How Did Metro Boston Grow? 2000-2010 11.521 – Spatial Database Management and Advanced GIS Final 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

Evaluating Growth in metro-Boston Process Map Allocation to Residential Areas Allocation to Sensible Geographies Evaluating Growth in metro-Boston Input Data Allocation to 25m Grid Land Use Polygons (1999 & 2005) ‘Non-Residential’ Block Finder Results Geoprocessing Allocation to 250m Grid Census Block Populations Allocation Model Allocation to TAZ VMT (205m Grid) MetroFuture Scenarios (TAZs)

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

ArcGIS Models: Allocating to Residential Areas Model to Identify Block that do not Intersect with Residential Areas Model to Allocate to Residential Areas

Allocation to Residential Areas

Allocation to Sensible Geographies 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).

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

The Allocation: A Regional View Population Households 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%

Results

Metro Boston Population by Community Type

Metro Boston Population Proportion by Community Type

Metro Boston Housing Units By Community Type

Metro Boston Housing Units Proportion, by Community Type

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

Average Household Vehicle Miles Traveled by 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 2827

Average Household Vehicle Miles Traveled by Community Type & CODA

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 2777 CODA 11682 1301 29948 2638 Metro Future Region 12845 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

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.