Unlocking Smart Growth: The Effects of a Proposed Transit-Oriented Development Law on the Puget Sound Region

Tiernan Martin; Alex Brennan

Abstract

During the 2024 legislative session in Washington State, members of the House of Representatives introduced House Bill 2160, aiming to promote community and transit-oriented housing development. The bill would have required cities to allow developments of a specified scale within defined distances from high-capacity transit stops. This study assesses how the proposed increases in development capacity by the bill compare to existing allowances. The results show that while the typical developable station area parcel already permits more development capacity than HB 2160 would have, a significant amount of land would be affected by the bill. Specifically, for developable land currently zoned for a lower development capacity than the bill’s requirements, the estimated average capacity change would be an additional 1.79 floor area ratio (FAR). If adopted, this bill could have increased the development capacity of land near the region’s public transit network by as much as 1.8 billion square feet.

About Futurewise

Futurewise is a nonprofit organization that works throughout Washington State on the implementation of the Growth Management Act (GMA). We partner with local communities to support land use policies that encourage healthy, equitable and opportunity-rich communities, and that protect our most valuable farmlands, forests and water resources. We have members across the state including the central Puget Sound region. For more information about our organization, visit our website at https://futurewise.org/.

Acknowledgments

The authors wish to express their gratitude for the support received during the preparation of this article.

No financial assistance was provided for the research, authorship, or publication of this work.

Thanks to Yonah Freemark of the Urban Institute for the provision of zoning district data. Thanks to Lauren Engel, Carol Naito, and Robin Koskey from the Puget Sound Regional Council for their generosity in sharing the agency’s public transit data and for their analysis of Washington State House Bill 2160. We are grateful to Noha Mahgoub from the Office of Governor Jay Inslee for her valuable feedback and guidance. Additionally, our thanks to Dan Bertolet of the Sightline Institute for his review and feedback on our manuscript.

1 Introduction

An aerial photo of Mercer Island, Seattle, and Kitsap County — Central Puget Sound | Photo courtesy of Clemens Vasters from Viersen, Germany, CC BY 2.0, via Wikimedia Commons

1.1 Growth in the Central Puget Sound Region

The Puget Sound metropolitan region is one of North America’s major growth centers for people, jobs, and housing. Between 2010 and 2023, the central Puget Sound’s four-county region (King, Kitsap, Pierce, and Snohomish counties) added more residents and housing units than the rest of Washington state combined.¹ According to forecasts by the Puget Sound Regional Council, the region’s population is expected to grow to 5.8 million people living within 2.8 million households by 2050 (Puget Sound Regional Council 2018).

As the region grows, it faces challenges that come with that growth. One such challenge is high, rising housing costs. The Puget Sound Regional Council’s Housing Stability Strategy: 2023 Monitoring Report provides several sobering statistics about the region’s housing costs. According to the report, during the decade between 2010 and 2020, the region added only one housing unit for every three new people that were born or moved there. Between July 2015 and July 2023, the median rent cost increased by 50%² and the annual income required to purchase the area’s median priced home was $160,000 (Puget Sound Regional Council 2023c). In 2020, an estimated 11,751 people experienced homelessness within King County alone—a 5% increase from the county’s 2019 estimate (All Home 2020). Despite the efforts by both public and private housing developers to tackle the shortage of affordable housing, researchers estimate that the central Puget Sound region will experience a shortfall of approximately 140,000 units over the next 20 years (Freemark et al. 2023).

Another challenge that the region faces is climate change. In 2009, the Climate Impacts Group at the University of Washington developed a climate model that projected several series climate-related impacts over the coming decades. Those impacts include water shortages in the Yakima Basin, loss of salmon habitat due to elevated stream temperatures, increased wildfire risk, and more human deaths caused by heat events and poor air quality (Climate Impacts Group 2009).

