赤潮是在特定的环境条件下，海水中某些浮游植物、原生动物或细菌爆发性增殖或高度聚集而引起水体变色的一种常见的海洋生态灾难。目前，赤潮监测的手段主要包括船舶定点监测、监测站监测以及航空和卫星遥感监测。其中，卫星遥感监测因具有监测范围大、监测信息全面的特点，而被广泛使用。本文基于5种可以指示赤潮爆发的子指数及其综合方式，提出了一种可用于多光谱卫星图像中赤潮识别的线性综合识别指数(LCI)方法。基于大连市星海湾现场实测的多日内赤潮连续监测光谱数据，开展了支持向量机与逻辑回归分类，并得到分类平面系数作为归一化的子指数组合权重，获得了两种最佳的赤潮识别指数组合方式。这两种方式在验证集上均取得了F1分数0.86以上的分类效果，且LCI数值与赤潮发生的概率也呈现正相关。本文进一步将得到的分类系数应用于多光谱卫星图像的赤潮像元提取，结果显示两种线性综合指数均在图像中成功提取出赤潮区域。本文提出的赤潮综合识别指数为遥感图像中的赤潮识别提供了新的光谱指数运算方法。

Red tide is a common marine ecological disaster caused by the explosive proliferation or high aggregation of certain phytoplankton, protozoa, or bacteria in seawater under specific environmental conditions, leading to discoloration of the water. At present, the main methods for monitoring red tide include fixed-point monitoring of ships, monitoring stations, and aerial and satellite remote sensing monitoring. Among them, satellite remote sensing monitoring is widely used due to its wide monitoring range and comprehensive monitoring information. This article proposes a linear comprehensive identification index (LCI) method for red tide identification in multispectral satellite images based on five sub indices and their comprehensive methods that can indicate red tide outbreaks. Based on the multi day continuous monitoring spectral data of red tide in Xinghai Bay, Dalian City, support vector machine and logistic regression classification were carried out, and the classification plane coefficients were obtained as normalized sub index combination weights. Two optimal combinations of red tide identification indices were obtained. Both methods achieved classification results with an F1 score of 0.86 or higher on the validation set, and the LCI value showed a positive correlation with the probability of red tide occurrence. This article further applies the obtained classification coefficients to the extraction of red tide pixels in multispectral satellite images, and the results show that both linear composite indices have successfully extracted red tide areas in the images. The comprehensive identification index of red tide proposed in this article provides a new spectral index calculation method for red tide identification in remote sensing images.