ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model

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㎞ grid. Ten factors were selected to estimate the impact of topographic (elevation, slope, northern slope, curvature, wetness, relief) and geographic (distances from water, road, forest road, urban area) factor on H` using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. H` increased with the increase in spatial scale. Also, the coefficient of determination (R²) of the GWR and OLS models increased proportionally and R² of the GWR model was higher than that of the OLS model. Akaike’s Information Corrected 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 for than the OLS model understanding the effect of topographic and geographic factors on H` at different scales.

Corresponding author: Jungsoo Lee




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