Open AccessNear real-time detection of abnormal vessels’ behaviours and vessel sourced pollution in Sri Lanka’s maritime zones: An investigation
Author(s) -
W. Kamal M. Mahindapala
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/509/1/012035
Subject(s) - sustainability , earth observation , marine pollution , environmental resource management , synthetic aperture radar , constellation , sri lanka , remote sensing , environmental science , marine ecosystem , satellite , pollution , geography , ecosystem , environmental planning , engineering , ecology , physics , tanzania , astronomy , biology , aerospace engineering
The largest ecosystems on Earth are the oceans and it is essential to conserve and sustainably use these vital resources. Waste created by the activities on land and sea, leads to the destruction of the ecosystems. As Sri Lanka is an island in the Indian Ocean, with rights to a vast sea area that extends from the shores, it is mandatory to sustainably manage its marine environment. Regular, systematic reviews of the state of marine environment provide an understanding of the various aspects of marine environment change and the implications for sustainability. Space borne platforms provide Earth observation data collected by different types of sensors, at regular intervals for the management of Earth environment. Earth observation data acquired with Synthetic Aperture Radar (SAR) technology has become useful for the detection of marine pollution during the day and night, regardless of cloud covers. However, availability of near real-time data is important for prompt detection and response. Revisit time of a satellite is an important factor and satellite constellations are used to further improve revisit times, for example, Copernicus Sentinel-1 satellite constellation can provide SAR data with a high revisit time. The research aims to explore the use of near real-time Sentinel-1 SAR data with automated mechanisms, for information extraction that supports early detection of abnormal vessels’ behaviours and vessel sourced pollution in Sri Lanka’s maritime zones.