Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis).
Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis).
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DOI：
10.1016/j.hal.2010.02.002
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发表时间：
2010-06-01
期刊：
影响因子：
6.6
通讯作者：
Baringer W
中科院分区：
文献类型：
--
作者：
Carvalho GA;Minnett PJ;Fleming LE;Banzon VF;Baringer W
为继续努力开发适用于利用卫星辐射计监测赤潮赤潮的方法，开发了一种新的多算法方法，以探索是否有可能改进对佛罗里达赤潮的遥感探测。介绍了一种混合方案，它顺序地应用了两种先前存在的基于卫星的算法的优化版本：一种经验方法(使用离水辐射作为叶绿素浓度的函数)和一种生物光学技术(使用颗粒后向散射和叶绿素浓度)。新的多算法方法的长期评估是使用一个多年的MODIS数据集(2002年至2006年；北方夏秋季-7月至12月)沿25.75°N至28.25°N的佛罗里达州中西部陆架进行的，算法的验证通过现场测量K.Brivis的丰度进行；细胞计数≥1.5×104细胞L−1定义了一个可检测的赤潮。当两种算法中的一种或两种算法正确地标记了已知样本时，就会得出令人鼓舞的统计结果。大多数有效匹配都被正确识别(HAB和非开花条件下约80%)，产生的假阴性或假阳性很少(每种情况下约20%)。此外，卫星数据中的大多数赤潮阳性鉴定确实是赤潮样本(阳性预测值：~70%)，而被归类为赤潮阴性的几乎都是非水华病例(阴性预测值：~86%)。这些结果显示了良好的检测能力，平均比单独使用的单个算法的准确率高10%。因此，新的混合计划可能成为监测赤潮环境的有力工具，其有价值的结果包括导致更快、更有效地利用船只对赤潮进行现场测量。
In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.
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影响因子：
8.2
作者：
Esaias, WE;Abbott, MR;Minnett, PJ
通讯作者：
Minnett, PJ
影响因子：
6.6
作者：
Heil, Cynthia A.;Steidinger, Karen A.
通讯作者：
Steidinger, Karen A.
影响因子：
2.9
作者：
Haywood, AJ;Steidinger, KA;MacKenzie, L
通讯作者：
MacKenzie, L
影响因子：
1.9
作者：
GORDON, HR;MCCLUNEY, WR
通讯作者：
MCCLUNEY, WR
DOI：
10.1186/1476-069x-7-s2-s5
发表时间：
2008-11-07
期刊：
Environmental health : a global access science source
影响因子：
--
作者：
Dyble J;Bienfang P;Dusek E;Hitchcock G;Holland F;Laws E;Lerczak J;McGillicuddy DJ Jr;Minnett P;Moore SK;O'Kelly C;Solo-Gabriele H;Wang JD
通讯作者：
Wang JD