Intention SCAG Mission Statement
Under the guidance of the Regional Council and in collaboration with our partners, our mission is to facilitate a forum to develop and foster the realization of regional plans that improve the quality of life for Southern Californians
2016-2040 RTP/SCS SCAG envisions a region that has grown by nearly four million
people—sustainably. In communities across Southern California, people enjoy increased mobility, greater economic opportunity and a higher quality of life
Title VI of the 1964 Civil Rights Act of 1964 Environmental Justice Analysis seeks to avoid disproportionately
high and adverse impacts on minority and low income populations with respect to human health and the environment
Image credit: trinityconsultants
Environmental Justice Analysis
2016 RTP/SCS EJ Appendix SCAG identified 18 performance measures.
Here are some of the areas we analyzed: Benefits and burdens analysis (tax,
system usage, investments) Distribution of travel time savings and
travel distance reductions Jobs-housing imbalance or jobs-
housing mismatch Accessibility to employment and
services Gentrification and displacement Emissions impacts analysis Aviation noise impacts Roadway noise impacts Active transportation hazards Public health analysis Rail-related impacts Climate vulnerability …and more!
Theoretical Background
Transportation and land use decisions determine access to opportunities and have far-reaching effects on social justice and equity
Land use patterns or the distribution of activities within the urban landscape describe the spatial dispersion of these destinations, and together transportation and land use influence the ability of households to meet their daily needs
Accessibility is measured by the spatial distribution of potential destinations, the ease of reaching each destination, and the magnitude, quality and character of activities at potential destination sites
Methodology
There are two types of analysis on accessibility: time and distance Time-based Job Accessibility Measure the accessibility by travel time using
street network Distance-based Job Accessibility Measure the accessibility by distance from a
centroid of a TAZ This approach can be useful for determining the
relative accessibility for short trips, such as those that are more likely to be completed using active transportation modes.
Methodology (Cont.)
Distance-based Job Accessibility Calculation Calculate regional job share within one mile buffer
from a TAZ’s centroid
Calculate Weighted Average Job Accessibility within One Mile Distance (Measured as the Percent of Regional Employment Accessible for Each Cohort)
. ∑ . ∗ .
+. ∗
.+
. ∗ .
Methodology (Cont.)
11,267 Transportation Analysis Zones (TAZs) in SCAG region
LA51%
OR15%
RV14%
SB12%
VN6%
IM2%
Methodology (Cont.) - GIS
Utilizing spatial analysis and data management tools in ArcGIS to calculate jobs within one-mile buffer
Centroid Select Intersect
Methodology (Cont.) - GIS
ArcGIS 10.3 ModelBuilder to automatically perform spatial analysis and field management to calculate jobs within one mile buffer
Feature To Poin Tie2_scag_201emp12 pnt im Buffer
Tie2_scag_201emp12_2mibuf
m
Add Field "PROPTie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (6
Add Field "PCT TTie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (7
Calculate Field"PROP AC"
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(6)
Calculate Field"PCT TAZ"
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(7)
Intersect (4)Tie2_scag_201emp12_2mibuf
t im
Add Field "EMP1Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (2)
Add Field "RETAITie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (3
Calculate Field"EMP12"
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (5
Calculate Field"RETAIL12"
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (6)
Tie2_taz_scag10_emp12_sec
im
Tie2_taz_scag10_emp12_sec
Copy.shp
Summary StatistiTie2_scag_201emp12_2mibuf
im.dbf
Feature To Point Tie2_scag_201emp12 pnt r Buffer (2) Tie2_scag_201
