How Did Metro Boston Grow?2000-2010

11.521 – Spatial Database Management and Advanced GISFinal Presentation

Group Members: Amy Jacobi, Eric Schultheis, Nse Umoh, Rob Goodspeed, Samira Thomas

Prof. Joseph Ferreira

Presentation Outline

• Project Goals• Process• Methodology• Results• Conclusions

PROJECT GOALS

Project Goals

• Evaluate growth patterns in the metro-Boston between 2000 and 2010.

• Compare observed growth in the last decade with the MetroFuture scenarios: Let It Be and Winds of Change.

• Understand the effect of observed growth on greenhouse gas emissions by private vehicles.

PROCESS

Process Map

Land Use Polygons

(1999 & 2005)

Census Block Populations

‘Non-Residential’ Block Finder

Allocation ModelAllocation to 250m Grid

MetroFuture Scenarios (TAZs)

Results

Allocation to TAZ

Allocation to Residential Areas

Allocation to Sensible GeographiesInput Data Evaluating

Growth in metro-BostonAllocation to 25m

Grid

Geop

roce

ssin

g

VMT(205m Grid)

METHODOLOGY

Conflicting Topographies: An Example Area

Conflicting Topographies

Conflicting Topographies

The Grid(s)

Resolving Conflicts with the Grid (25m)

Allocation to Residential Areas

• Identify residential and institutional land uses.• Identify blocks that do not intersect residential land use

areas.• Land use allocation

– Sliver Finder• Integrate Census Blocks (2000, 2010) and residential land uses• Calculate areas, perimeter, and area/perimeter ratio• Eliminate features with areas less than 400 sqm and area/perimeter

ratio less than 1

– Population/housing unit allocation model (Access)• Paloc= P * (A + L) / 2• A = land use area % of total area of Block, L = land use area %

of residential area in Block

Model to Identify Block that do not Intersect with Residential Areas

Model to Allocate to Residential Areas

ArcGIS Models: Allocating to Residential Areas

Allocation to Residential Areas

• Merge allocated residential areas with ‘missed’ blocks forming an allocated areas polygon file.

• Calculate the number of 25m grid centroids that fall in each allocated areas polygon.

• Identify allocated areas polygons with no 25m grid centroids.

• Convert the allocated areas polygons to 25m grid celss.• Aggregate allocated 25m grid cells to 250m grid cells

(add in population missed by 25m grid method).• Aggregate allocated 25m grid cells to TAZs (add in

population missed by 25m grid method).

Allocation to Sensible Geographies

ArcGIS Models: Allocating to Sensible Geographies

Model to Merge Habitable Area and Populated Blocks with no Residential Area.

Model to Allocate to 25m Grid and then Aggregate to 250m Grid (due to resolution of 25m grid, metro-Boston area must be divided into 32

slivers and the model needs to be ran for each sliver )