1.2 Transit-Oriented Development

One potential solution to the Puget Sound region’s challenges is to concentrate urban growth in existing urban areas while investing in climate-friendly forms of transportation. During the 1980s, sharp increases in sprawling, low-density residential and commercial development in Washington State resulted in many unintended consequences, including ecological disruption, traffic congestion, urban disinvestment, and loss of agricultural lands (Trohimovich 2002). This led the Washington State Legislature to adopt the Growth Management Act (GMA), a law requiring cities and counties to plan to accommodate growth within designated areas (urban growth areas or UGAs). Many of the GMA’s planning goals align with a transit-oriented development (TOD) strategy to accommodating population growth within existing urban places.³

The region’s metropolitan planning organization, the Puget Sound Regional Council (PSRC), incorporates TOD into its regional growth strategy. VISION 2050 defines regional growth centers—the places where most of the region’s growth should occur—as compact, walkable, mixed use communities centered around high-quality transit systems. This plan also adopts greenhouse gas emission reduction goals set by the Puget Sound Clean Air Agency, including reducing greenhouse to 50% below 1990 levels by 2030 and to80% below 1990 levels by 2050. PSRC lists multiple strategies for achieving these goals, including the reduction of vehicle miles traveled by planning for transit-oriented development (Puget Sound Regional Council 2023a, 2022).

1.3 House Bill 2160

House Bill 2160 (HB 2160) of the 2023-2024 Washington State Legislative Session proposed changes to the GMA intended to promote community and transit-oriented housing development.⁴ These changes, which would apply to all cities planning under the GMA, included the following:

Prohibiting cities from preventing the siting of multifamily housing on residential land within transit station areas
Prohibiting cities from enacting maximum floor area ratio (FAR) regulation under the following thresholds: 3.5 FAR for station areas of light rail, commuter rail, or streetcars; 2.5 FAR for station areas of bus rapid transit
Categorically exempting residential or mixed-use projects within station areas from the State Environmental Policy Act (SEPA)

The bill also proposed several requirements of residential development built within station areas, including making at least 10% of its residential units affordable.⁵

HB 2160 defines the floor area ratio (FAR) as “a measure of development intensity equal to the building square footage divided by the developable property square footage” (Reed 2024). This metric merges two commonly used regulatory tools—maximum building height and maximum lot coverage—into a single ratio. It offers developers design flexibility and allows local governments to establish a maximum level of development intensity within a zoning district. Refer to Figure 1 for an illustration of how this tool permits various development configurations while ensuring a consistent amount of building floor area.

A diagram showing different ways that a development could arrange 1.0 FAR on a lot: 1 story, 2 stories, 3 stories — Figure 1: Illustrations of FAR Limits | Source: *Accessory Dwelling Unit Final EIS*, City of Seattle, 2018

1.4 Research Questions

The purpose of this study is to provide information about the effects of the proposed HB 2160. Specifically, we seek to answer the following questions:

What are the characteristics of the current land uses of the transit station areas as defined in the bill?
Would this bill have an effect on the allowed development capacity of transit station areas?
What is the size of any effect this bill may have?
How are the bill’s effects distributed between the two station area types that it defines?
What patterns are present in the cities that would be significantly impacted by the bill?

2 Data & Methods

2.1 Approach

We employ a quantitative methodology to address our research questions. First we evaluate the impact of House Bill 2160 across the entire study area, specifically the central Puget Sound region, and then proceed to analyze several individual cities as case studies.

2.2 Methods

HB 2160 would increase community and housing development capacity by requiring cities to adopt maximum FAR requirements no more restrictive than those specified in the bill. While some cities use maximum FAR to regulate development, many cities use other measures, the most common of which is a combination of maximum building height and maximum lot coverage. In order to accurately compare development capacity across the study area, we create a standardized measurement of development capacity which we define as follows:

\[ \text{SDC}_i = \begin{cases} \text{FAR}_i & \text{if parcel } i \text{ uses FAR} \\ (\text{MBF}_i \times \text{MLC%}_i) & \text{if parcel } i \text{ does not use FAR} \end{cases} \tag{1}\]

Where:

$\text{SDC}_i$: Standardized Development Capacity for parcel $i$
$\text{FAR}_i$: Floor Area Ratio for parcel $i$
$\text{MBF}_i$: Maximum Building Floors for parcel $i$
$\text{MLC%}_i$: Maximum Lot Coverage Percentage for parcel $i$

We use net development capacity (${NDC}$) to represent the effect of the bill on development capacity at the scale of individual tax parcels. We define ${NDC}$ as follows:

\[ NDC_i = SDC_{new,i} - SDC_{old,i} \tag{2}\] Where:

$SDC_{old,i}$: parcel $i$’s current (standarized) maximum development capacity.
$SDC_{new,i}$: the (standardized) maximum development capacity that would apply to parcel $i$ if HB 2160 became law.

