Journal of Cadastre & Land InformatiX (지적과 국토정보)

LX Spatial Information Research Institute (한국국토정보공사 공간정보연구원)
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A Study on the Spatial Distribution Patterns of Urban Green Spaces Using Local Spatial Autocorrelation Statistics

국지적 공간자기상관통계를 이용한 도시녹지의 공간적 분포패턴에 관한 연구

  • Kim, Yun-Ki (Department of Land Management, Choengju University)
  • Received : 2020.02.21
  • Accepted : 2020.06.12
  • Published : 2020.06.30
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Abstract

The primary purpose of this study is to compare and analyze the performance of local spatial autocorrelation techniques in identifying spatial distribution patterns of green spaces. To achieve the objective, this researcher uses satellite image analysis and spatial autocorrelation techniques. The result of the study shows that the LISA cluster map with the spatial outlier cluster is superior to other analytical methods in identifying the spatial distribution pattern of urban green space. This study can contribute to the related fields in that it uses several different research methods than the existing ones. Despite this differentiation and usefulness, this study has limitations in using low-resolution satellite imagery and NDVI among vegetation indices in identifying spatial distribution patterns of green areas. These limitations may be overcome in future studies by using UAV images or by simultaneously using several vegetation indices.

본 연구의 주된 목적은 녹지의 공간 분포 패턴을 식별하는데 있어 국지적 공간자기상관 기법들의 성능을 비교하고 분석하는 것이다. 이 연구목적을 달성하기 위해 본 연구는 위성영상분석기법과 공간자기상관기법들을 이용하였다. 분석의 결과 공간 특이치 군집을 갖는 LISA 군집지도가 도시녹지의 공간 분포 패턴을 식별하는 데 있어서 다른 분석기법들보다 우수함이 확인되었다. 본 연구는 기존의 연구들과는 다른 몇 가지 연구방법을 이용했다는 점에서 관련분야에 기여할 수 있다. 이러한 차별성과 유용성에도 불구하고 본 연구는 녹지의 공간적 분포패턴을 식별하는 있어서 저해상도 위성영상을 이용했다는 점과 식생지수들 중에서 NDVI만을 이용했다는 점에서 한계를 지닌다. 이러한 한계들은 향후연구에서 UAV영상을 이용하거나 또는 여러 가지 식생지수들을 동시에 이용한다면 극복될 수 있을 것이다.

Keywords

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