Journal of Environmental Impact Assessment (환경영향평가)

Korean Society of Environmental Impact Assessment (한국환경영향평가학회)
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A Study on Fauna Habitat Valuation of Urban Ecological Maps

도시생태현황지도 작성을 위한 육상동물 서식지 가치평가 방안 연구

  • Received : 2020.07.14
  • Accepted : 2020.08.27
  • Published : 2020.10.31
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Abstract

URBAN ECOLOGICAL MAPS must be created by local governments by NATURAL ENVIRONMENT CONSERVATION ACT, and the maps are generally called biotope map. So far, biotope maps study was a tendency to focus on the type of vegetation, naturalness, land use, landscape ecology theories. However, biotope related studies have not reflected the concept of animal habitat, which is a component of biotope, and that is the limitation of biotope map research. This study suggest a methodology to predict potential habitats for fauna using machine learning to quantify habitat values. The potential habitats of fauna were predicted by spatial statistics using machine learning, and the results were converted into species richness. For biotope type assessments, we classified biotope values into vegetation value and habitat value and evaluated them using a matrix for value summation. The vegetation value was divided into 5 stages based on vegetation nature and land use, and the habitat value was classified into five stages by predicting the species richness predicted by machine learning. This is meaningful because our research can positively reflect the results of field surveys of fauna that were negatively reflected in the evaluation of biotope types in the past. Therefore, in the future, if the biotope map manual is revised, our methodology should be applied.

도시생태현황지도는 자연환경보전법에 의해 시(市)단위 이상의 지방자치단체는 의무적으로 작성해야 하며 일반적으로 비오톱지도라고 한다. 그 동안 비오톱지도 관련 연구는 식생유형, 식생자연성, 토지이용, 경관생태학 배경으로 이루어 졌으며, 비오톱의 구성요소인 동물서식지 개념을 적용하지 못하는 한계성을 가지고 있었다. 이 연구는 이러한 한계성을 개선하기 위해 육상동물 잠재서식지 개념을 도입하여 비오톱 유형평가에 적용할 수 있는 방법론을 제안하기 위해 수행되었다. 육상동물의 잠재서식지는 머신러닝을 이용한 공간통계 방법을 이용하여 예측하였고 그 결과를 종합하여 종풍부도로 변환하였다. 비오톱 유형평가는 식생학적 가치, 동물서식지 가치로 구분하여 가치합산 하였다. 식생학적 가치는 식생의 자연성과 토지이용을 고려하여 5단계로 구분하였고, 동물 서식지 가치는 머신러닝으로 예측한 종풍부도를 5단계로 구분하여 비오톱 유형평가에 적용하였다. 이 연구는 그동안 비오톱 유형평가에 소극적으로 반영된 육상동물 현장조사 결과를 적극적으로 반영할 수 있는 방법론을 도출하였다는 것에 의미가 있으며 향후 도시생태현황 지도 작성 매뉴얼 개정 시 고려될 필요가 있다.

Keywords

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