Modeling urban wasp nest occurrences using 119 fire service reports, LiDAR, and hyperspectral imagery: The role of green spaces and structural factors.

The increasing presence of wasp nests in urban areas raises ecological, economic, and public safety concerns. This study integrates 10 years (2014-2023) of data from 119 fire service reports, high-resolution LiDAR-derived structural information, hyperspectral imagery, and urban microclimate analysis to examine the spatial distribution and key environmental factors influencing wasp nest occurrences in Gwacheon, South Korea. The results indicate a 4.23-fold increase in wasp nest incidents over the past decade, highlighting the increasing prevalence of urban wasp populations. Analysis of fire service reports classified nest occurrence types into four categories: artificial structures (28.2%), natural environments (10.5%), subterranean environments (1.0%), and underground structures (0.13%). The majority of wasp nests were found in artificial structures, particularly in low-rise buildings, demonstrating a strong correlation between nesting preferences and urban structural characteristics. MaxEnt species distribution modeling (AUC = 0.797) identified proximity to green spaces (within 170 m) as the strongest predictor of wasp nest occurrences, followed by building height and shadow relief. Both fire service reports and model predictions confirmed that low-rise buildings (2-5 m) served as the primary nesting sites, emphasizing the role of structural factors in habitat selection. Additionally, urban microclimates around 37 °C promoted nest establishment, whereas extreme temperatures had a negative impact. These findings highlight the importance of high-resolution spatial, ecological, and social data in proactively identifying high-risk urban areas for wasp nest formation. This study proposes an integrated management strategy that considers spatial, ecological, and social factors for effective wasp mitigation. By leveraging long-term incident reports, predictive modeling, and participatory data, urban planners and policymakers can develop targeted interventions that mitigate wasp-related risks while promoting urban biodiversity conservation.