emp12 2mibuf
Add Field "PROP_(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (2
Add Field "PCT_T(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (3
Calculate Field"PROP AC" (2)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(2)
Calculate Field"PCT TAZ" (2)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(3)
Intersect (2)Tie2_scag_201emp12_2mibuf
t rv
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (4)
Add Field "RETAI(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (7
Calculate Field"EMP12" (2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (8
Calculate Field"RETAIL12" (2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (9)
Tie2_taz_scag10_emp12_sec
Copy.shp (2)
Summary StatisticTie2_scag_201emp12_2mibuf
rv.dbf
Feature To Point Tie2_scag_201emp12 pnt s Buffer (3)
Tie2_scag_201emp12_2mibuf
b
Add Field "PROP_(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (4
Add Field "PCT_T(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (5
Calculate Field"PROP AC" (3)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(4)
Calculate Field"PCT TAZ" (3)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(5)
Intersect (3)Tie2_scag_201emp12_2mibuf
t sb
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (10
Calculate Field"EMP12" (3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (11
Tie2_taz_scag10_emp12_sec
Copy.shp (3)
Add Field "RETAI(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (12
Calculate Field"RETAIL12" (3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (13Summary Statistic
Tie2_scag_201emp12_2mibuf
sb.dbf
Feature To Point Tie2_scag_201emp12 pnt v Buffer (4)
Tie2_scag_201emp12_2mibuf
n
Add Field "PROP_(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (8
Add Field "PCT_T(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (9
Calculate Field"PROP AC" (4)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(8)
Calculate Field"PCT TAZ" (4)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(9)
Intersect (5)Tie2_scag_201emp12_2mibuf
t vn
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (14
Calculate Field"EMP12" (4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (15
Tie2_taz_scag10_emp12_sec
Copy.shp (4)
Add Field "RETAI(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (16
Calculate Field"RETAIL12" (4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (17Summary Statistic
Tie2_scag_201emp12_2mibuf
vn.dbf
Tie2_taz_scag10_emp12_sec
rv
Tie2_taz_scag10_emp12_sec
sb
Tie2_taz_scag10_emp12_sec
vn
Feature To Point Tie2_scag_201emp12 pnt o Buffer (5) Tie2_scag_201
emp12 2mibuf
Add Field "PROP_(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (1
Add Field "PCT_T(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (1
Calculate Field"PROP AC" (5)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(10)
Calculate Field"PCT TAZ" (5)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(11)
Intersect (6)Tie2_scag_201emp12_2mibuf
t or
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (18
Calculate Field"EMP12" (5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (19
Tie2_taz_scag10_emp12_sec
Copy.shp (5)
Add Field "RETAI(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (20
Calculate Field"RETAIL12" (5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (21Summary Statistic
Tie2_scag_201emp12_2mibuf
or.dbf
Tie2_taz_scag10_emp12_sec
or
Merge Tie2_scag_20emp12 2mibu
Feature To Poin Tie2_scag_201emp12 pnt im Buffer
Tie2_scag_201emp12_2mibuf
m
Add Field "PROPTie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (6
Add Field "PCT TTie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (7
Calculate Field"PROP AC"
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(6)
Calculate Field"PCT TAZ"
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(7)
Intersect (4)Tie2_scag_201emp12_2mibuf
t im
Add Field "EMP1Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (2)
Add Field "RETAITie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (3
Calculate Field"EMP12"
