Can transit-oriented development (TOD) cool the city? A multi-scale geospatial assessment of daytime surface heat exposure in Tokyo

● Links transit oriented development patterns to land surface temperature in Shinjuku ● Uses street view imagery, remote sensing and population data in one framework ● Shows well designed transit corridors can cool land surface by about 0.9°C ● Reveals that excessive density without greenery and shading increases urban heat ● Applies explainable machine learning to guide climate sensitive station area design Extreme heat is an escalating urban health and equity risk. Transit-oriented development (TOD) is widely promoted for low-carbon mobility, yet its thermal effects remain contested: densification may intensify midday surface heat exposure, whereas corridor design and streetscape morphology may mitigate it. Using Shinjuku Ward, Tokyo, we integrate summer daytime Landsat Collection 2 Level-2 land surface temperature (LST) with multimodal urban-form indicators derived from street-view semantics, OpenStreetMap kernel densities, building footprints, and fine-scale population (n = 12,562 street points). An XGBoost model learns a nonlinear mapping to Landsat-referenced LST and is interpreted with SHAP and one- and two-dimensional partial dependence plots. The model explains 92.1% of observed LST variance (R² = 0.921) and reveals strong non-additive interactions: higher railway-station intensity is associated with lower model-estimated LST only when paired with high railway-line density, indicating a corridor-node synergy rather than a station-only effect. Across the Railways × Railway Stations interaction surface, the model-predicted LST range spans approximately 1.4°C within the Landsat-referenced temperature space, demonstrating substantial contrasts among TOD configurations without comparing independent temperature products. Additional interaction surfaces suggest nonlinear thresholds involving building intensity, road configuration, and streetscape sky-tree composition. We discuss limitations of daytime LST as a proxy for pedestrian thermal comfort and outline transferability to other cities by adapting locally available mobility and morphology indicators.

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Publication Details

Journal
Sustainable Cities and Society
Published
2026-03-21
DOI
https://doi.org/10.1016/j.scs.2026.107318
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
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article

Can transit-oriented development (TOD) cool the city? A multi-scale geospatial assessment of daytime surface heat exposure in Tokyo

Zhewei Liu, Jingxue Xie, Jue Wang
Sustainable Cities and Society
Urban Heat Island Mitigation
article

Can transit-oriented development (TOD) cool the city? A multi-scale geospatial assessment of daytime surface heat exposure in Tokyo

Zhewei Liu, Jingxue Xie, Jue Wang
article en

Abstract

● Links transit oriented development patterns to land surface temperature in Shinjuku ● Uses street view imagery, remote sensing and population data in one framework ● Shows well designed transit corridors can cool land surface by about 0.9°C ● Reveals that excessive density without greenery and shading increases urban heat ● Applies explainable machine learning to guide climate sensitive station area design Extreme heat is an escalating urban health and equity risk. Transit-oriented development (TOD) is widely promoted for low-carbon mobility, yet its thermal effects remain contested: densification may intensify midday surface heat exposure, whereas corridor design and streetscape morphology may mitigate it. Using Shinjuku Ward, Tokyo, we integrate summer daytime Landsat Collection 2 Level-2 land surface temperature (LST) with multimodal urban-form indicators derived from street-view semantics, OpenStreetMap kernel densities, building footprints, and fine-scale population (n = 12,562 street points). An XGBoost model learns a nonlinear mapping to Landsat-referenced LST and is interpreted with SHAP and one- and two-dimensional partial dependence plots. The model explains 92.1% of observed LST variance (R² = 0.921) and reveals strong non-additive interactions: higher railway-station intensity is associated with lower model-estimated LST only when paired with high railway-line density, indicating a corridor-node synergy rather than a station-only effect. Across the Railways × Railway Stations interaction surface, the model-predicted LST range spans approximately 1.4°C within the Landsat-referenced temperature space, demonstrating substantial contrasts among TOD configurations without comparing independent temperature products. Additional interaction surfaces suggest nonlinear thresholds involving building intensity, road configuration, and streetscape sky-tree composition. We discuss limitations of daytime LST as a proxy for pedestrian thermal comfort and outline transferability to other cities by adapting locally available mobility and morphology indicators.

Sustainable Cities and SocietyVol. 142
University of Toronto (CA), University College London (GB), Tokyo University of Agriculture and Technology (JP)
Sustainable cities and communities
Openalex Percentile: Top 14%
Urban Heat Island Mitigation
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