Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.
Remote Sensing Group, Plymouth Marine Laboratory (PML), Plymouth, Devon, United Kingdom.
PLoS One. 2019 Apr 16;14(4):e0215463. doi: 10.1371/journal.pone.0215463. eCollection 2019.
Harmful Algal Blooms (HABs) are of global concern, as their presence is often associated with socio-economic and environmental issues including impacts on public health, aquaculture and fisheries. Therefore, monitoring the occurrence and succession of HABs is fundamental for managing coastal regions around the world. Yet, due to the lack of adequate in situ measurements, the detection of HABs in coastal marine ecosystems remains challenging. Sensors on-board satellite platforms have sampled the Earth synoptically for decades, offering an alternative, cost-effective approach to routinely detect and monitor phytoplankton. The Red Sea, a large marine ecosystem characterised by extensive coral reefs, high levels of biodiversity and endemism, and a growing aquaculture industry, is one such region where knowledge of HABs is limited. Here, using high-resolution satellite remote sensing observations (1km, MODIS-Aqua) and a second-order derivative approach, in conjunction with available in situ datasets, we investigate for the first time the capability of a remote sensing model to detect and monitor HABs in the Red Sea. The model is able to successfully detect and generate maps of HABs associated with different phytoplankton functional types, matching concurrent in situ data remarkably well. We also acknowledge the limitations of using a remote-sensing based approach and show that regardless of a HAB's spatial coverage, the model is only capable of detecting the presence of a HAB when the Chl-a concentrations exceed a minimum value of ~ 1 mg m-3. Despite the difficulties in detecting HABs at lower concentrations, and identifying species toxicity levels (only possible through in situ measurements), the proposed method has the potential to map the reported spatial distribution of several HAB species over the last two decades. Such information is essential for the regional economy (i.e., aquaculture, fisheries & tourism), and will support the management and sustainability of the Red Sea's coastal economic zone.
有害藻华（HABs）是全球性关注的问题，因为它们的存在通常与社会经济和环境问题相关，包括对公共健康、水产养殖和渔业的影响。因此，监测 HAB 的发生和演替对于管理世界各地的沿海地区至关重要。然而，由于缺乏足够的现场测量，沿海海洋生态系统中 HAB 的检测仍然具有挑战性。卫星平台上的传感器已经对地球进行了几十年的综合采样，为常规检测和监测浮游植物提供了一种替代的、具有成本效益的方法。红海是一个大型海洋生态系统，其特点是广泛的珊瑚礁、高生物多样性和特有性以及不断增长的水产养殖业，是一个对 HAB 了解有限的地区。在这里，我们使用高分辨率卫星遥感观测（1km，MODIS-Aqua）和二阶导数方法，结合可用的现场数据集，首次研究了遥感模型在红海检测和监测 HAB 的能力。该模型能够成功地检测和生成与不同浮游植物功能类型相关的 HAB 地图，与同期的现场数据非常吻合。我们还承认使用遥感方法的局限性，并表明无论 HAB 的空间覆盖范围如何，当 Chl-a 浓度超过约 1mg m-3 的最小值时，该模型才能够检测到 HAB 的存在。尽管在较低浓度下检测 HAB 以及识别物种毒性水平存在困难（仅通过现场测量才能实现），但该方法有可能绘制过去二十年报告的几种 HAB 物种的空间分布。这些信息对于区域经济（即水产养殖、渔业和旅游业）至关重要，并将支持红海沿海经济区的管理和可持续性。
