Hu Chuanmin, Barnes Brian B, Qi Lin, Gower James F R, Jiao Junnan, Xie Yuyuan
College of Marine Science, University of South Florida, St. Petersburg, FL, 33701, USA.
College of Marine Science, University of South Florida, St. Petersburg, FL, 33701, USA.
Harmful Algae. 2025 Apr;144:102840. doi: 10.1016/j.hal.2025.102840. Epub 2025 Mar 17.
While pelagic Sargassum as a critical habitat to marine animals is known to be abundant in the Sargasso Sea, Gulf of Mexico, and the Caribbean Sea, attempts to detect this brown macroalgae from space did not start until 2006 when the proof of concept was demonstrated with medium-resolution satellite sensors. The annually recurrent Great Atlantic Sargassum Belt (GASB) since 2011 motivated efforts to develop new algorithms and approaches to detect and quantify Sargassum using data collected by various satellite sensors. This is mainly because of this macroalgae's harmful impacts on the coastal environments. Here, we review the principles and practices of using satellite remote sensing to map, quantify, and monitor pelagic Sargassum in the Atlantic Ocean. We first present the concept of how Sargassum can be detected, discriminated (against look-alikes), and quantified, where four types of data products are defined to meet the various needs. Then, we present the various published approaches in realizing such a concept using data collected by different satellite sensors. Following this concept and using recently developed algorithms and medium-resolution satellite data, we show the spatial distribution patterns and temporal changes of the GASB as well as a near real-time system to monitor Sargassum in the GASB. Finally, we discuss the gaps in the current technology and propose pathways forward to fill these gaps.
虽然作为海洋动物重要栖息地的浮游马尾藻在马尾藻海、墨西哥湾和加勒比海大量存在,但直到2006年利用中分辨率卫星传感器证明了概念验证后,才开始尝试从太空探测这种棕色大型藻类。自2011年以来每年都会出现的大西洋巨型马尾藻带(GASB)促使人们努力开发新的算法和方法,利用各种卫星传感器收集的数据来检测和量化马尾藻。这主要是因为这种大型藻类对沿海环境有有害影响。在此,我们回顾利用卫星遥感绘制、量化和监测大西洋浮游马尾藻的原理和实践。我们首先介绍如何检测、区分(与类似物区分)和量化马尾藻的概念,其中定义了四种类型的数据产品以满足各种需求。然后,我们介绍利用不同卫星传感器收集的数据实现这一概念的各种已发表方法。遵循这一概念并使用最近开发的算法和中分辨率卫星数据,我们展示了GASB的空间分布模式和时间变化以及一个监测GASB中马尾藻的近实时系统。最后,我们讨论当前技术中的差距并提出填补这些差距的前进途径。