光谱学与光谱分析, 2019, 39 (8): 2462, 网络出版: 2019-09-02  

基于野外实测数据的珊瑚礁不同底质光谱可分性及珊瑚色素影响分析

The Analysis of Spectral Separability of Different Coral Reef Benthos and the Influence of Pigments on Coral Spectra Based on in Situ Data
作者单位
国家海洋环境监测中心, 辽宁 大连 116023
摘要
珊瑚礁遥感监测的任务之一是获取底栖物质的组成及分布, 但由于珊瑚礁存在较强的空间异质性及复杂的光谱, 使得目前利用遥感技术进行底栖物质信息提取还存在较大难度。 珊瑚礁不同底栖物质的光谱特性是开展珊瑚礁遥感监测的基本先验知识, 但目前关于不同珊瑚种类的光谱特性分析研究较为匮乏。 本研究基于野外实测光谱数据和模拟卫星遥感数据, 开展珊瑚礁不同底质类型的光谱特性研究, 特别是针对不同造礁石珊瑚种间及种内的光谱差异进行比较分析, 并探讨不同珊瑚体内色素组成对珊瑚光谱特性的影响研究, 最后甄选了四种常用卫星数据, 通过数值模拟探讨了不同底质类型的光谱可分性。 结果显示, 利用反射光谱曲线值的大小能较好的识别沙和白化珊瑚, 而利用蓝绿红波段反射率的一阶微分值能有效识别出海藻、 海草和健康珊瑚。 对于不同种类的珊瑚而言, 科、 属、 种、 珊瑚形状、 珊瑚颜色的不同均会对珊瑚的反射光谱造成影响。 叶绿素含量(包含叶绿素a、 叶绿素b、 叶绿素c)与珊瑚反射光谱值相关性较好, 是影响珊瑚光谱反射率的主要因素之一, 虫黄藻密度在一定程度上也能影响珊瑚光谱反射率, 但不如叶绿素影响明显, 其密度的高低会影响珊瑚光谱在局部波段的峰值特征。 在目前常用的多光谱卫星数据中, Landsat8数据具有可观测近岸的蓝波段, 具备识别沙、 白化珊瑚、 海藻、 健康珊瑚、 海草的能力, 而IKONOS和Quickbird可识别沙、 白化珊瑚和海草。 相对而言, SPOT5表现较差, 仅能识别沙和白化珊瑚。 在不同种类珊瑚的识别方面, 多光谱遥感数据由于无法捕捉特征波段, 需要采用具有高空间分辨率的高光谱遥感数据进行有效识别。 在今后的工作中, 将进一步扩大珊瑚礁底质样本数据集, 并建立珊瑚礁光谱库, 为今后我国珊瑚礁遥感监测体系建立提供数据支撑。
Abstract
One task of coral reef remote sensing is to obtain the composition and distributionof benthic categories. However, there is still a great deal of uncertainty anddifficulty to discriminate reef benthos by means of remote sensing owing to thespatial heterogeneity and complicated spectrum of coral reef. Spectral characteristics of different coral reef benthos are the basic prior knowledge for remote sensing of coral reefs. Based on in situ spectral data and simulated satellite data, this paper analyzed the spectral characteristics of different coral reef benthos, especially the spectral properties of different coral types. The influence of coral pigments on coral spectra was also analysed. Finally, four kinds of commonly used satellite data(Landsat 8, IKONOS, Quickbird and SPOT 5) were simulated to investigate the spectral separability of different reef benthos from space. Results showed that sand and bleached corals could be easily identified by the reflectance curves in the visible bands. The first-order spectral derivation in visible bands was a good way to distinguish algae, seagrass and healthy corals. The differences of families, genera, species, coral shapes and coral colors would have obvious impact on the spectral characters of corals. In addition, Chlorophyll contents (including Chlorophyll-a, Chlorophyll-b and Chlorophyll-c) had high correlativity with reflectance of corals, which would exert notable influence on coral spectral features. Zooxanthella had the similar influence, but not as obviously as that of chlorophyll. Its density would affect the peak features of coral reflectance. Among the commonly used multi-spectral satellite data, Landsat 8 had the ability to distinguish sand, bleached corals, algae, healthy corals and seagrass owing to its coastal band, while IKONOS and Quickbird could identify sand, bleached corals and seagrass. Comparatively, SPOT5 had a poor performance, which could only identify sand and bleached corals. However, in the identification of different types of corals, multi-spectral satellite data failed to capture the elaborated spectral features and hyperspectral data with high spatial resolution was needed for effective identification. In the future work, we will further expand more coral reef benthos samples and establish the spectral database of coral reef to provide the data support for the establishment of coral reef monitoring system in China.

徐京萍, 李方, 孟庆辉, 王飞. 基于野外实测数据的珊瑚礁不同底质光谱可分性及珊瑚色素影响分析[J]. 光谱学与光谱分析, 2019, 39(8): 2462. XU Jing-ping, LI Fang, MENG Qing-hui, WANG Fei. The Analysis of Spectral Separability of Different Coral Reef Benthos and the Influence of Pigments on Coral Spectra Based on in Situ Data[J]. Spectroscopy and Spectral Analysis, 2019, 39(8): 2462.

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