Marine Pollution Bulletin 174 (2022) 113182 0025-326X/© 2021 Elsevier Ltd. All rights reserved. Application of C-band sentinel-1A SAR data as proxies for detecting oil spills of Chennai, East Coast of India Kiran Dasari a , Lokam Anjaneyulu b , Jayaraju Nadimikeri c, * a Dept of Electronics and communication, MLR Institute of Technology, Hyderabad, India b Department of Electronics and Communication, National Institute of Technology Warangal, Telangana, India c Department of Geology, Yogi Vemana University, Kadapa, Andhra Pradesh, India A R T I C L E INFO Keywords: Synthetic aperture radar (SAR) Radar remote sensing Sentinel-1A Supervised classifer Chennai oil spill accident East Coast of India ABSTRACT This paper presents the utilization of Synthetic Aperture Radar (SAR) data for monitoring and detection of oil spills. In this work, a case study of an oil spill has been investigated using C-band Sentinel-1A SAR data to detect the oil spill that occurred on 28 January 2017, near Ennore port, Chennai, India. Oil spill damages marine ecosystems causing serious environmental effects. Quite often, oil spills on the sea/ocean surface are seen nowadays, mainly in major shipping routes. They are caused due to tanker collisions, illegal discharge from the ships, etc. An oil spill can be monitored and detected using various platforms such as vessel-based, airborne- based and satellite-based. Vessel based and airborne methods are expensive with less area coverage. This process also consumes more time. For ocean applications such as oil spill and Ship detection, optical sensors cannot image during bad weather. As SAR is an active sensor, weather independent, and has cloud penetrating capa- bility, the images can be acquired during the day as well as at night. Radar Remote Sensing (RRS) has rapidly gained popularity for monitoring and detection of oil spills and ships for more than a decade. With the avail- ability of the satellite images, detection of oil spill has improved due to its wide coverage and less revisit time. The present paper gives an overview of the methodologies used to detect oil spills on the SAR images using dual- pol Sentinel-1A Level 1 SLC data. This work clearly demonstrates the preprocessing steps of the Sentinel 1A data for oil spill detection. The oil spill was only visible in the VV channel, therefore, for ocean application VV channel image is preferred. SEASAT was the frst space-borne SAR mission launched in 1978 by NASA to observe sea surface. The preprocessing was carried out at the European Space Agency (ESA), the Sentinel Application Platform (SNAP) toolbox and Envi 5.1 toolbox. Based on the Sigma naught values, oil spill can be discriminated with the ocean surface. The results obtained with the VV channel are satisfactory and one could map out the oil spill very well. Supervised classifers SVM and NN were applied on the boxcar fltered 3 × 3 VV channel image to delineate the oil spill. The result of oil spill detection mapping is validated with Supervised SVM and Neural Network classifers. The results show there is a good agreement between oil spill mapping and classifed image using SVM and NN classifed images. The Overall Accuracy (OA) obtained using SVM classifer is 98.13% with kappa coeffcient as 0.95 and using NN classifer is 98.11% with kappa coeffcients 0.95. This technique is considered to be a potential proxy for the detection and monitoring of Oil spills on water bodies. Application of SAR data for oil spill detection is considered to be frst of its kind from Indian coasts. This study aims to detect the oil spill occurred due to collision of two LPG tankers with Sentinel-1A SLC data in Chennai coast area. 1. Introduction Two tankers carrying Liquefed Petroleum Gas (LPG) by BW Maple tanker and Dawn Kanchipuram tanker collided near Ennore Port Chennai on 28 January 2017, resulting in an oil spill on the Coromandel Coast, South India. The oil spill affected the marine life, as many turtles and fsh were found dead and washed ashore, destroying the marine habitat (Han et al., 2018). Oil Spills are one of the forms of marine pollution, directly affecting marine ecosystems. Thus oil spill detection and monitoring draw the priority. Space-borne-based SAR systems are effective in detecting and monitoring oil spills. Oil spills affect the delicate ecosystem such as fshes, turtles, sea creatures, and sea birds. * Corresponding author. E-mail address: nadimikeri@gmail.com (J. Nadimikeri). Contents lists available at ScienceDirect Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul https://doi.org/10.1016/j.marpolbul.2021.113182 Received 28 September 2021; Received in revised form 15 November 2021; Accepted 20 November 2021