International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLIII-B1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 627–630, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-627-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 627–630, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-627-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Aug 2020

06 Aug 2020

BILGE DUMP AUTOMATIC ALERT SYSTEM IN SOUTHERN AFRICA OCEANS

L. W. Mdakane, R. G. V. Meyer, and B. Sibolla L. W. Mdakane et al.
  • Spatial Information Systems, e-Government, NextGen Enterprises and Institutions, CSIR, Pretoria, South Africa

Keywords: Bilge Waste Dumping, Oil Spill, Oceans, Image Classification, Synthetic Aperture Radar

Abstract. Oil spill over the sea surface formed because of oil-tanker accidents or illegal bilge dumping of tankers can cause significant environmental damage depending on the location and amount. The international legislation contains minor and well-defined exceptions related to ocean areas (internal waters, marine protected areas, MARPOL “special” areas, territorial seas or exclusive economic zones). These areas often determine whether or not an action is considered legal/illegal and define the rights and obligations, including law enforcement obligations. Deliberated oil spill are often caused by vessels illegally discharging oily waste during cleaning operations. To minimise the ecological impact caused by the oil spill, a rapid response from the authorities is required. To facilitate the quick response, we propose an automated bilge dump alert system based on space-borne SAR analysis over Southern Africa oceans. The proposed alert system detects potential bilge dumps and classifies them according to confidence and alert levels. The confidence levels described the quality of the detected bilge dump, based on the probability measures of the observed bilge candidates. The alert levels described the enormity of the alert based on the detection location and confidence level. The system showed promising results in classifying bilge dumps according to the alert level.