Oil Spill Impacts on Mangrove Forest from Satellite Remote Sensing

Siti Sarah Farhana Ahmad, Nurul Hazrina Idris
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Abstract

The mangrove forest has been continuously threatened by oil spills occurring on the sea surfaces. The oil spills pose and cause severe and long-term effect havoc on mangrove forests that sustain them. Previous research has found that satellite remote sensing technologies are one of the most effective techniques to detect oil spills and assess the health of mangrove forests in contaminated areas. This study utilized the Synthetic-Aperture Radar (SAR) images from dualpolarized Sentinel-1 and Multi-Spectral Instrument (MSI) from Sentinel-2 to study the impact of oil spills on Mangrove Forest in Pantai Cermin, Negeri Sembilan. The Random Forest classification was used to detect the oil spill areas, while vegetation indices were used to assess the impact of oil pollution on mangrove forests in the early stages. Analysis from Sentinel1 imagery shows that the oil spill could be accurately detected using the Random Forest classifer with accuracy of 76%. Spectral indices: the normalized difference vegetation index (NDVI) was explored and evaluated to study the health of mangrove forest after the oil spills event. It is found that the oil spills have caused physical suffocation as well as toxicological effects to the mangrove forests.
从卫星遥感看溢油对红树林的影响
红树林一直受到海面石油泄漏的威胁。石油泄漏对维持它们的红树林造成了严重和长期的破坏。以前的研究发现,卫星遥感技术是探测石油泄漏和评估受污染地区红树林健康状况的最有效技术之一。本研究利用Sentinel-1的双偏振合成孔径雷达(SAR)图像和Sentinel-2的多光谱仪器(MSI)图像,研究了石油泄漏对森美兰州Pantai Cermin红树林的影响。采用随机森林(Random Forest)分类方法检测溢油区域,采用植被指数评估溢油污染对红树林的早期影响。对Sentinel1图像的分析表明,使用随机森林分类器可以准确地检测到溢油,准确率为76%。光谱指数:利用归一化植被指数(NDVI)研究溢油后红树林的健康状况。研究发现,石油泄漏对红树林造成了身体窒息和毒理学影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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