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Analysis of Roadkill Hotspot According to the Spatial Clustering Methods

공간 군집지역 탐색방법에 따른 로드킬 다발구간 분석

  • Received : 2019.10.07
  • Accepted : 2019.12.05
  • Published : 2019.12.31

Abstract

This study analyzed roadkill hotspots in Yeongju, Mungyeong-si Andong-si and Cheongsong-gun to compare the method of searching the area of the spatial cluster for selecting the roadkill hotspots. The local spatial autocorrelation index Getis-Ord Gi* statistics were calculated by different units of analysis, drawing hotspot areas of 9% from 300 m and 14% from 1 km on the basis of the total road area. The rating of Z-score in the 1km hotspot area showed the highest Z-score in the 28th National Road section on the border between Yecheon-gun and Yeongj-si. The kernel density method performed general kernel density estimation and network kernel density estimation analysis, both of which made it easier to visualize roadkill hotspots than district unit analysis, but there were limitations that it was difficult to determine statistically significant priority. As a result, local hotspot areas were found to be different according to the cluster analysis method, and areas that are in common need of reduction measures were found to be the hotspot of 28th National Road through Yeongju-si and Yecheon-gun. It is deemed that the results of this study can be used as basic data when identifying roadkill hotspots and establishing measures to reduce roadkill.

본 연구는 로드킬 다발구간을 선정하기 위한 공간 군집지역 탐색방법을 비교하기 위하여 영주시, 문경시, 안동시, 청송군 로드킬 핫스팟 분석을 수행하였다. 국지적 공간 자기상관 지수인 Getis-Ord Gi* 통계량은 분석 단위를 달리하여 산출하였으며, 전체 도로면적 기준으로 300m에서 9%, 1km에서 14%의 핫스팟 지역을 도출하였다. 1km 단위 핫스팟 지역의 Z-score를 5개로 등급화한 결과, 예천군과 영주시 경계에 있는 28번 국도 구간의 Z-score가 가장 높게 나타났다. 커널 밀도 방법은 일반 커널 밀도 추정과 네트워크 커널 밀도 추정 분석을 수행하였다. 두 방법 모두 구역 단위의 분석보다 로드킬 다발구간의 시각적 확인이 용이했으나, 통계적으로 유의한 우선순위를 산정하기 어려운 한계가 있었다. 결과적으로 군집 분석방법에 따라 국지적인 핫스팟 지역이 다르게 나타나고 있음이 확인되었으며, 공통적으로 저감 대책이 시급한 지역은 영주시와 예천군을 통과하는 28번 국도의 다발구간으로 나타났다. 본 연구의 결과는 향후 로드킬 다발구간 도출 및 저감 대책 수립시 기초자료로 활용될 수 있을 것으로 판단된다.

Keywords

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