Urban Morphological Evolution and the Spatial Restructuring of Carbon Emissions in High-Density Taipei: A 3D Historical GIS, XAI, and MGWR Analysis, 1980–2025

Compact development is often treated as a low-carbon strategy; yet, high-density cities may face new carbon pressures as vertical development, agglomeration, and cross-district mobility intensify. This study examines Taipei using 27,239 100 m × 100 m grid cells and 1980–2025 data integrating Historical GIS, remote sensing, official LOD1 building models, zone-level energy statistics, and anonymized origin–destination data. Zone-level energy totals were converted to CO2 and allocated to 100 m cells through a mass-preserving proxy surface; the resulting grid target is therefore a reconstructed allocation rather than an independently observed cell-level outcome. XGBoost, TreeSHAP, multiscale geographically weighted regression (MGWR), CASA, and network analysis served as complementary instruments. Random ten-fold cross-validation provided internal reconstruction diagnostics but was not spatially blocked and does not establish spatial transferability. The mean carbon-emission compound annual growth rates of existing built-up cells were 2.994% in the historic western districts and 2.890% in the emerging eastern districts (Welch’s test, p = 0.104). This non-significant result does not establish equivalence or identify the contributions of existing and newly built-up areas to aggregate growth; the extensive-margin hypothesis remains untested. TreeSHAP identified model-specific empirical breakpoints at 12.83 for a standardized, unitless nighttime-light index, 197.67 buildings/km2 for the building density, and 99.61 for the dimensionless FAR × Nightlight composite. These values indicate changes in the model-predicted feature contributions; they are not physical emission triggers, causal transition points, universal planning standards, or transferable regulatory cut-offs. MGWR achieved an adjusted R2 of 0.886 and revealed marked multiscale spatial non-stationarity; its coefficients are interpreted only as conditional spatial statistical associations. The observed Taipei Metro OD flows further indicated a cross-boundary carbon-burden asymmetry, but the network covers metro travel only and excludes buses, motorcycles, private cars, walking, cycling, and other modes. As an observational and proxy-based reconstruction, the study supports predictive and spatial associations rather than strict causal effects.