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Accurately identifying extreme land surface temperature (LST) zones—heat cores (HCs, areas with persistent high temperatures) and cold cores (CCs, areas with persistent low temperatures)—is crucial for urban climate resilience. Traditional approaches fail to capture subtle LST variations and hierarchical structures. This study introduces the Local Contour Tree Analysis (LCTA), a graph theory–based method that captures topological hierarchies and dynamic interactions, surpassing conventional fixed-threshold techniques. Applied to western Shenzhen, China, it revealed HCs' northward interannual migration from southern clustering through dispersion to northern clustering, while CCs remained stable as primary cooling sources. Seasonally, HCs exhibited stronger clustering in summer and greater dispersion in winter; CCs maintained structural layering year-round with reduced heterogeneity in winter. Structurally, HCs were simple and compact, while CCs were complex, multi-layered, and interconnected. Urban thermal deterioration concentrated in stable HCs due to impervious surface expansion and vegetation loss, while improvements occurred around CCs through vegetation recovery. These shifts reflected urbanization trends and revealed scale-specific characteristics tied to development stages. Findings elucidate HC and CC mechanisms, informing green-blue infrastructure planning via targeted vegetation corridors to enhance cooling connectivity and counteract HC expansion, offering actionable heat mitigation strategies for rapidly developing urban regions.

Identification and tracking of heat and cold cores in highly urbanized areas: spatiotemporal characteristics and evolutionary patterns