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机构地区:[1]福建省海洋环境科学联合重点实验室(厦门大学) [2]厦门大学海洋与环境学院,福建厦门361005
出 处:《厦门大学学报(自然科学版)》2011年第6期1037-1041,共5页Journal of Xiamen University:Natural Science
基 金:国家自然科学基金项目(40876031);国家高技术研究发展计划(863)项目(2006AA09A302;2007AA09Z127)
摘 要:太阳耀光水体和水云的光谱相似性导致绝大部分多光谱遥感图像云检测算法的太阳耀光信号误识别.选取对耀光水体、非耀光水体、水云、冰云光谱信息差异性和敏感性最大的红光波段及中红外波段,结合上述4类分类对象的遥感统计数据,从黑体辐射理论和云粒子微观物理性质出发,分析二维特征空间中不同类型水体和云层的辐射分布差异,提出利用多光谱遥感数据AVHRR识别不同类型水体和云层的红光-中红外光谱普适性分类模型.该分类模型对于多光谱遥感数据具有广泛适用性,可作为发展多光谱识别分类自动化算法的基础.Sea surface sunglint contains useful oceanic information,even the sunglint signal could be used for atmospheric components inversion.Sunglint water area and water cloud area in the images have similar characteristics with high brightness temperature and high reflectance.This phenomenon usually causes misrecognition of sunglint signal in remote sensing images,using traditional multispectral cloud detection algorithms.In order to resolve the problem,the present study structured a two-dimensional model using a red light band at the wavelength of 0.63 μm and a middle infrared band at the wavelength of 3.74 μm.The former could discriminate the clear sky and the cloud,and the latter could enhance the spectral differences between sunglint water area and water cloud area.The model was built on the basis of the scatter plot which is assemble with training samples of typical sunglint water area,non sunglint water area,water cloud area and ice cloud area,and according to the black body radiation theory and the micro-physical properties of the cloud particle,different areas could be separated.The model proposed in the present study affords a flexible method that can be used to recognize different water areas and cloud areas with remote sensing data from multispectral sensors e.g.AVHRR,and it is helpful to develop the automatic recognition algorithm with multispectral data.
分 类 号:X87[环境科学与工程—环境工程]
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