연안 폐기물 관리 목적의 UAV 사진측량 기반 굴패각 적치량 정량적 평가: 통영시 사례 연구

초록

Tongyeong is the largest oyster-producing region in Korea, but despite the substantial annual generation of oyster shell waste, the lack of quantitative data on stockpile volumes has limited effective management and recycling strategies. UAV (Unmanned Aerial Vehicle) photogrammetry and SfM (Structure-from-Motion) techniques are widely used for volume estimation, yet oyster shell stockpiles pose challenges due to surface heterogeneity, internal settlement, uneven layering, and noise from seawater reflections. This study proposes a refined procedure to improve the reliability of quantitative volume estimation by addressing these site-specific characteristics. High-resolution UAV imagery was acquired for eight representative stockpile sites, and spatial accuracy was ensured using RTK-GNSS–based ground control points and check points. Shadowed and water-affected areas were excluded to construct DTM (Digital Terrain Model) candidates, and the DTM was normalized to match the resolution of the DSM (Digital Surface Model). The DSM–DTM analysis estimated a total stockpile volume of approximately 8,490 m3. This study provides a foundational methodology for reliably evaluating irregular oyster shell stockpiles in a context where quantitative data remain extremely limited. Future periodic observations and time-series analyses are expected to identify key factors influencing stockpile volume changes and support the development of a more systematic dataset. © 2025, Korean Society of Surveying. All rights reserved.

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