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (5
Calculate Field"RETAIL12"
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (6)
Tie2_taz_scag10_emp12_sec
im
Tie2_taz_scag10_emp12_sec
Copy.shp
Summary StatistiTie2_scag_201emp12_2mibuf
im.dbf
Feature To Point Tie2_scag_201emp12 pnt r Buffer (2) Tie2_scag_201
emp12 2mibuf
Add Field "PROP_(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (2
Add Field "PCT_T(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (3
Calculate Field"PROP AC" (2)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(2)
Calculate Field"PCT TAZ" (2)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(3)
Intersect (2)Tie2_scag_201emp12_2mibuf
t rv
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (4)
Add Field "RETAI(2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (7
Calculate Field"EMP12" (2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (8
Calculate Field"RETAIL12" (2)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (9)
Tie2_taz_scag10_emp12_sec
Copy.shp (2)
Summary StatisticTie2_scag_201emp12_2mibuf
rv.dbf
Feature To Point Tie2_scag_201emp12 pnt s Buffer (3)
Tie2_scag_201emp12_2mibuf
b
Add Field "PROP_(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (4
Add Field "PCT_T(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (5
Calculate Field"PROP AC" (3)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(4)
Calculate Field"PCT TAZ" (3)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(5)
Intersect (3)Tie2_scag_201emp12_2mibuf
t sb
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (10
Calculate Field"EMP12" (3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (11
Tie2_taz_scag10_emp12_sec
Copy.shp (3)
Add Field "RETAI(3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (12
Calculate Field"RETAIL12" (3)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (13Summary Statistic
Tie2_scag_201emp12_2mibuf
sb.dbf
Feature To Point Tie2_scag_201emp12 pnt v Buffer (4)
Tie2_scag_201emp12_2mibuf
n
Add Field "PROP_(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (8
Add Field "PCT_T(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (9
Calculate Field"PROP AC" (4)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(8)
Calculate Field"PCT TAZ" (4)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(9)
Intersect (5)Tie2_scag_201emp12_2mibuf
t vn
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (14
Calculate Field"EMP12" (4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (15
Tie2_taz_scag10_emp12_sec
Copy.shp (4)
Add Field "RETAI(4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (16
Calculate Field"RETAIL12" (4)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (17Summary Statistic
Tie2_scag_201emp12_2mibuf
vn.dbf
Tie2_taz_scag10_emp12_sec
rv
Tie2_taz_scag10_emp12_sec
sb
Tie2_taz_scag10_emp12_sec
vn
Feature To Point Tie2_scag_201emp12 pnt o Buffer (5) Tie2_scag_201
emp12 2mibuf
Add Field "PROP_(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (1
Add Field "PCT_T(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
1of2b int (1
Calculate Field"PROP AC" (5)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(10)
Calculate Field"PCT TAZ" (5)
Tie2_2010_em_ejvar09to13_3buffer_intrsct_
(11)
Intersect (6)Tie2_scag_201emp12_2mibuf
t or
Add Field "EMP12Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (18
Calculate Field"EMP12" (5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (19
Tie2_taz_scag10_emp12_sec
Copy.shp (5)
Add Field "RETAI(5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (20
Calculate Field"RETAIL12" (5)
Tie2_taz_scag10_emp12_ejv9to13_2mibuff_
4of4 int (21Summary Statistic
Tie2_scag_201emp12_2mibuf
or.dbf
Tie2_taz_scag10_emp12_sec
or
Merge Tie2_scag_20emp12 2mibu
Methodology (Cont.) - SAS
Statistical Analysis Software (SAS)
Methodology (Cont.) - SAS
Utilizing SAS to calculate job accessibility within one-mile buffer weighted by different population groups Proc import, proc sort, proc means, merge
Results
Results (Cont.)
