GeoAI for Infrastructure Resilience: Mapping Exposure to Invasive Albizia Trees in Hawai’i

Invasive albizia (Falcataria falcata (L.) Greuter & R. Rankin) trees pose an increasing threat to infrastructure, transportation networks, and public safety in Hawai’i because their rapid growth and shallow root systems make them susceptible to windthrow during severe weather events. However, comprehensive spatial information on albizia distribution remains limited, constraining invasive-species management, hazard mitigation, and sustainable infrastructure planning. This study evaluates the applicability of a GeoAI-based framework for identifying invasive-tree-related infrastructure exposure at a regional planning scale. This study develops a GeoAI framework using a U-Net convolutional neural network with a ResNet-34 backbone to detect and map albizia canopy from 0.6 m National Agriculture Imagery Program (NAIP) aerial imagery. Training data from two geographically distinct areas, Mānoa and Kahalu’u, were used for model development and iterative refinement. The final model achieved a precision of 0.76, compared with 0.64 in the initial iteration, and was applied to estimate potential tree-fall exposure through spatial proximity analysis of roads and buildings. Following manual quality control, approximately 2 km2 of albizia canopy were identified within the study area. More than 53 km of roads and 2300 buildings were located within the potential tree-fall exposure zone, including portions of major transportation corridors such as Pali Highway, Likelike Highway, and Interstate H-3. By integrating scalable invasive-tree detection with infrastructure exposure assessment, the framework provides a spatial decision-support tool for prioritizing vegetation management, hazard mitigation, and infrastructure maintenance. The approach contributes to sustainability by supporting more targeted use of management resources, reducing potential disruption to critical infrastructure and essential access, and strengthening long-term community and infrastructure resilience.