Application of C-band sentinel-1A SAR data as proxies for detecting oil spills of Chennai, East Coast of India.

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 capability, 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 availability 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 first 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 classifiers SVM and NN were applied on the boxcar filtered 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 classifiers. The results show there is a good agreement between oil spill mapping and classified image using SVM and NN classified images. The Overall Accuracy (OA) obtained using SVM classifier is 98.13% with kappa coefficient as 0.95 and using NN classifier is 98.11% with kappa coefficients 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 first 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.

Assessment of a naturally occurring high background radiation area with elevated levels of thorium along coastal Odisha, India using radiometric methods.

The present study evaluates the enrichment and distribution of radioelements along the eastern coast of India. India possesses the second largest reserve of thorium bearing monazite in the world, in terms of heavy minerals present primarily along its long coastline. Radioelement estimation of about 30 km long beach area along the eastern coast of India is reported and implications discussed. A total number of 822 data points were studied using a portable Geiger Muller counter, to estimate the variation of dose rates, due to the ambient radionuclides along two different trends. One was parallel (northeast-southwest) and the second one perpendicular to the coastline. Pre-selected samples from in-situ radiometric surveys on the heavy mineral placers were studied further, for quantitative estimation of the abundance of radioactive elements primarily uranium and thorium, using a High Purity Germanium detector. Radioelement concentration assessment of core samples (depth ~2 m), were studied from two different beaches. Radiological parameters like radium equivalent, annual effective doserate and absorbed dose rate has been calculated based on the 238U, 232Th and 40K concentrations. Heavy mineral placers along the shoreline indicate a very high thorium (avg - 2990.22 Bq kg-1) which is due to the extensive distribution indicative of monazite. The coastal area also exhibits relatively low uranium (avg - 319.1 Bq kg-1). Based on its high thorium concentration, the area can be considered as a high natural background radiation area. Based on the concentrations of uranium and thorium, the weathering conditions and depositional environment prevalent along the beach areas have been discussed.