<![CDATA[Urban crime is an ecological problem due to the interaction of various ecological, social and economic factors. Factors that are thought to trigger crime rates include the availability of green open space (RTH), extreme poverty, population density, light at night, relative wealth, and the number of security services and worship facilities. The green open space identification process utilizes Sentinel-2 Multi Spectral Instrument Level 2A by measuring the Enhanced Vegetation Index (EVI). Spatial regression analysis with Queen Contiguity weighting was used to see the influence of these factors on crime rates between regions. The Ordinary Least Squares model is better than spatial regression because the data does not show spatial autocorrelation between regions, so Ordinary Least Squares can be used as a simpler model. The number of extreme poor people significantly affects the crime rate in Medan City. Policy implications include increased night light in vulnerable areas, access to green spaces, poverty alleviation, and improved security services to create a safer urban environment.]]>
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