pp. 3197-3213
S&M2005 Research Paper of Special Issue https://doi.org/10.18494/SAM.2019.2300 Published: October 31, 2019 Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model [PDF] Jeongmook Park, Byoungkoo Choi, and Jungsoo Lee (Received January 16, 2019; Accepted August 19, 2019) Keywords: GWR model, Moran’s index, species diversity, Shannon–Weaver index
The objective of this study is to evaluate the spatial distribution patterns of species diversity at different spatial scales, focusing on the Baekdudaegan Protected Area, which is a biodiversity hotspot in the Republic of Korea. The tree species diversity index (Shannon–Weaver index; H′) was calculated using tree species data from a 1:5k forest-type map, and the spatial analysis was performed with a 1 × 1 km2 grid. Ten factors were selected to estimate the impact of topographic (elevation, slope, northern slope, curvature, wetness, and relief) and geographic (distances from water, road, forest road, and urban area) factors on H′ using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. H′ increased with the spatial scale. Also, the coefficient of determination (R²) of the GWR and OLS models increased proportionally and the R² of the GWR model was higher than that of the OLS model. Corrected Akaike Information Criterion (AICc) was lower in the GWR model than in the OLS model, which indicates that the GWR model fits the calculated H′ better than the OLS model. Thus, the GWR model is considered to be more practical than the OLS model for understanding the effects of topographic and geographic factors on H′ at different scales.
Corresponding author: Jungsoo LeeThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Jeongmook Park, Byoungkoo Choi, and Jungsoo Lee, Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model, Sens. Mater., Vol. 31, No. 10, 2019, p. 3197-3213. |