Computational Techniques of Oil Spill Detection in Synthetic Aperture Radar Data: Review Cases

Abstract

In this chapter, a major role of environmental assessment is an oil spill identifies or detected from the coastal region surfaces or marine surroundings. Normally, the oil spills on the coastal regions impact their characteristics of environmental activities. However, these activities are monitoring through several radar satellites and sensor. For those achievable activities detecting or identifying, many researchers developed several approaches. Particularly, this chapter discusses about the detection of oil spill current operational effects on coastal region surfaces. In addition, the current research operations of oil spill characterizations and quality of its impacts, effects of current environmental bio-systems, their control measurement strategies, and its surveillance operations are discussed. Finally, the oil spill detection is done through the SAR image region classification based on its feature extraction. This could be monitored from the image dark region selection through remote sensing techniques.

Satellite imagery in evaluating oil spill modelling scenarios for the Syrian oil spill crisis, summer 2021

“…Currently, machine learning techniques based on various classifiers (e.g., decision trees, random forests, etc.) have been widely applied to aid oil detection (Vijayakumar, 2023). Technical details and method limitations using SAR images for detection of oil spill are referred in Fingas and Brown (2018) and Dong et al, (2022 Supplementary Materials).…”