Extreme storms and accelerating shoreline retreat require coastal management that can rapidly diagnose recovery and select interventions that remain spatially and economically viable. We present two complementary approaches for adaptive management of coupled beach-community systems. First, repeated UAV surveys at pre-storm, storm-affected and recovery stages generated high-resolution elevation and imagery products for six systems exposed to Typhoons In-fa and Chanthu in Zhoushan. UAV-derived geomorphic changes were integrated with vegetation, hazard exposure and community-development indicators, while machine learning identified their contributions to resilience. Community-managed beaches achieved recovery rates up to 114.74% and the highest resilience index (0.455), whereas infrastructure-protected beaches recovered less effectively. Beach-community distance was the leading contributor to resilience (32.8%), demonstrating the management value of spatial buffers. Second, a multi-scenario strategy was developed for six beaches in Shenzhen. Two ecological setback zones were delineated using predicted shoreline erosion and maximum historical retreat, and three management strategies - business-as-usual, ecological protection retreat and ecological adaptive restoration - were compared through cost-benefit analysis for 2024-2050. The larger setback zones based on maximum historical retreat, combined with ecological adaptive restoration, achieved the highest investment efficiency across all beaches. Together, the studies establish a monitoring-to-decision framework in which rapid UAV assessment identifies recovery constraints, while scenario-based setback planning determines where and how adaptation should be implemented. This framework supports adaptive coastal management through iterative monitoring, community participation, spatial retreat, ecosystem restoration and site-specific investment decisions.