인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
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.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.3
- 수록면
- 189 - 198 (10page)
이용수
초록· 키워드
The shape of land parcels greatly affects land value, the density of buildings, and the shape of a building. Although the Korean system classifies parcel shapes into 6 types, there are irregularly shaped land parcels that cannot be classified. Irregular shaped land parcels impose many restrictions on the arrangement and form of buildings, and these restrictions are even more severe with small parcels. Until now, studies on the shape of parcels have been conducted, but studies on irregularly shaped land parcels have been insufficient. Therefore, this study aims to typify irregular shaped land parcels that are difficult for humans to distinguish by applying machine learning methodology and to identify the characteristics of each type. The subject of this study is irregular shaped land parcels in the class-II general residential areas of Seoul; there were 500 sample parcels extracted and used for analysis. Irregular shaped land parcels were typified using K-means clustering, which is a representative method of unsupervised learning to solve classification problems. Afterwards, the values of Shape Index (SI), STandard Index (STI), and With-depth Ratio (WR), which are indices related to parcel shape, were compared by type. Upon analysis, the types of irregular parcels could be divided into avocado type, potato type, corner type, bell type, stick type, and L-shaped type. The stick type and L-shaped type reflected small SI values. The avocado type, corner type, and L-shaped type revealed small STI values. Lastly, the WR value was substantial for the stick type and L-shaped type.
#부정형필지
#필지형태
#기계학습(머신러닝)
#K-평균 클러스터링
#도시공간구조
#Irregular Shaped Land Parcel
#Shape of Land Parcel
#Machine Learning
#K-means Clustering
#Urban Spatial Structure
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목차
- Abstract
- 1. 서론
- 2. 이론적 배경 및 선행연구 검토
- 3. 분석의 틀
- 4. 분석결과
- 5. 결론
- REFERENCES
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2022-540-001061417