인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
This study proposes a methodology for generating 3D cadastral boundaries by utilizing point cloud data acquired from a UAV (Unmanned Aerial Vehicle) LiDAR (Light Detection and Ranging) system. For this purpose, 2D continuous cadastral maps and point cloud data of the study area were first acquired, and a workflow was established to generate 3D cadastral boundaries from the collected data. To facilitate the integrated processing of 3D cadastral information, the workflow was developed based on QGIS, an open source GIS (Geographic Information System) platform that supports extensive interoperability and various plugins. The workflow was structured into four major stages including 1) the ground classification of point cloud data, 2) the generation and interpolation of a grid model DEM, 3) the unification of coordinates between datasets, and 4) the generation of 3D cadastral boundaries. By performing data processing according to this established workflow and automatically assigning height values to 2D cadastral boundaries, 3D cadastral boundaries were successfully generated for a total of 56 boundary points without any omissions. These results demonstrate the practical feasibility of the proposed UAV LiDAR point cloud-based methodology for 3D cadastral boundary generation. In the future, these findings are expected to be utilized as a technical solution for renovation of cadastre projects as well as various construction sites requiring precise 3D cadastral information.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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