Work

Uncovering nonlinear threshold effects of urban morphology on carbon emissions: Toward optimal low-carbon urban spatial planning

Year: 2026

Type: article

Abstract: The transition toward urban carbon neutrality has intensified attention on the coupling mechanisms between urban spatial morphology and carbon emissions. However, existing studies are often constrained by single-scale analyses and linear assumptions, limiting their ability to capture nonlinear interactions among multiple morphological indicators and spatial heterogeneity. This study proposes an integrated spatiotemporal nonlinear regression (ISTNR) model that combines geographically weighted regression, ensemble machine learning, and game-theoretic feature attribution to enable high-dimensional modeling and threshold identification. Supported by multi-source remote sensing data, the model is applied to systematically analyze how the evolution of urban form influences carbon emissions across spatiotemporal scales in Japan. The results highlight significant regional heterogeneity and nonlinear interactions. In dense urban areas like Tokyo and Osaka, emissions are mainly driven by compactness, while in sparsely populated regions such as Hokkaido, shape complexity and fragmentation dominate. Spatial connectivity shows asymmetric effects across regions. Key thresholds are identified: emissions increase rapidly when urban area exceeds 60,000 hectares or connectivity surpasses 0.85. Conversely, mitigation potential is highest when adjacent urban land comprises 55–70% and population density ranges between 0.004–0.007 persons/m². Strong interaction effects are also observed—for instance, the amplification of emissions when total urban area and spatial connectivity rise simultaneously, and the reversal in the influence of landscape mesh complexity and land aggregation depending on spatial scale. This study establishes a flexible and interpretable nonlinear modeling framework, offering a novel methodological basis for identifying optimal morphological zones and guiding low-carbon spatial planning.

Source: Cities

DOI: 10.1016/j.cities.2026.106831

Authors: Lei Li, Shujie Sun, Zijie Pang, Liang Dong, Ji Han, Xuepeng Qian

Institutions: Sophia University, Xinjiang University, City University of Hong Kong, Ritsumeikan Asia Pacific University

Language: English

Topic: Urban Design and Spatial Analysis

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Climate action

Open Access status: hybrid

Estimated APC paid: $3,000