To quantify the impact of the proposed bill on a geographic scale larger than an individual parcel, we employ two metrics: an absolute metric, the total net development capacity ($T_{NDC}$), and a relative metric, the area-weighted mean of net development capacity ($AWM_{NDC}$).

Total Net Development Capacity ($T_{NDC}$)

The total net development capacity ($T_{NDC}$) is calculated as the sum of the net development capacity for each parcel, adjusted by the parcel’s area and eligibility based on specific criteria. We define it as follows:

\[ T_{NDC} = \sum_{i}(NDC_i \cdot A_i \cdot I_i) \]

Where:

$NDC_i$: the net development capacity for parcel $i$.
$A_i$: the geometric area of parcel $i$.
$I_i$: an indicator function that equals 1 if parcel $i$ satisfies all of the following conditions: it is within a station area, it lies within a zoning district where residential use is permitted, and it is within an urban growth area; otherwise, $I_i$ equals 0.

This formula ensures that only parcels meeting all specified conditions contribute to the total net development capacity. The indicator function ($I_i$) serves as a filter, excluding parcels not suited for development under the proposed bill’s guidelines.

Area-Weighted Mean of Net Development Capacity ($AWM_{NDC}$)

To calculate the mean net development capacity, weighted by the proportion of the area that each parcel occupies within the eligible region, we use the following formula:

\[ AWM_{NDC} = \frac{\sum_{i}(NDC_i \cdot A_i \cdot I_i)}{\sum_{i}(A_i \cdot I_i)} \tag{3}\]

This calculation divides the sum of the net development capacity of each parcel, adjusted by its area and eligibility, by the total eligible area. This method results in a weighted mean that reflects the proportional impact of each parcel, with larger parcels having a greater influence on the overall metric.

In a region where cities employ various tools to regulate development intensity, our method introduces two metrics for assessing changes in development capacity, irrespective of the regulatory tool in use. It also enables us to summarize the bill’s effect at different geographic levels, including station areas, cities, and regions. This approach allows us to describe individual geographies (for example, a specific station area) and to compare them with one another (for example, several cities in comparison to the region as a whole).

2.3 Data Collection

The study uses several data sets from a variety of different sources. The following table summarize the study’s data:

Data	Description	Citation
Current Parcels (2023)	A statewide data set of tax parcels	Washington State Parcels Project (2023)
Transit Stations	Transit station locations for light rail, commuter rail, streetcar, and existing bus rapid transit routes in the central Puget Sound Region	Puget Sound Regional Council (2024)
Puget Sound Zoning Districts (2023)	Zoning and land use regulations collected from central Puget Sound local governments’ land use codes and maps	Urban Institute (2023)
Urban Growth Areas	Urban growth areas for the central Puget Sound region (King, Snohomish, Kitsap, and Pierce counties)	Puget Sound Regional Council (2023b)
City Boundaries	Boundaries of city jurisdictions with the central Puget Sound region	Puget Sound Regional Council (2023b)

2.4 Data Analysis

The study uses a combination of a relational database and statistical software to conduct its analysis. The relational database, PostgreSQL with the PostGIS extension, is used to perform spatial filters and spatial joins on the Current Parcel data set. The R programming language is used to perform aggregations and calculate summary statistics on the filtered and augmented parcel data set. R is also also used to produce summary tables and visualizations. Construction of the study data set and analysis of its data are coordinated using the targets pipeline tool (see Landau (2021)).

