Keywords
Moran’s I
LISA
Earthquake Distribution
North Sumatra
How to Cite
Abstract
This study aims to analyze the spatial distribution patterns of earthquake occurrences in North Sumatra during 2022 using spatial statistical approaches, namely the global Moran’s I autocorrelation test and Local Indicators of Spatial Association (LISA), visualized through a Moran Scatter Plot. The data used in this study are secondary data obtained from the official earthquake catalog released by the Meteorology, Climatology, and Geophysics Agency (BMKG), including information on geographic location, time of occurrence, magnitude, and depth of earthquakes. The analysis was conducted using R and QGIS software, applying three types of spatial weighting: inverse distance, k-nearest neighbors (KNN), and adaptive Gaussian kernel functions. The results of the Moran’s I test revealed significant global spatial autocorrelation, indicating that earthquakes with similar magnitudes tend to cluster geographically. In contrast, the LISA analysis showed that most points did not exhibit significant local spatial association, although a few clusters of high-high, low-low, high-low, and low-high types were identified. These findings confirm the presence of spatial patterns in the distribution of earthquakes in North Sumatra, which are relevant for supporting mitigation efforts and spatially-based disaster management planning.
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