Earticle

초록

영어

This study analyzed the road infrastructure of North Korea through big data analysis. Google Distance Matrix API was used to crawling data. Based on the collected data, the Shimbel index was calculated and the spatial autocorrelation was examined. The results of autocorrelation analysis showed that the road infrastructure of North Korea has spatially clustered. Result of hot spot analysis, Pyongyang and Hwanghae province has good road infrastructure but Chagang has poor. Finally, the condition of road infrastructure was visualized through Kernel Density Estimation. It is interesting that the development of a specialized zone in North Korea does not affect the surrounding area. This study suggests a new direction of North Korean spatial research using a differentiated method. It suggests the possibility of application to accessibility research not only in North Korea but also in other developing countries.

목차

Abstract
1. 서론
2. 북한의 도로 인프라 현황
2.1. 북한의 도로망 체계
2.2. 북한 도로 인프라의 문제점
2.3. 북한의 도로 인프라 분석 선행연구
3. 도로 인프라 측정 및 공간분석 방법론
3.1. 도로 인프라의 측정과 평가
3.2. Google Distance Matrix API를 활용한 교통 데이터 크롤링
3.3. 공간자기상관을 활용한 공간군집 분석
3.4. 커널밀도추정을 활용한 시각화
4. 실증분석
4.1. 우회 및 심벨지수를 활용한 북한의 도로 인프라 평가
4.2. Moran’s I 지수를 활용한 도로 인프라 공간군집 분석
4.3. 커널밀도추정을 활용한 북한의 도로 인프라 시각화
5. 결론 및 정책적 시사점
주
참고문헌

키워드

저자

• 김철민 [ Kim, Chulmin | 강원대학교 부동산학과 시간강사 ] 주저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국지역개발학회지 [Journal of the Korean Regional Development Association]

• 간기

  연5회

• pISSN

  1225-9055

• 수록기간

  1989~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 322 DDC 330