水里溪上游集水區檳榔園熱點空間分析之研究

The Spatial Analysis of Betel Nut Plantation Hot Spots in the Upper Shui-Li Creek Watershed

10.29417/JCSWC.201309_44(3).0002

葉春國(Chun-Kuo Yeh)；莊永忠(Yung-Chung Chuang)；廖學誠(Shyue-Cherng Liaw)

空間自相關 ； 熱點 ； 檳榔園 ； 集水區經營 ； Spatial autocorrelation ； hot spots ； betel nut plantations ； watershed management

中華水土保持學報

44卷3期（2013 / 09 / 01）

202 - 214

繁體中文

This study investigated the spatial distribution of BNP hot spots in the upper Shui-Li Creek watershed. Two spatial autocorrelation methods, Moran's I and G statistics, were selected for analyzing the spatial cluster of BNPs with different grid sizes. The results show that spatial autocorrelation analysis can indeed discover BNP hot spots in this watershed. The strength and significance of spatial dependence can be easily compared and monitored. For the global spatial autocorrelation analysis, both Moran's I and G statistics values are positive with whole different grid sizes and statistically significant (p ＜ 0.05). This means that the BNPs in study areas obviously have the characteristics of positive spatial autocorrelation. Furthermore, with the increase of the grid size, the value of Moran's I decreases, but the value of G statistics increases.

This study investigated the spatial distribution of BNP hot spots in the upper Shui-Li Creek watershed. Two spatial autocorrelation methods, Moran's I and G statistics, were selected for analyzing the spatial cluster of BNPs with different grid sizes. The results show that spatial autocorrelation analysis can indeed discover BNP hot spots in this watershed. The strength and significance of spatial dependence can be easily compared and monitored. For the global spatial autocorrelation analysis, both Moran's I and G statistics values are positive with whole different grid sizes and statistically significant (p ＜ 0.05). This means that the BNPs in study areas obviously have the characteristics of positive spatial autocorrelation. Furthermore, with the increase of the grid size, the value of Moran's I decreases, but the value of G statistics increases.