• Title/Summary/Keyword: RK모형

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Population Distribution Estimation Using Regression-Kriging Model (Regression-Kriging 모형을 이용한 인구분포 추정에 관한 연구)

  • Kim, Byeong-Sun;Ku, Cha-Yong;Choi, Jin-Mu
    • Journal of the Korean Geographical Society
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    • v.45 no.6
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    • pp.806-819
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    • 2010
  • Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.

Patterning Zooplankton Dynamics in the Regulated Nakdong River by Means of the Self-Organizing Map (자가조직화 지도 방법을 이용한 조절된 낙동강 내 동물플랑크톤 역동성의 모형화)

  • Kim, Dong-Kyun;Joo, Gea-Jae;Jeong, Kwang-Seuk;Chang, Kwang-Hyson;Kim, Hyun-Woo
    • Korean Journal of Ecology and Environment
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    • v.39 no.1 s.115
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    • pp.52-61
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    • 2006
  • The aim of this study was to analyze the seasonal patterns of zooplankton community dynamics in the lower Nakdong River (Mulgum, RK; river kilometer; 27 km from the estuarine barrage), with a Self-Organizing Map (SOM) based on weekly sampled data collected over ten years(1994 ${\sim}$ 2003). It is well known that zooplankton groups had important role in the food web of freshwater ecosystems, however, less attention has been paid to this group compared with other community constituents. A non-linear patterning algorithm of the SOM was applied to discover the relationship among river environments and zooplankton community dynamics. Limnological variables (water temperature, dissolved oxygen, pH , Secchi transparency, turbidity, chlorophyll a, discharge, etc.) were taken into account to implement patterning seasonal changes of zooplankton community structures (consisting of rotifers, cladocerans and copepods). The trained SOM model allocated zooplankton on the map plane with limnological parameters. Three zooplankton groups had high similarities to one another in their changing seasonal patterns, Among the limnological variables, water temporature was highly related to the zooplankton community dynamics (especially for cladocerans). The SOM model illustrated the suppression of zooplankton due to the increased river discharge, particularly in summer. Chlorophyll a concentrations were separated from zooplankton data set on the map plane, which would intimate the herbivorous activity of dominant grazers. This study introduces the zooplankton dynamics associated with limnological parameters using a nonlinear method, and the information will be useful for managing the river ecosystem, with respect to the food web interactions.