Data sets containing information relevant to HB 2160 are combined through spatial filtering and spatial joining to produce a data set of all parcels within the station areas. The refined parcel data are augmented with zoning and land use regulation information from the zoning districts. A maximum FAR baseline is estimated for all parcels, then the new maximum FAR that would be introduced by HB 2160 is estimated. For each parcel, the net difference between the current (old) and new FAR is calculated. For parcels where the current zoning allows development greater than the new FAR, the effect of the bill is considered to be zero additional FAR; for parcels where the current zoning is more restrictive that the new FAR, the effect is calculated in terms of additional FAR allowed. The bill’s effect on each parcel is then aggregated by station area, jurisdiction, and region, and summarized using the area-weight mean.⁶

2.5 Limitations

Our method is subject to several limitations that are important to consider when interpreting our findings:

Changing Development Regulations: The study uses zoning and land use data collected in 2023. While Puget Sound jurisdictions will be required to update their development regulations to comply with recent changes to the GMA by mid-2025, the study focuses on current development regulations.
FAR Averaging: While this study assumes that the bill’s maximum FAR standards would be uniformly applied across all eligible parcels in every station area, the Second Substitute House Bill 2160 language would allow the new FAR to be calculated as an average of the station area. Additional implementation details would be needed to accurately assess the impact that this flexibility would have on the bill’s effect.
Additional Restrictions on Development: The analysis does not account for other significant restrictions, including those that prevent development from being sited within critical areas, shoreline environments, or on sites with landmark designations. Such restrictions can materially impact development possibilities but are not reflected in the study.⁷
Measurement of Transit Proximity: Transit walksheds are calculated using Euclidean distance, measuring straight lines to the center of parcels, rather than using network distances that reflect actual walking paths. This method may overestimate or underestimate the true accessibility of parcels to transit services.
Lot Coverage Assumptions: In cases where specific regulations on maximum building footprint or FAR are not provided, the study assumes that 100% lot coverage is permissible. This assumption may not align with actual zoning regulations, potentially leading to over-estimations of development capacity.
Omission of Other Development Regulations: The estimated FAR metric does not incorporate other development regulations, such as setbacks, which can significantly impact the buildable area on a parcel.
Homeowner Association (HOA) Restrictions: The analysis does not consider HOA restrictions that might limit allowed density on parcels, which could reduce the impact of bill in station areas where restrictive HOA’s exist.

Further research, data collection, and methodological refinements could help address these limitations in future analyses.

3 Results

3.1 Entire Study Area

The study includes approximately 116,600 tax parcels ($n = 116,635$), all within the four central Puget Sound counties, within an Urban Growth Area, and within HB 2160’s specified distance thresholds of a qualifying transit stop.

We separate the study data into three analysis groups:

Not Developable (${i | I_i = 0}$)
Parcels ineligible under HB 2160 criteria. This study applies the HB 2160 criteria by selecting parcels that: a) are located within cities and within a UGA; b) are located in zoning districts permitting residential uses; and c) have current land uses that are suitable for transit-oriented development. To evaluate current land use, we use tax assessor-assigned land use codes to exclude properties with incompatible uses. HB 2160 specifies incompatible uses as streets, roads, highways, sidewalks, lighting systems for streets and roads, traffic signals, domestic water systems, storm and sanitary sewer systems, parks and recreational facilities, and schools (Reed 2024). Although HB 2160 exempts parcels governed by shoreline master programs or critical area ordinances, this study does not exclude these lots due to the lack of comprehensive regional data sets with the required information.
Developable (${i | I_i = 1}$)
Parcels that meet 2160’s eligibility criteria. Within Developable parcels, we distinguish the following two subsets:
1. Developable, Not Affected ($\{i | I_i = 1 \text{ and } NDC_i \leq 0\}$)
  Parcels that meet the eligibility criteria and have a standardized development capacity equal or greater than the minimum required by HB 2160 and would, therefore, not be affected by the bill.
2. Developable, Affected ($\{i | I_i = 1 \text{ and } NDC_i \gt 0\}$)
  Parcels that meet the eligibility criteria and have a standardized development capacity less than the minimum required by HB 2160 and would, therefore, be affected by the bill.

