Understanding the spatiotemporal impacts of land use transition on carbon emissions is crucial for achieving regional carbon neutrality. This study presents an integrated analytical framework that combines dynamic land use modeling, the Geo-detector method (GDM), and Geographically and Temporally Weighted Regression (GTWR) to analyze land use transition and carbon emission dynamics in China’s Pearl River Delta (PRD) from 2000 to 2020. Key findings include: (1) Construction land expansion was the dominant explicit transition, with land conversion sources shifting from cropland-centric patterns to diverse transfers involving woodland and water bodies. (2) The implicit land use transition index exhibited an annual growth rate of 15.6%, progressing through three phases—rapid development (2000–2010), structural adjustment (2010–2015), and high-quality transition (2015–2020). (3) Regional carbon emissions increased by 186.96%, exhibiting spatial disparities between core and peripheral regions. Construction land expansion and GDP density were primary drivers. This research advances the theoretical integration of land system science and low-carbon governance, offering actionable insights for spatially differentiated emission reduction strategies in megacity clusters.
Wang et al. (Fri,) studied this question.