공간자기상관을 위한 이웃 정의 방법 비교

Title
공간자기상관을 위한 이웃 정의 방법 비교
Alternative Title
A Comparison of Neighbor Definition Methods for Spatial Autocorrelation
Author(s)
박재문; 최현우; 윤홍주
KIOST Author(s)
Choi, Hyun Woo(최현우)
Publication Year
2008-06-18
Abstract
For the identifying of spatial autocorrelation pattern, Moran’s Index (I) which has the range of value is -1 to +1 is common method for spatial autocorrelation measurements. When I is close to 1, all neighboring features have close to the same value, indicating clustered pattern. Conversely, if the spatial pattern is dispersed, I is close to -1. And I closing to 0 means spatially random pattern. However, this index equation is influenced by how define the neighboring features for target feature. To compare and understand the difference of neighbor definition methods, Fixed Euclidean Distance neighboring method and Gabriel Network method were used for I. In this study, these two methods were applied to two marine environments with water quality data. One is Gwangyang Bay which has complex geometric costal structure located in the South Sea of Korea. And for the Fixed Euclidean Distance method popular ArcGIS (ESRI) tool was used, but, for the Gabriel Network, Visual Basic program was developed to produce Gabriel Network and calculate Moran’s I and its Z-score automatically. According to those experimental results, different spatial pattern was showed differently for some data with the using of neighboring definition methods. Therefore, it is need to choose neighboring definition method carefully for spatial pattern analysis.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/29889
Bibliographic Citation
Geoinformation Forum Japan 2008, pp.1 - 6, 2008
Publisher
Japan Association Surveyors(JAS)
Type
Conference
Language
English
Publisher
Japan Association Surveyors(JAS)
Related Researcher
Research Interests

Spatial information,Marine bigdata,Marine index,해양공간정보,해양빅데이터,해양지수개발

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