ABSTRACT Recent advances in hyperspectral remote sensing using hundreds of spectral channels make it possible to derive oceanic variables and to understand the spatial distribution of diverse oceanic phenomena. In this study, hyperspectral measurements were obtained using airborne and ground experiments and hyperspectral data processing techniques were applied for the detection of vessels. The observed hyperspectral data were analysed by using the spectral characteristics of endmembers and a representative spectral mixture analysis technique. The pixels in the image were classified into endmembers by using spectral matching algorithms and the marine library spectra from preliminary experiments. The estimated lengths and widths of the detected ships based on a series of hyperspectral data processing methods show root mean square error (RMSE) of 2.28% and 8.72% with respect to actual ship sizes, respectively. The investigation of the errors revealed that undulating surface waves, surface water penetration of the deck, and the submerged portion of the ship below the water surface potentially contributes to unclear ship boundaries. In this study, an optimal method for the objective determination of the threshold of abundance fractions based on pixels with multiple endmember contributions is proposed. The validation results based on the proposed hyperspectral method are in good agreement with the actual sizes of the ships.

中文翻译：

---

基于机载和地面实验的高光谱遥感方法在舰船检测中的应用

摘要 使用数百个光谱通道的高光谱遥感的最新进展使得推导出海洋变量和了解不同海洋现象的空间分布成为可能。在这项研究中，高光谱测量是通过机载和地面实验获得的，并将高光谱数据处理技术应用于船只检测。观察到的高光谱数据通过使用端元的光谱特征和代表性光谱混合分析技术进行分析。通过使用光谱匹配算法和来自初步实验的海洋图书馆光谱，图像中的像素被分类为端元。基于一系列高光谱数据处理方法的检测到的船舶的估计长度和宽度显示均方根误差（RMSE）为2。实际船舶尺寸分别为 28% 和 8.72%。对错误的调查表明，起伏的表面波浪、甲板的地表水渗透以及船舶水面以下的淹没部分可能导致船舶边界不明确。本研究提出了一种基于多端元贡献像素客观确定丰度分数阈值的最优方法。基于所提出的高光谱方法的验证结果与船舶的实际尺寸非常吻合。船舶在水面以下的淹没部分可能会导致船舶边界不明确。本研究提出了一种基于多端元贡献像素客观确定丰度分数阈值的最优方法。基于所提出的高光谱方法的验证结果与船舶的实际尺寸非常吻合。船舶在水面以下的淹没部分可能会导致船舶边界不明确。本研究提出了一种基于多端元贡献像素客观确定丰度分数阈值的最优方法。基于所提出的高光谱方法的验证结果与船舶的实际尺寸非常吻合。