Synergistic application of Sentinel 1 and Sentinel 2 derivatives for terrestrial oil spill impact mapping

M. S. Ozigis; J. Kaduk; C. Jarvis

doi:10.1117/12.2325107

20 November 2018 Synergistic application of Sentinel 1 and Sentinel 2 derivatives for terrestrial oil spill impact mapping

M. S. Ozigis, J. Kaduk, C. Jarvis

Author Affiliations +

Proceedings Volume 10788, Active and Passive Microwave Remote Sensing for Environmental Monitoring II; 107880R (2018) https://doi.org/10.1117/12.2325107
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Terrestrial Oil spills pose serious health risk to human lives from indirect ingestion of contaminated drinking water, aquatic products and on contaminated farmland produce. Spill impact mapping is essential in establishing the extent of damage by oil spills to inland vegetation. It also helps ascertaining the type of environmental remediation required for a particular landcover. Various detection methods have been reported in the literature's ranging from radiative transfer models, vegetation health indices, canopy water use efficiency and UAVSAR Polarimetric Backscatter Decomposition among several others. These approach in isolation cannot be effectively used in wide area mapping and discrimination of oil free from oil polluted landcover. Similarly, it is also necessary to develop transferable techniques that will leverage freely accessible space borne satellite data for consistent spill impact mapping in near real time. In this study, we integrated derivatives from the freely accessible sentinel 2 spectral reflectance and vegetation health indices, with sentinel 1 retrieved backscatter, alpha (α) and entropy (Η) scatter to examine and map oil spill impacted areas within terrestrial habitat. The utility of machine learning random forest was explored to assess classification accuracies. Initial results suggest that the Red Edge and SWIR Bands of Sentinel 2 are vital discriminators of oil polluted and oil free landcover.

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M. S. Ozigis, J. Kaduk, and C. Jarvis "Synergistic application of Sentinel 1 and Sentinel 2 derivatives for terrestrial oil spill impact mapping", Proc. SPIE 10788, Active and Passive Microwave Remote Sensing for Environmental Monitoring II, 107880R (20 November 2018); https://doi.org/10.1117/12.2325107

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KEYWORDS

Vegetation

Image classification

Short wave infrared radiation

Image processing

Infrared radiation

Accuracy assessment

Near infrared

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