We also divide the parcel data by the type of station area it is within:

Large (0.5 Mile)
Parcels within a half mile of a light rail station, commuter rail station, or streetcar stop.
Small (0.25 Mile)
Parcels within a quarter mile of a bus rapid transit stop and not within a Large station area

Using HB 2160’s definition of station areas, we create two station area types and assign one type to every parcel. Parcels that are within both Large and Small station area types as classified as part of a Large station area.⁸

Our study focuses primarily on the third analysis group, Developable, Affected, which make up the majority of the station area parcels (77.2%) but constitute only 47% of the total land area. We find that the total amount of additional development capacity that would be added by HB 2160 to be approximately 1.83 billion ft².⁹

Our findings suggest that the Large (0.5 mile) station areas would account for the majority of the parcels (64.7%), land area (60%), and added development capacity (67%) associated with HB 2160. See Table 1 below.

Table 1: Summary of Study Data

	Parcels (n)	Land Area (mi²)	Added Dev. Capacity (ft²)	AWM_NDC
All Station Area Parcels	116,635	79	1.83B	-0.67
Analysis Groups
Developable, Affected	90,042 (77.2%)	37.1 (47%)	1.83B (100%)	1.77
Developable, Not Affected	18,510 (15.9%)	20.2 (26%)	--	-5.14
Not Developable	8,083 (6.9%)	21.4 (27%)	--	--
Station Area Types
Large (0.5 Mile)	75,416 (64.7%)	47.6 (60%)	1.23B (67%)	-0.96
Small (0.25 Mile)	41,219 (35.3%)	31.1 (40%)	600.04M (33%)	-0.27

	Population, Housing, & Land			Transit Station Areas
	Population	Housing Units	Land Area (mi²)	LR	CR	SC	BRT
Kent	135,169	48,322	34	2	2	0	15
Mercer Island	25,464	10,514	13	1	0	0	0
Redmond	73,728	31,762	17	4	0	0	30
Shoreline	58,673	23,505	12	2	0	0	31
Sources: American Community Survey, 2022 ACS 5-Year Estimates; authors' analysis of transit stop data from Puget Sound Regional Council 2024

	Parcels (n)	Land Area (mi²)
Kent
Developable, Affected	1,165 (68%)	0.91 (53%)
Developable, Not Affected	119 (7%)	0.2 (12%)
Not Developable	441 (26%)	0.61 (35%)
Mercer Island
Developable, Affected	548 (87%)	0.31 (62%)
Developable, Not Affected	68 (11%)	0.09 (18%)
Not Developable	13 (2%)	0.1 (20%)
Redmond
Developable, Affected	1,303 (88%)	1.95 (70%)
Developable, Not Affected	31 (2%)	0.26 (9%)
Not Developable	149 (10%)	0.56 (20%)
Shoreline
Developable, Affected	3,621 (76%)	1.2 (57%)
Developable, Not Affected	1,122 (23%)	0.66 (32%)
Not Developable	45 (1%)	0.23 (11%)

	Parcels (n)	Land Area (mi²)	AWM_NDC	Net Dev. Capacity (ft²)
Single-Family	805	0.39	2.11	22.7M
Commercial Manufacturing	109	0.19	1.69	8.83M
Residential Agricultural	10	0.11	2.70	8.04M
General Commercial	81	0.10	2.70	7.70M
Medium Density Multifamily Residential	23	0.05	1.63	2.26M

	Parcels (n)	Land Area (mi²)	AWM_NDC	Net Dev. Capacity (ft²)
Single-Family	490	0.26	3.10	22.2M
Multiple-Family	58	0.05	2.46	3.33M
Town Center	68	0.09	−0.50	0

About Futurewise

Acknowledgments

1 Introduction

1.1 Growth in the Central Puget Sound Region

1.2 Transit-Oriented Development

1.3 House Bill 2160

1.4 Research Questions

2 Data & Methods

2.1 Approach

2.2 Methods

Total Net Development Capacity (\(T_{NDC}\))

Area-Weighted Mean of Net Development Capacity (\(AWM_{NDC}\))

2.3 Data Collection

2.4 Data Analysis

2.5 Limitations

3 Results

3.1 Entire Study Area

3.2 Case Studies

3.2.1 Kent

3.2.2 Mercer Island

3.2.3 Redmond

3.2.4 Shoreline

4 Conclusion

References

Appendices

4.1 Case Study Tables & Maps

4.1.1 Kent

4.1.2 Redmond

4.1.3 Shoreline

Footnotes

Citation