Military–civilian interface zones (MCIZs) adjacent to the Korean Demilitarized Zone (DMZ) represent complex wildfire environments shaped by restricted access, intensive military activities, and adjacent civilian land use. This study develops a spatially explicit wildfire ignition risk assessment framework for the DMZ and Civilian Control Zone (CCZ) in Paju, South Korea, employing Random Forest (RF), Generalized Additive Models (GAM), and Geographically Weighted Regression (GWR) in a complementary analytical design. A dataset of 318 wildfire ignition events (2001–2024), including 78 associated with military activities, was analyzed. The RF model achieved high predictive accuracy (AUC = 0.81), identifying proximity to military training zones, relative humidity, wind speed, and proximity to built infrastructure as dominant ignition drivers. GAM revealed narrow nonlinear thresholds—relative humidity at 13.8%–14.0% and wind speed at 13.5–14.0 m/s—corresponding to peak ignition probabilities. GWR demonstrated pronounced spatial heterogeneity, with military proximity exerting a stronger influence in the eastern and northern sectors, while the meteorological effects varied geographically. Based on these outputs, a unified analytical framework was established in which RF-derived ignition probabilities were interpreted alongside GAM- and GWR-based explanatory layers to provide spatially explicit ignition susceptibility assessments without numerical map fusion. The proposed approach provides a scientifically rigorous and operationally applicable method for quantifying ignition risk in politically sensitive, access-restricted landscapes, offering valuable insights for adaptive wildfire prevention and spatially informed governance of transboundary fire risk.

In this final of a three‐part series of review articles on the uneven geographies of COVID‐19, we zoom in on the social geographies of COVID's pandemic phase. We discuss research findings from across the globe that offer insights into the ways in which this phase was experienced by different populations and in various socio‐spatial contexts. Intersectionality provides an important lens to understand how pre‐COVID inequalities and injustices intersected with the COVID crisis. By mobilizing syndemics theory we highlight the interlocking of multiple burdens of disease and unjust social conditions turning the pandemic into a syndemic, where deprived populations experienced a much higher burden of disease and negative side‐effects from public health restrictions. Findings on the changing role of public space, borders, and mobility and immobility are discussed. This is followed by an analysis of research that has focused on migrants, refugees, gendered work and violence, women, youth and young people. The article concludes with a discussion of different interacting crises temporalities in relation to socio‐spatial unevenness. Avenues for further research and conceptual developments are suggested.