Allocation to Sensible Geographies

Comparing 11.521 & MassGIS Allocations

Population Households

Census 2000 Census 2010 Census 2000 Census 2010

Regional Block Data From Census

4,317,333 4,465,821 1,708,415 1,830,499

Grid Cell Allocation

4,292,166 4,426,075 1,707,385 1,808,216

Percent Allocated

99.42% 99.11% 99.4% 98.78%

The Allocation: A Regional View

RESULTS

Inner Core Regional Urban Centers Maturing Suburbs Developing Suburbs850,000

950,000

1,050,000

1,150,000

1,250,000

1,350,000

1,450,000

1,550,000

2000 Population2010 PopulationMetrofuture Population 2030Let it Be Population 2030

Metro Boston Population by Community Type

Inner Core Regional Urban Centers Maturing Suburbs Developing Suburbs20%

22%

24%

26%

28%

30%

32%

2000 Population2010 PopulationMetrofuture Population 2030Let it Be Population 2030

Metro Boston Population Proportion by Community Type

Inner Core Regional Urban Centers Maturing Suburbs Developing Suburbs250,000

300,000

350,000

400,000

450,000

500,000

550,000

600,000

650,000

700,000

2000 Housing Units2010 Housing UnitsMetroFuture Housing Units 2030Let it Be Housing Units 2030

Metro Boston Housing Units By Community Type

Inner Core Regional Urban Centers Maturing Suburbs Developing Suburbs15%

17%

19%

21%

23%

25%

27%

29%

31%

33%

35%

2000 Housing Units

2010 Housing Units

MetroFuture Housing Units 2030

Let it Be Housing Units 2030

Metro Boston Housing Units Proportion, by Community Type

2010 MetroFuture 2030 Current Trends 2030

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

-0.7%

2.5%

-1.4%

0.7%

-2.5%

1.4%

Inside CODA

Outside CODA

Change in Proportion of Population in CODAs, since 2000

Population Change (Percent & Raw) by Town, since 2000

Housing Unit Change (Percent & Raw) by Town, since 2000

TAZ Population Change (Percent & Raw) for Sub-Areas, since 2000

TAZ Population Change (Percent & Raw) for Lincol et al., since 2000

TAZ Population Change (Percent & Raw) for Hopkington, since 2000

TAZ Population Change (Percent & Raw) for Boston, since 2000

TAZ Housiing Unit Change (Percent & Raw) for Sub-Areas, since 2000

TAZ Housiing Unit Change (Percent & Raw) for Quincy, since 2000

TAZ Housiing Unit Change (Percent & Raw) for Marlborough et al,, since 2000

Histogram of Average Household Vehicle Miles Traveled by Grid Cell

1,829 - 4,614

4,614 - 7,399

7,399 - 10,184

10,184 - 12,969

12,969 - 15,754

15,754 - 18,538

18,538 - 21,323

21,323 - 24,108

24,108 - 26,893

26,893 - 29,678

29,678 - 32,463

0

2000

4000

6000

8000

10000

12000

14000

16000

Average Vechile Miles Traveled per Household

freq

uenc

y

Average Household Vehicle Miles Traveled by Community Type

Community Type Average VMT per Household

Minimum VMT per Household

Maximum VMT per Household

Standard Deviation of VMT per Household

Inner Core 10131 1473 29678 2259

Maturing Suburbs 12100 1074 29948 2571

Regional Urban Centers 12224 1319 28937 2683

Developing Suburbs 13604 1262 29638 2734

Metro Future Region 12845 1074 29948 2827

Average Household Vehicle Miles Traveled by Community Type & CODA

Developing S

uburbs

Inner Core

Maturin

g Suburb

s

Regional

Urban Cen

ters

MetroFu

ture Reg

ion0

2000

4000

6000

8000

10000

12000

14000

16000

Non-CODACODATotal

Community Type

Aver

age

Hous

ehol

d VM

T

Average Household Vehicle Miles Traveled by CODA

TAZ TYPE Average VMT per Household

Minimum VMT per Household

Maximum VMT per Household

Standard Deviation of VMT per Household

Non-CODA 13255 1074 29448 2777CODA 11682 1301 29948 2638Metro Future Region

12845 1074 29948 2827

Population Change by CODA, since 2000

Growth by Average Household Vehicle Miles Traveled Area Type

Growth by Average Household Vehicle Miles Traveled Area Type

Very Low Low Medium High Very High0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.005.99 5.93

0.98 1.16

5.24

Average Household VMT

Addi

onal

Peo

ple

Growth by Average Household Vehicle Miles Traveled Area Type

VMT Type Average VMT per Household

% of Region (Area)

% of Regional Growth

Very Low <7000 1% 3%Low 7001-10,000 19% 53%Medium 10,001-13,000 48% 22%High 13,001-18,000 30% 17%Very High >18,000 2% 5%

The two lowest VMT categories (less than 10,000 miles per Household per year) , which accounted for 20% of the regions land, contained 56% of the region’s growth over the pat decade.

Greenfield development which occurred in 3% of the region’s area, contributed 44% of the population growth for the metro-Boston region. The average household VMT for these cells was over 1,000 miles higher than the average household VMT for the metro-Boston region (13,186 vs. 12,037).

CONCLUSIONS

Conclusions: Broadly Stated

• The region grew (both in terms of population and housing units) slower than expected under either scenario.

•There was strong growth in the regional urban centers, CODAs, and regional urban centers but this is, from a regional perspective, offset by dispersed growth in developing suburbs .

•Greenfield development occurred in only 3% of the metro-Region’s area.

The Good,

• Population growth in areas with low average household VMTs accounted for 56% of the growth in metro-Boston region since 2010.•There was substantial growth in Boston and regional urban centers.

The Bad,

• The percentage growth in developing suburbs is more consistent with Let It Be than Winds of change.•Greenfield development accounted for 44% of the metro-Boston region’s population growth.

The (Somewhat) Ugly.

• The largest percentage changes in population and housing unit are occurring in non-CODA and ‘undesirable’ community types.