메뉴 건너뛰기
Library Notice
Institutional Access
If you certify, you can access the articles for free.
Check out your institutions.
ex)Hankuk University, Nuri Motors
Log in Register Help KOR
Subject

Estimation of Building Boundaries from Airborne LiDAR Data
Recommendations
Search
Questions

항공 라이다 데이터를 이용한 건물의 윤곽선 추정

논문 기본 정보

Type
Proceeding
Author
Yoo, Eun Jin (세종대학교) Lee, Dong-Cheon (세종대학교)
Journal
Korea Society of Surveying, Geodesy, Photogrammetry, and Cartography 한국측량학회 학술대회자료집 2016 한국측량학회 정기학술발표회
Published
2016.4
Pages
152 - 155 (4page)

Usage

cover
📌
Topic
📖
Background
🔬
Method
🏆
Result
Estimation of Building Boundaries from Airborne LiDAR Data
Ask AI
Recommendations
Search
Questions

Abstract· Keywords

Report Errors
Delineation of the accurate building boundaries is crucial to provide reliable spatial products such as digital maps and city models. In LiDAR(Light Detection and Ranging) data, physical boundaries of the building exist somewhere between outer-most points on the roofs and surrounding points on the ground. The positional accuracy of the boundaries is influenced by ground sampling distance, and only a few points could be obtained from the sidewalls because airborne laser systems collect data from near-nadir direction. This paper presents a method to estimate physical building boundaries from the LiDAR data. Firstly, outer-most points on the buildings were identified, then the nearest points on the ground were determined at every point along the outer-most boundaries. Secondly, Midpoints were computed using outer-most points and the nearest points. Finally, refinement processes including model key point detection and regularization were performed since the midpoints represent approximation of the physical boundaries.

Contents

Abstract
1. 서론
2. 연구방법 및 실험
3. 결과 및 분석
4. 결론
References

References (0)

Add References

Recommendations

It is an article recommended by DBpia according to the article similarity. Check out the related articles!

Related Authors

Frequently Viewed Together

Recently viewed articles

Comments(0)

0

Write first comments.

UCI(KEPA) : I410-ECN-0101-2017-533-001152504