Development of a UAV LiDAR-Based Framework for Consolidation Settlement Monitoring Through Spatial Analysis
2025
Seok-Jun Ko | Seongho Hong | Tae-Young Kwak
Construction sites with deep soft deposits usually experience significant consolidation settlement that can compromise structural integrity if not properly monitored. Conventional methods, such as settlement plates, are limited by high costs and sparse spatial coverage, which leaves areas unmonitored and vulnerable to unexpected settlement. Therefore, this study develops an integrated UAV LiDAR monitoring framework that optimizes data preprocessing and introduces a novel timeseries settlement correction and interpolation technique for staged surcharge loading. Using UAV LiDAR data acquired at biweekly intervals from May 2021 to March 2022 at Busan Newport, high-quality digital elevation models were generated through optimal preprocessing. We are the first to evaluate the spatial representativeness of consolidation settlement at multiple section sizes (10 m × 10 m, 50 m × 50 m, and 100 m × 100 m) using high-resolution LiDAR, revealing that larger section sizes produce greater spatial variability and prediction error. Moreover, we demonstrate that at least seven biweekly UAV LiDAR surveys are essential to reliably capture early-stage settlement behaviors, providing a practical guideline for monitoring campaigns. These findings show that the proposed UAV LiDAR framework can deliver valuable insights for managing settlement in marine and soft ground construction projects.
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