<![CDATA[Illegal oil mining activities present significant environmental, economic, and regulatory challenges, particularly in resource-abundant regions that are difficult to monitor such as Musi Banyuasin Regency in South Sumatra. This study applied an integrated method that combines drone-based remote sensing, visual interpretation, and spatial statistical analysis to detect, map, and evaluate the spatial distribution of illegal shallow oil wells. High-resolution aerial imagery was acquired using DJI Phantom 4 Pro drones, processed into orthomosaic images, and interpreted visually to identify suspected well locations. A total of 2664 illegal oil wells were identified and georeferenced. The results of spatial autocorrelation analysis using Moran’s I indicated a clustered distribution pattern, with significant concentrations found in subdistricts such as Lawang Wetan, Batang Hari Leko, and Tungkal Jaya. The Moran’s I index value of 0.652075 confirmed a statistically significant spatial clustering. Ground validation was conducted through direct field surveys, which verified the presence of the wells and provided supporting photographic documentation and GPS coordinates. The dataset was also compared with official records of legal oil wells to ensure accuracy and distinction between legal and illegal infrastructure. The findings demonstrate that unmanned aerial vehicle-based spatial analysis offers a reliable and scalable solution for monitoring unregulated extraction activities. This approach supports data-driven enforcement, enhances environmental oversight, and informs the development of more effective regulatory policies in regions impacted by informal oil production.]]>
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