Tokyo's streets reveal hidden gaps in urban inclusion and quality

Tokyo's streets reveal hidden gaps in urban inclusion and quality Swati Mestri Scientific Editor Andrew Zinin Chief Editor Citywide measures of urban sustainability can conceal sharp differences between neighborhoods. A city may appear to provide good streets overall while some areas lack greenery, openness or pedestrian-friendly space where diverse populations live. For Sustainable Development Goal 11 (SDG 11), which calls for inclusive, safe, resilient and sustainable cities, averages alone may miss where everyday street environments fail to keep pace with local needs. Addressing this challenge, a research team led by professor Xuepeng Qian from the Graduate School of Global Environmental Studies, Sophia University, Japan, along with associate professor Liang Dong from the Department of Public and International Affairs, City University of Hong Kong, China, compared street-space quality (SQ) with an inclusion-relevant sociodemographic composition proxy (SI) across Tokyo. The team also included Shujie Sun and Jiushuai Zhao from Sophia University; Yujin Huang and Jinming Yan from Renmin University of China; Hanwei Liang from Nanjing University of Information Science & Technology; Chenyang Wang from Xi'an Jiaotong University; and Jian Zuo from Adelaide University. Using street-view imagery and small-area demographic statistics, they mapped both dimensions on a 100 m × 100 m (328 feet × 328 feet) grid and examined spatial mismatch from 2015 to 2024. SI reflects population composition across dimensions including age, gender, nativity, occupation, household characteristics and residential duration; it is not a direct measure of realized inclusion. Their findings were published in npj Urban Sustainability. The analysis found that Tokyo's average SQ changed little over the study period, masking contrasting shifts in individual features. Street vitality and some pedestrian and street-interface indicators improved, while greenery, sky view, openness and nonvehicle interference stagnated or declined. The researchers identified areas where inclusion-relevant population composition outpaced street-space provision (SI ≫ SQ), and places where street-space quality was comparatively strong relative to population diversity (SI ≪ SQ). The first mismatch expanded toward eastern and bayside Tokyo, revealing local gaps hidden by citywide averages. "Urban sustainability should not be judged by citywide averages alone," Qian said. "Comparing population composition with the street environment at a fine spatial scale can reveal where these dimensions are not keeping pace with each other." The study offers a diagnostic for identifying where planning priorities may need to differ, rather than treating every neighborhood as if it faced the same challenges. Local governments could use these maps to prioritize place-specific measures. Where SQ lags SI, actions could include improving walkability, adding street greenery, making public spaces more accessible and strengthening transportation and public services. Where SQ is relatively high but SI is low, policy may instead focus on social integration, employment, housing and service access rather than physical upgrades alone. The mismatch indicator could inform urban renewal, budget allocation and local SDG 11 monitoring, helping officials coordinate transportation, land use, public space and social-service planning. "Regularly updating this diagnostic could help local authorities identify priority areas earlier and coordinate investment across departments," Qian said. The authors emphasize that the analysis describes spatial patterns and policy context; it does not establish that particular policies caused the observed changes. Future work could combine more frequent imagery and demographic data with residents' perceptions and behavior and use quasi-experimental methods to test which interventions reduce mismatches. Applying the framework in other cities would require suitable local data, calibration and validation. Overall, the study presents a street-scale way to make hidden inequalities in urban environments more visible and translate SDG 11 into place-specific governance priorities. Its central message is that population composition and street-space provision should be assessed together, while recognizing that SI is a proxy rather than a direct measure of lived inclusion. More information Shujie Sun et al., Street view diagnostics of inclusion and street quality gaps to guide governance in Tokyo, npj Urban Sustainability (2026). DOI: 10.1038/s42949-026-00412-2 Provided by Sophia University