Journal of the Korean Society of Environmental Restoration Technology (한국환경복원기술학회지)

The Korea Society of Environmental Restoration Technology (한국환경복원기술학회)
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Spatial Estimation of Forest Species Diversity Index by Applying Spatial Interpolation Method - Based on 1st Forest Health Management data-

공간보간법 적용을 통한 산림 종다양성지수의 공간적 추정 - 제1차 산림의 건강·활력도 조사 자료를 이용하여 -

  • Lee, Jun-Hee (Environmental Science & Ecological Engineering, Korea University) ;
  • Ryu, Ji-Eun (Environmental GIS/RS Center, Korea University) ;
  • Choi, Yu-Young (Environmental Science & Ecological Engineering, Korea University) ;
  • Chung, Hye-In (Environmental Science & Ecological Engineering, Korea University) ;
  • Jeon, Seong-Woo (Environmental Science & Ecological Engineering, Korea University) ;
  • Lim, Jong-Hwan (National institute of forest science) ;
  • Choi, Hyung-Soon (National institute of forest science)
  • Received : 2019.04.01
  • Accepted : 2019.08.19
  • Published : 2019.08.31
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Abstract

The 1st Forest Health Management survey was conducted to examine the health of the forests in Korea. However, in order to understand the health of the forests, which account for 63.7% of the total land area in South Korea, it is necessary to comprehensively spatialize the results of the survey beyond the sampling points. In this regard, out of the sample points of the 1st Forest Health Management survey in Gyeongbuk area, 78 spots were selected. For these spots, the species diversity index was selected from the survey sections, and the spatial interpolation method was applied. Inverse distance weighted (IDW), Ordinary Kriging and Ordinary Cokriging were applied as spatial interpolation methods. Ordinary Cokriging was performed by selecting vegetation indices which are highly correlated with species diversity index as a secondary variable. The vegetation indices - Normalized Differential Vegetation Index(NDVI), Leaf Area Index(LAI), Sample Ratio(SR) and Soil Adjusted Vegetation Index(SAVI) - were extracted from Landsat 8 OLI. Verification was performed by the spatial interpolation method with Mean Error(ME) and Root Mean Square Error(RMSE). As a result, Ordinary Cokriging using SR showed the most accurate result with ME value of 0.0000218 and RMSE value of 0.63983. Ordinary Cokriging using SR was proven to be more accurate than Ordinary Kriging, IDW, using one variable. This indicates that the spatial interpolation method using the vegetation indices is more suitable for spatialization of the biodiversity index sample points of 1st Forest Health Management survey.

Keywords

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