| 河口悬浮泥沙浓度Sea WiFS遥感定量模式研究 |
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| 引用本文： | 李四海,恽才兴,唐军武.河口悬浮泥沙浓度Sea WiFS遥感定量模式研究[J].海洋学报,2002,24(2):51-58. |
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| 作者姓名： | 李四海 恽才兴 唐军武 |
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| 作者单位： | 1.华东师范大学河口海岸国家重点实验室, 上海 200062;国家海洋信息中心, 天津 300171 |
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| 基金项目： | 国家卫星海洋应用中心项目“HY-1卫星水色扫描仪和CCD成像仪资料的典型河口泥沙信息提取算法研究”和“九五”科技攻关项目“区域海洋地理信息示范系统”资助项目（96-922-04-04）. |
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| 摘 要： | 利用海洋水色卫星 Seastar/SeaWiFS数据和准同步实测表层含沙量资料,建立长江口区悬浮泥沙遥感定量模式.通过“exact closed-form”算法对多时相SeaWiFS数据进行几何定位,并利用大气辐射传输简化理论对其进行大气校正,求得各波段遥感反射率;在完成投影变换和几何精校正之后,建立遥感参数与含沙量相关关系,得到长江口区悬浮泥沙遥感定量模式.
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| 关 键 词： | SeaWiFS 几何定位 大气校正 泥沙遥感 |
| 文章编号： | 0253-4193(2002)06-0000-09 |
| 收稿时间： | 7/2/2000 12:00:00 AM |
| 修稿时间： | 2000年7月2日 |
A study on the quantitative remote sensing model for the sediment concentration in estuary |
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| LI Si-hai,TANG Jun-wu and YUN Cai-xing.A study on the quantitative remote sensing model for the sediment concentration in estuary[J].Acta Oceanologica Sinica (in Chinese),2002,24(2):51-58. |
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| Authors: | LI Si-hai TANG Jun-wu and YUN Cai-xing |
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| Affiliation: | 1.State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China;National Marine Data and In formation Service, Tianjin 300171, China2.National Satellite Marine Application Center, Beijing 100081, China3.State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China |
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| Abstract: | According to the Seastar/SeaWiFS remote sensing data and in-situ sediment concentration data acquired quasi-synchronously, the quantitative remote sensing model for suspended sediment in the Changjiang Estuary is set up. The primary SeaWiFS data are geolocated by the "exact closed-form" algorithm, and atmospherically corrected with the simplified procedures for the atmosphere transference computation, so the surface reflectance is got. After these, the remote sensing parameter, which shows the typical spectral features for sediment concentration, is obtained, and is correlated with the in-situ sediment concentration. Finally, the quantitative remote sensing model is got for sediment concentration. |
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| Keywords: | SeaWiFS geolocation atmosphere correction sediment remote sensing |
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