The expansion and evolution of urban areas are the most perceptible manifestations of the transformation of the urban spatial form. This study uses remote sensing images of Nanjing from 2001, 2006, 2011, 2016, and 2021, along with socio-economic data to analyse the spatio-temporal characteristics of the city’s urban expansion. Furthermore, we utilize a binary logistic regression to quantitatively analyse the driving forces in each stage. We find that from 2001 to 2021, Nanjing’s urban area expanded approximately 3.97 times. Notably, the city started moving from a stage of medium-speed development to rapid development in 2006, and then slowed down and returned to medium-speed development in 2011. The urban land mainly expanded in the north, northeast, southeast, and southwest directions in a lopsided cross-shape roughly along the northwest-southeast direction; meanwhile, the city’s centre of gravity continuously moved towards the southeast. Among the driving factors, neighbourhood (distance from planned commercial centres, railways, and highways), topography, and geolocation (distance from the Yangtze River, and elevation) had a greater, albeit inhibitory effect on urban expansion. However, the effects of different socio-economic factors (GDP per capita, resident population, secondary and tertiary industry, etc.) varied across different time periods.

Rapid urban development has changed urban substrate conditions, greatly affecting urban ecology and heating urban environment. Mitigating urban temperature rises by optimizing urban morphology is considered a promising approach; most studies ignore spatial and temporal heterogeneity. This study analyzes how plot spatial form influences urban thermal environment in the main Nanjing area from 2001, 2006, 2011, 2016, and 2021, based on geographically weighted regression models (spatio-temporal- and multi-scale). Results show that: 1. The formation of geothermal heat islands matches the direction of urban expansion, mainly due to changes in land substrate; 2. the spatio-temporal model performs best, indicating that urban morphology and surface thermal environment have obvious spatio-temporal heterogeneity; obvious scale differences exist in each index influencing the heat island effect; and 3. floor area ratio (FAR) and building density (BD) negatively and positively correlate with surface thermal conditions, with gradually increasing effect, respectively. Normalized difference vegetation index (NDVI) and distance from the nearest water body (Dis_W) negatively and positively correlate with surface thermal conditions separately; good ecological infrastructure reduces surface temperatures but shows a gradually weakening effect. Proximity to roads is associated with warmer thermal environment. This study elucidates how urban form influences surface thermal environments and suggests measures to reduce surface temperatures in the main urban Nanjing area.