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遥感技术与应用  2020, Vol. 35 Issue (1): 132-140    DOI: 10.11873/j.issn.1004-0323.2020.1.0132
模型与反演     
利用MODIS数据反演南海南部海表温度及时空变化分析
郑贵洲(),熊良超,廖艳雯,王红平
中国地质大学 地理与信息工程学院, 湖北 武汉 430074
Sea Surface Temperature Inversion of the Southern South China Sea from MODIS and Temporal and Spatial Variation Analysis
Guizhou Zheng(),Liangchao Xiong,Yanwen Liao,Hongping Wang
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
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摘要:

南海海水表面温度对中国陆地的气候变化具有显著的影响。以南海南部海域为例,首先对MODIS基础数据进行几何校正及影像去云等预处理,利用辐射传输模型MODTRAN计算大气透过率,利用MODIS数据第31和32波段辐射亮度值计算亮度温度,采用劈窗算法反演南海南部海域海表温度,反演结果与产品及实测数据进行回归分析,采取决定系数(R 2)、误差平方和(SSE)及均方根误差(RMSE)进行拟合情况评价。决定系数(R 2)大于0.8,SSE、RMSE较小,其中反演结果与实测数据的SSE为1.025,RMSE为0.158,说明反演精度良好。研究表明:温度具有明显的区域和季节变化特征,秋冬较低,春夏较高,在空间上从离近岸向中心海域方向递减,海盆中心温度低。温度受气候的影响,与厄尔尼诺现象呈正相关,与拉尼娜现象呈负相关。

关键词: 南海南部海域MODIS海表温度反演劈窗算法温度时空变化    
Abstract:

The sea surface temperature in the southern South China Sea has a significant influence on the climate change of China land. In the paper, on the basis of the geometric correction and cloud removal of MODIS basic data in the southern South China Sea, the atmospheric transmittance was calculated by MODTRAN Model, and the brightness temperature was calculated by the radiance intensity of the MODIS 31, 32 channels. The split-window algorithm was used to retrieve the sea surface temperature in the southern South China Sea. Finally, the accuracy was evaluated byR 2, SSE, RMSE and the regression analysis between retrieved temperature and the products temperature or ground measured temperature.R 2 is lager than 0.8. SSE and RMSE are all smaller. The inversion accuracy is good. The research showed the distinct seasonal variation of lower temperature in autumn and winter and higher temperature in spring and summer. The research still showed the fundamental variation of temperature with declines from the near shore to the center of the sea, and lowest temperature over the deep basin. The sea surface temperature was affected by variations of weather. The sea surface temperature was positively correlated with El Ni?o, and was negatively correlated with La Ni?a.

Key words: Southern South China Sea    MODIS    Sea surface temperature inversion    Split-window algorithm    Temporal and spatial temperature variation
收稿日期: 2018-10-12 出版日期: 2020-04-01
ZTFLH:  TP79  
基金资助: 海洋地质保障工程“南海北部陆坡油气资源调查技术应用研究”项目之研究专题(GZH201200508)
作者简介: 郑贵洲(1963-), 男, 福建屏南人,教授, 主要从事资源与环境遥感、三维地理信息系统、空间信息应用工程和3S集成技术研究。E?mail:zhenggz@cug.edu.cn
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引用本文:

郑贵洲,熊良超,廖艳雯,王红平. 利用MODIS数据反演南海南部海表温度及时空变化分析[J]. 遥感技术与应用, 2020, 35(1): 132-140.

Guizhou Zheng,Liangchao Xiong,Yanwen Liao,Hongping Wang. Sea Surface Temperature Inversion of the Southern South China Sea from MODIS and Temporal and Spatial Variation Analysis. Remote Sensing Technology and Application, 2020, 35(1): 132-140.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.1.0132        http://www.rsta.ac.cn/CN/Y2020/V35/I1/132

图1  MODIS影像云修复(红色区域为研究区范围)
图2  大气透过率与大气水汽之间的关系
图3  温度反演结果
图4  温度回归分析
各组温度 R 2 SSE RMSE
实测温度与反演温度 0.923 1.025 0.1581
产品温度与实测温度 0.8672 1.190 0.1703
反演温度与产品温度 0.8159 1.322 0.1794
表1  精度评价指标
图5  2014年研究区月平均海表温度变化趋势图
图6  2007~2014年96个月温度变化趋势图
图7  2014年研究区月平均海表温度等值线图
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