Optical interpretation of oil emulsions in the ocean - Part II: Applications to multi-band coarse-resolution imagery
Optical interpretation of oil emulsions in the ocean - Part II: Applications to multi-band coarse-resolution imagery
复制标题
海洋中油乳剂的光学解释 - 第二部分：多波段粗分辨率图像的应用
DOI：
10.1016/j.rse.2020.111778
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发表时间：
2020
影响因子：
13.5
通讯作者：
Liu Yongxue
中科院分区：
文献类型：
--
作者：
Lu Yingcheng;Shi Jing;Hu Chuanmin;Zhang Minwei;Sun Shaojie;Liu Yongxue
海洋溢油中油包水（WO）和油包水（OW）乳剂具有不同的物理性质、体积浓度和光谱特征。识别和量化这些不同类型的油乳剂对溢油响应和溢油后评估具有重要意义。虽然在包括本系列第一部分在内的先前研究中已经介绍了WO和OW乳剂的光谱特性，但本文将进一步展示它们在航空和卫星图像中的应用。利用AVIRIS和Landsat观测，我们首先发现，来自类似Landsat传感器的假色红绿蓝合成图像（R: 1677 nm, G: 839 nm, B: 660 nm）可以有效区分WO和OW乳剂，因为它们在合成图像中分别显示为红色和绿色。这是WO和OW乳剂在1677 nm和839 nm处反射率相对差异的结果，不受中等强度的太阳光反射或中等分辨率像素（例如30 m）内表面不均匀性的影响。基于图像统计，提出了一种决策树方法对油类进行分类，并进一步尝试油类量化，通过光谱分析和空间相干性测试对结果进行了部分验证。利用AVIRIS像元进行的数值混合实验进一步表明，一旦将粗分辨率油污像元分类为WO和OW类型，SWIR波段可以用于建立线性解混模型，1295 nm是对混合粗分辨率像元进行光谱解混的最佳波长。
Water in oil (WO) and oil in water (OW) emulsions from marine oil spills have different physical properties, volume concentrations, and spectral characteristics. Identification and quantification of these different types of oil emulsions are important for oil spill response and post-spill assessment. While the spectral characteristics of WO and OW emulsions have been presented in previous studies including Part I of this series, their application to airborne and satellite imagery is further demonstrated here. Using AVIRIS and Landsat observations, we firstly show that false color Red-Green-Blue composite images from Landsat-like sensors (R: 1677 nm, G: 839 nm, B: 660 nm) are effective in differentiating WO and OW emulsions as they show reddish and greenish colors, respectively, in such composite images. This is a consequence of the relative difference in the reflectance of WO and OW emulsions at 1677 and 839 nm, which is not impacted by the presence of medium-strength sunglint or the surface heterogeneity within medium-resolution pixels (e.g., 30 m). Based on image statistics, a decision tree method is proposed to classify oil type, and oil quantification is further attempted, with results partially validated through spectral analysis and spatial coherence test. The numerical mixing experiments using AVIRIS pixels further indicate that the SWIR bands might be used to develop linear unmixing models in the future once the coarse-resolution oiled pixels are first classified to WO and OW types, and 1295 nm is the optimal wavelength to perform spectral unmixing of mixed coarse-resolution pixels.