Equity in Accessibility

Page 1

Assessing job accessibility of essential workers in Atlanta, GA Cumulative Opportunity Model

Jobs per CBG Population

Q1

Q2

Q4

Miles

0

2

Q2

Q3 Q4 Q5

Hot Spot - 99% Confidence Hot Spot - 95% Confidence

Essential Job Kernel Density

Hot Spot - 90% Confidence Not Significant

0

CCUMR60

0.15

0.50

1.00

0.95

0.91

0.64

0.75

0.50

KCUMR60

0.13

0.57

0.95

1.00

0.90

0.70

CPOWER1_0

0.77

0.69

0.91

0.90

1.00

0.86

KPOWER1_0

0.05

0.67

0.64

0.70

0.86

1.00

0.25

0.00

1 - 610

611 - 1,221

Coefficient Value = .13

1,222 - 3,052

3,053 - 155,673

Miles

0

2

4

Coefficient Value = .05 40000

250000

35000

200000

Quartile 1

Quartile 2

30000

150000

100000

50000

0 0

Quartile 3

50000

100000

150000

200000

250000

Median Household Median Household IncomeIncome

25000 20000 15000 10000

5000 0 0

Quartile 4

50000

100000

150000

200000

250000

Median Household Median Household IncomeIncome

Quartile 5

Q5

0.67

250000

Q4

0.69

200000

Coefficient Value = -.01

Accessibility Score

0.57

150000

Coefficient Value = .08

Q3

0.50

100000

Median Household Median Household Income Income

(1 mile from centroid)

Accessibility Score

1.00

50000

Straight-Line Distance

Q2

-0.01

0

Coefficient Value = .15

Q1

JobsPerPerson

250000

Accessibility Score

0.05

200000

Median Household Median Household IncomeIncome

Accessibility Score

0.77

150000

Kernel Density

0.13

100000

4

STRAIGHT-LINE DISTANCE

The cumulative opportunity models in both aggregation techniques had stronger correlations with income than the gravity models, but were still extremely weak (r2=.15 for fishnet and r2=.13 for kernel density). 0.15

50000

3,053 - 155,673

The gravity model accessibility scores had no significant correlation with income for the fishnet aggregation (r2= .08) or the kernel density aggregation (r2=.05).

-0.01

0

1,222 - 3,052

Q1

1.00

0

0

611 - 1,221

The correlation between cumulative opportunity accessibility scores and gravity scores have an extremely strong correlation (r2=.91) for the fishnet aggregation and a strong correlation for kernel density aggregation (r2=.70).

Income

500

10000

Not Significant

Jobs per CBG Population

1.00

1000

Hot Spot - 90% Confidence

We identified job locations of essential jobs according to CDC definition. The jobs were aggregated to zones identified through two aggregation techniques: a fishnet determined through the average nearest neighbor and census block groups. The opportunity of each zone was determined by the number of jobs in each zone for the fishnet and the average kernel density for each census block group. The centroids of fishnets and the census block groups were used as destinations.

FINDINGS

1500

Hot Spot - 95% Confidence

1 - 610

With GTFS data, we created a public transportation network based on travel time.Using Higgins (2019) accessibility toolbox, the accessibility scores from each census block group centroids to job locations were calculated using cumulative opportunity models and gravity models.

20000

2000

Hot Spot - 99% Confidence

0

METHODS

30000

(Getis Ord GI*)

Q5

How can we assess the spatial access of essential jobs for Atlanta residents by income using public transportation?

40000

Essential Job Clusters

Q3

RESEARCH QUESTIONS

2500

50000

Accessibility Score

STRAIGHT-LINE DISTANCE

60000

Accessibility Score

GA

Inverse Power, α=1.0

3000

Accessibility Score

RAIGHT-LINE DISTANCE

Atlanta

Aggregation

Public transit is important for marginalized groups in Atlanta as 75% of public transit riders are low-income, and 70% of riders are Black. Compounded with traffic congestion, rising housing prices, and the economic recession from the pandemic, understanding people’s access to jobs is important. Even with the pandemic, many low-income residents still have to commute to work as their jobs are considered essential and can only be done in person.

bs per CBG Population

BACKGROUND

Gravity Model

Travel Time = 60 min

Accessibility Score

EQUITY IN ACCESSIBILITY

Tamim Abedin Moses Levich Soyeon Kim Advanced Spatial Analysis Spring 2021 Columbia GSAPP.

Miles

0

2

4


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