91ÁÔÆæ

This interactive map visualizes the Bike Infrastructure Gap Index across the Bay Area's nine counties, using 40+ spatial and demographic indicators to identify where cycling investment is most needed. Developed by 91ÁÔÆæ researchers, it supports planners and policymakers in making equitable, data-driven decisions to advance multimodal mobility for underserved communities.

This interactive map scores over 66,000 transit station areas across California on affordability, built environment, and racial equity. Using a 0–100 index, it helps planners and policymakers identify where transit-oriented development is succeeding—and where investment is most needed to advance housing affordability and transportation justice.

This interactive map visualizes the location and sectoral typology of high-tech clusters across 52 large U.S. metropolitan regions. Using firm-level data and spatial statistics, it identifies 627 micro-scale tech zones classified by industry specialization — from professional services to R&D — helping planners target innovation-driven economic development strategies.

This interactive map visualizes broadband access disparities across California's 30th Assembly District, classifying census blocks as well-served, served, or unserved based on provider availability and download speeds. Overlaid with demographic and socioeconomic data, it reveals how low-income communities and students of color bear the greatest burden of digital inequity.

This interactive map displays Climate Policy Alignment Scores for 25 California cities across five MPO regions, measuring how well local Climate Action Plans align with regional Sustainable Communities Strategies under SB 375. Scores span transportation, land use, TDM, and cross-cutting strategies to identify where coordinated climate action is strongest.

As part of SPUR's 15-minute city projects, SAVI measured and mapped access and proximity (within one-half mile) to groceries, financial institutions, parks, community centers, childcare, and health facilities. They show that areas with high access to some services and amenities, say, financial institutions, can have low access to other services and amenities, in particular, groceries.

Yang, B., Liu, H., Kang, E., Shu, S., Xu, M., Wu, B., Beck, R., Hinkel, K., & Yu, B., (2021) 

Yang, B.; Hawthorne, T.L.; Hessing-Lewis, M.; Duffy, E.J.; Reshitnyk, L.Y.; Feinman, M.; Searson, H. (2020) 

Zandiatashbar, A., & Hamidi, S. (2022)

Zandiatashbar, A. (2021)

Rohrmeier, K. and Heher, J. (2021)

Albrecht, J., Petutschnig, A., Ramasubramanian, L., Resch, B., & Wright, A. (2021)

Petutschnig A, Albrecht J, Resch B, Ramasubramanian L, and A Wright (2022)

Hamerlinck, J. and Ramasubramanian, L. (2021)

Kovacs-Györi, A, Ristea, A, Havas, C, Mehaffy, M, Hochmair, H, Resch, B, Juhasz, L, Lehner, A, Ramasubramanian, L, and T Blaschke (2020)