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首页> 外文期刊>Remote Sensing >Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques
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Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques

机译：利用神经网络及其与其他技术的比较，对西佛罗里达大陆架上的短小克雷氏菌有害藻华进行卫星检索

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We describe the application of a Neural Network (NN) previously developed by us, to the detection and tracking, of Karenia brevis Harmful Algal Blooms ( KB HABs) that plague the coasts of the West Florida Shelf (WFS) using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite observations. Previous approaches for the detection of KB HABs in the WFS primarily used observations from the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A) satellite. They depended on the remote sensing reflectance signal at the 678 nm chlorophyll fluorescence band ( Rrs 678) needed for both the normalized fluorescence height (nFLH) and Red Band Difference algorithms (RBD) currently used. VIIRS which has replaced MODIS-A, unfortunately does not have a 678 nm fluorescence channel so we customized the NN approach to retrieve phytoplankton absorption at 443 nm ( a ph 443 ) using only Rrs measurements from existing VIIRS channels at 486, 551 and 671 nm. The a ph 443 values in these retrieved VIIRS images, can in turn be correlated to chlorophyll- a concentrations [ Chla ] and KB cell counts. To retrieve KB values, the VIIRS NN retrieved a ph 443 images are filtered by applying limiting constraints, defined by (i) low backscatter at Rrs 551 nm and (ii) a minimum a ph 443 value known to be associated with KB HABs in the WFS. The resulting filtered residual images, are then used to delineate and quantify the existing KB HABs. Comparisons with KB HABs satellite retrievals obtained using other techniques, including nFLH, as well as with in situ measurements reported over a four year period, confirm the viability of the NN technique, when combined with the filtering constraints devised, for effective detection of KB HABs.
机译：我们描述了先前由我们开发的神经网络（NN）在探测和跟踪使用可见光红外成像辐射计套件困扰西佛罗里达州大陆架（WFS）的短小卡氏藻有害藻华（KB HAB）中的应用。 （VIIRS）卫星观测。 WFS中检测KB HAB的先前方法主要是使用中分辨率成像光谱仪Aqua（MODIS-A）卫星的观测结果。它们取决于当前使用的归一化荧光高度（nFLH）和红色谱带差异算法（RBD）所需的678 nm叶绿素荧光带（Rrs 678）的遥感反射率信号。不幸的是，已替代MODIS-A的VIIRS没有678 nm荧光通道，因此我们仅使用来自现有VIIRS通道在486、551和671 nm的Rrs测量值，定制了NN方法来检索443 nm（ph 443）的浮游植物吸收。这些检索到的VIIRS图像中的ph 443值又可以与叶绿素a浓度[Chla]和KB细胞计数相关。为了检索KB值，通过应用限制约束对VIIRS NN检索的ph 443图像进行滤波，该限制由（i）Rrs 551 nm处的低反向散射和（ii）已知与KB HAB相关的最小ph 443值定义。世界粮食首脑会议。然后将所得的滤波后残留图像用于描述和量化现有KB HAB。与使用包括nFLH在内的其他技术获得的KB HAB卫星检索结果的比较，以及四年期间报告的原位测量结果，证实了NN技术的可行性，结合设计的过滤约束条件，可以有效地检测KB HAB 。

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