손영환 교수
Young Hwan Son
서울대학교 조경·지역시스템공학부 · 공학
연구실 소개
손영환 교수의 연구실은 토양의 수분 함량 측정, 기후 변화 영향 평가, 토양 물리적 특성 분석 및 친환경 건축자재 개발을 중심으로 한 다학제적 연구를 수행하고 있습니다. 드론 기반 영상 분석과 딥러닝 기반 이미지 처리 기술을 활용해 토양의 수분과 밀도를 정밀하게 예측하며, 기후 변화에 따른 지반 안정성과 강우 유도 지반 붕괴를 수리적·확률적 방법으로 분석하고 있습니다. 또한 산업 부산물(굴껍질, 슬래그, 생분허브 등)을 활용한 친환경 투수 콘크리트 개발을 통해 자원 재활용과 환경 보존을 동시에 고려한 기술 혁신을 추구하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15The objective of this study is to monitor the water content of soil quickly and accurately using a UAV. Because UAVs have higher spatial and temporal resolution than satellites, they are currently becoming more useful in remote sensing areas. We developed a water content estimation equation using the color of the soil and suggested a calibration method for field application. Since the resolution of the images taken by the UAV is different according to the altitude, the water content estimation f
Rainfall is a major trigger of shallow slope failures, and it is necessary to consider the spatial correlation of soil properties for probabilistic analysis of slope stability in heterogeneous soil. In this study, a case study of a weathered soil slope in Korea was performed to identify the rainfall‐induced landslides considering the spatial variability of the soil properties and the probabilistic rainfall intensity depending on the return period and the rainfall duration. Various laboratory tes
This study aimed to develop a deep neural network model for predicting the soil water content and bulk density of soil based on features extracted from in situ soil surface images. Soil surface images were acquired using a Canon EOS 100d camera. The camera was installed in the vertical direction above the soil surface layer. To maintain uniform illumination conditions, a dark room and LED lighting were utilized. Following the acquisition of soil surface images, soil samples were collected using
In this study, permeable concrete blocks using industrial by-products (Oyster shell, bottom ash, and biochar) were developed, and the recycling suitability of the industrial by-products and engineering performances were evaluated. The flexural strength of permeable concrete blocks using by-products decreased as the bottom ash aggregate replacement ratio increased. When using oyster shell and biochar, the 28 days flexural strength was increased, and the development of initial strength was faster.
Digital image processing (DIP) is used to measure shape properties and settling velocity of soil particles. Particles with diameters of 1 to 10 mm are arbitrarily sampled for the test. The size of each particle is also measured by a Vernier caliper for comparison with the classification results using the shape classification table. The digital images were taken with a digital camera (Canon EOS 100d). Shape properties are calculated by image analysis software. Settling velocity of soil particles
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