Utilizing SAS script to efficiently generate summary tableWeighted Average Job Accessibility within One Mile Distance (Measured as the Percent of Regional Employment Accessible for Each Cohort)
SCAG (BY) SCAG (BL) SCAG (PL) EJA (BY) EJA (BL) EJA (PL) DGA (BY) DGA (BL) DGA (PL) CoC (BY) CoC (BL) CoC (PL) Urban (BY)
Urban (BL)
Urban (PL) Rural (BY) Rural (BL) Rural (PL)
Elderly 0.13% 0.13% 0.14% 0.15% 0.15% 0.17% 0.17% 0.17% 0.20% 0.14% 0.14% 0.15% 0.13% 0.13% 0.15% 0.00% 0.00% 0.00%
Disabled 0.14% 0.12% 0.13% 0.15% 0.13% 0.15% 0.16% 0.15% 0.17% 0.14% 0.13% 0.14% 0.14% 0.13% 0.14% 0.00% 0.00% 0.00%
Poverty 0.17% 0.15% 0.17% 0.19% 0.16% 0.18% 0.21% 0.17% 0.21% 0.16% 0.14% 0.15% 0.18% 0.15% 0.17% 0.00% 0.00% 0.00%
NH‐White 0.12% 0.12% 0.13% 0.15% 0.15% 0.16% 0.18% 0.18% 0.21% 0.13% 0.15% 0.15% 0.13% 0.13% 0.14% 0.00% 0.00% 0.00%
NH‐Black 0.13% 0.11% 0.11% 0.14% 0.11% 0.12% 0.15% 0.12% 0.13% 0.12% 0.11% 0.11% 0.13% 0.11% 0.12% 0.00% 0.00% 0.00%
NH‐Asian 0.16% 0.15% 0.16% 0.18% 0.17% 0.19% 0.20% 0.19% 0.22% 0.18% 0.17% 0.18% 0.16% 0.15% 0.17% 0.00% 0.00% 0.00%
NH‐Indian 0.10% 0.10% 0.11% 0.11% 0.11% 0.12% 0.16% 0.14% 0.16% 0.13% 0.12% 0.12% 0.11% 0.11% 0.12% 0.00% 0.00% 0.00%
Hispanic 0.13% 0.12% 0.13% 0.13% 0.13% 0.14% 0.15% 0.15% 0.16% 0.14% 0.13% 0.14% 0.13% 0.12% 0.14% 0.00% 0.00% 0.00%
NH‐Other 0.14% 0.13% 0.14% 0.16% 0.15% 0.17% 0.18% 0.18% 0.21% 0.14% 0.15% 0.16% 0.14% 0.14% 0.15% 0.00% 0.00% 0.00%
Income 1 0.17% 0.15% 0.17% 0.19% 0.16% 0.18% 0.22% 0.18% 0.21% 0.17% 0.14% 0.15% 0.18% 0.15% 0.17% 0.00% 0.00% 0.00%
Income 2 0.15% 0.14% 0.16% 0.16% 0.15% 0.18% 0.18% 0.17% 0.20% 0.15% 0.14% 0.15% 0.15% 0.14% 0.16% 0.00% 0.00% 0.00%
Income 3 0.14% 0.13% 0.15% 0.15% 0.15% 0.17% 0.16% 0.17% 0.20% 0.14% 0.14% 0.15% 0.14% 0.14% 0.16% 0.00% 0.00% 0.00%
Income 4 0.13% 0.13% 0.15% 0.15% 0.15% 0.17% 0.16% 0.17% 0.21% 0.14% 0.14% 0.15% 0.13% 0.14% 0.15% 0.00% 0.00% 0.00%
Income 5 0.14% 0.14% 0.15% 0.17% 0.16% 0.19% 0.17% 0.19% 0.23% 0.14% 0.15% 0.16% 0.14% 0.14% 0.16% 0.00% 0.00% 0.00%
Average 0.139% 0.130% 0.143% 0.154% 0.145% 0.163% 0.176% 0.167% 0.194% 0.145% 0.141% 0.147% 0.143% 0.135% 0.150% 0.002% 0.002% 0.001%
Results (Cont.)
0.00% 0.05% 0.10% 0.15% 0.20%
Hispanic
NH White
NH Black
NH Am. Indian
NH Asian & PI
NH Others
Age 0 to 4
Age 5 to 15
Seniors (65+)
Disabled
Male
Female
Existing Distanced‐Based Job Accessibility (one‐mile) of 2012 Base Year by Different Population Groups
Entire Region
EJA
DGA
COC
0.16% 0.15% 0.14%
0.09% 0.09% 0.08%
0.05% 0.05% 0.05%0.05% 0.04% 0.04%
Poverty 1* Poverty 2* Poverty 3*
Existing Distanced‐Based Job Accessibility (one‐mile) of 2012 Base Year by Different Household
Poverty Levels
Entire Region
EJA
DGA
COC
0.16%0.14% 0.14% 0.13% 0.14%
0.09%0.08% 0.08% 0.07% 0.07%
0.05% 0.05% 0.04% 0.04% 0.04%0.04% 0.03% 0.03%
0.02% 0.01%
HHQuintile 1
HHQuintile 2
HHQuintile 3
HHQuintile 4
HHQuintile 5
Existing Distanced‐Based Job Accessibility (one‐mile) of 2012 Base Year by Different Household
Income Quintiles
Entire Region
EJA
DGA
COC
Results (Cont.)
Conclusions
Significantly efficient and effective in processing job accessibility analysis with ModelBuilder and SAS script in lights of data management and visualization
ModelBuilder in ArcGIS
Automatically perform spatial analysis to proportionally calculate job availability within one mile from TAZ’s centroid
SAS Script
Automatically calculate and summarize Weighted Average Job Accessibility within One Mile Distance (Measured as the Percent of Regional Employment Accessible for Each Cohort)
Future Studies
Integrate both ModelBuilder and SAS script into Python environment to fully automate job accessibility calculation Elevate this application to ArcGIS Online
to calculate and visualize data on the fly Statistical analysis to explore the
relationship between job accessibility, built environment, and EJ variables Explore other methods to improve
distance-based job accessibility calculation
Thank you!Tom Vo
Southern California Association of Governments
Division of Land Use and Environmental Planning
Department of Research and Analysis