Detection of Oil Pollution along the Peruvian Coastline through the Use of Remote Sensing Technology
In the district of Ventanilla, within the constitutional Province of Callao, in the Department of Lima, an oil spill occurred near the La Pampilla Refinery, operated by the transnational company Repsol [coordinates: 12.216 S, -77.887 W to -11.005 S, -77.023 W]. To monitor and assess this hydrocarbon spill, a combination of remote sensing technologies was employed, including Sentinel-1, Sentinel-2, and PeruSAT-1.
Sentinel-1, a Synthetic Aperture Radar (SAR) satellite, is renowned for its ability to penetrate through clouds and operate during both day and night, making it ideal for monitoring oil spills in often cloudy or low-light maritime environments. SAR sensors detect oil spills by identifying calm areas on the water surface where oil dampens capillary waves, thus reducing radar backscatter and appearing as dark patches on SAR images [1]. Sentinel-1's high-resolution SAR imaging and near-real-time processing capabilities make it ideal for timely detection, monitoring, and change detection of hydrocarbon spills.
Sentinel-2, on the other hand, captures high-resolution multispectral optical images across visible and infrared bands. These images allow for detailed observation of surface features and water properties under clear sky and daylight conditions. Sentinel-2 can detect oil spills by identifying spectral signatures of hydrocarbons, which may alter water color or reflectance patterns. However, Sentinel-2 is limited by cloud cover and is not useful at night [1].
PeruSAT-1 provides very high-resolution optical imagery, suitable for detailed analysis of spill extent near coastlines and infrastructure like the La Pampilla Refinery. Like Sentinel-2, it depends on clear weather and daylight but offers finer spatial resolution for localized assessment, damage evaluation, and support for response efforts.
In the case of the La Pampilla Refinery oil spill, combining Sentinel-1's SAR data for continuous monitoring under all conditions with Sentinel-2 and PeruSAT-1's optical data for detailed surface characterization under clear conditions enables comprehensive spill detection, extent mapping, and damage assessment. This multimodal approach leverages the complementary strengths of radar and optical sensors to overcome individual limitations and produce a more complete picture of hydrocarbon spills [1].
This integrated use of remote sensing improves early detection, spill trajectory forecasting, environmental impact assessment, and informs timely response management. The materials used for this study included optimized workstations, Catalyst Professional Software, ArcGIS 10.8.1, SNAP 8.0, multispectral satellite images Sentinel-2, Peru-SAT-1, and Sentinel-1A radar. Due to a failure of the Sentinel 1B satellite, Sentinel 1A images were used with the IW acquisition mode and a GRD processing level.
[1] Source: [URL provided for reference]
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