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利用Landsat数据反演近岸海水表层温度的大气校正算法
引用本文:邢前国,陈楚群,施平.利用Landsat数据反演近岸海水表层温度的大气校正算法[J].海洋学报,2007,29(3):23-30.
作者姓名:邢前国  陈楚群  施平
作者单位:1.中国科学院, 烟台海岸带可持续发展研究所, 山东, 烟台, 264003;中国科学院, 南海海洋研究所, 热带海洋环境动力学重点实验室, 广东, 广州, 510301;广东省环境科学与技术公共实验室, 广东, 广州, 510650
基金项目:国家863项目(2002AA639130),广东省科技创新项目(2KB06701S)
摘    要:介绍了一种将大气效应考虑在内、利用Landsat TM、ETM+热红外数据进行近海岸海表水温反演的单窗算法.在该算法中,将地表气温、相对湿度等常规气象资料作为初始参数,根据对流层中大气温度随高度呈线性降低、水汽随高度呈指数衰减的规律,建立了估算平均大气温度及水汽含量的通用模式.通过与实测数据及MODIS Terra海表水温产品比较发现,该算法能够提高运用TM/ETM+TIR单波段数据进行近岸海表水温(SST)反演的精度:一方面,反演所得结果更接近于海表实际水温;另一方面,它在一定程度上剔除大气中的水汽对SST反演的影响,进而提高海表水温的温度对比度.该提出的大气校正算法只需地表大气温度及相对湿度资料,该算法也无需进行大气模式的界定.

关 键 词:海表水温    热红外    遥感    气温    湿度
文章编号:0253-4193(2007)03-0023-08
收稿时间:2006/5/25 0:00:00
修稿时间:2006-05-252007-03-02

Atmospheric correction of using Landsat data to retrieve sea surface temperature in coastal waters
XING Qian-guo,CHEN Chu-qun and SHI Ping.Atmospheric correction of using Landsat data to retrieve sea surface temperature in coastal waters[J].Acta Oceanologica Sinica (in Chinese),2007,29(3):23-30.
Authors:XING Qian-guo  CHEN Chu-qun and SHI Ping
Institution:1. Yantai Institute of Coastal Zone Research for Sustainable Development, Chinese Academy of Sciences, Yantai , 264003 China; 2. LED, South China Sea Institute of Oceanography, Chinese Academy of Sciences, Guangzhou 510301, China; 3. Guangdong Public Laboratory of Environmental Science and Technology, Guangzhou 510650, China
Abstract:A mono-window algorithm was introduced to retrieve Sea Surface Temperature(SST) using Landsat data in coastal waters.In this algorithm,the effective mean air temperature and the water vapor content of air column were estimated with the local meteorological parameters of air temperature and relative humidity,based on the facts in troposphere: 1,air temperature decrease linearly with the altitude,and 2,water vapor concentration lapses exponentially with the altitude.The sea-truth temperature data and MODIS Terra SST product were used to validate the SST retrieved from Landsat TM and ETM Thermal Infrared(TIR) data with the algorithm.The results show that the algorithm can improve the spatial temperature contrast which is often masked due to water vapor effects,and the temperature derived from the algorithm is closer to the sea-truth SST.When applying the algorithm,the initial parameters of air temperature and relative humidity can be easily collected from local meteorological stations,and there is no need to identify the model of air profile.
Keywords:sea surface temperature  thermal infrared  remote sensing  air temperature  humidity
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