Institute of Oceanology, Chinese Academy of Sciences, 7 Nanhai Road, Qingdao 266071, China; Fisheries and Oceans Canada, Bedford Institute of Oceanography, 1 Challenger Drive, Dartmouth B2Y 4A2, Canada; Key Laboratory of Ocean Circulation and Waves, Chinese Academy of Sciences, 7 Nanhai Road, Qingdao 266071, China.
Fisheries and Oceans Canada, Bedford Institute of Oceanography, 1 Challenger Drive, Dartmouth B2Y 4A2, Canada.
Mar Pollut Bull. 2014 Jan 15;78(1-2):190-5. doi: 10.1016/j.marpolbul.2013.10.044. Epub 2013 Nov 14.
Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.
绿藻水华的频繁发生及其对海洋环境和人类社会造成的严重破坏,要求我们采用改进的高分辨率早期检测方法。传统的基于光谱辐射计的卫星遥感方法在云层覆盖的区域无法正常工作,因此无法满足这些业务应用的需求。我们提出了一种基于 RADARSAT-2 合成孔径雷达(SAR)图像的绿藻水华检测方法。与开阔海面相比,绿藻斑块在 SAR 测量的复雷达后向散射回波的幅度和相位域中表现出不同的极化特性。在本研究中,定义了新的指数因子,它们在绿藻覆盖区域的符号与开阔水面相反。这些指数因子可以从 SAR 图像中进行无监督检测,为绿藻水华的检测提供了一种高分辨率的新工具,这可能有助于更好地理解全球海洋沿岸绿藻水华爆发的相关机制。