摘要
为了建立水色三要素的反演模式,根据2003年和2004年测量的珠江口区域水色数据,采用中分辨率成像光谱仪(MODIS)图像水色通道的遥感反射率组合建立神经网络模型,同时反演珠江口水域水色三要素(叶绿素、悬浮泥沙、黄色物质)的浓度,并对模型进行验证分析。根据反演模型利用MODIS数据获取三要素的浓度图,对形成原因进行了简要的分析。结果表明,采用443nm,488nm,531nn,551nm,667nm,678nm,748nm通道遥感反射率组合作为输入时,模型反演精度比其他输入组合要高,该方法具有较理想的精度。
In order to establish the mode of the concentration of three elements (chlorophyll-a, suspended matter and gelbstoff), several neural network models were established to retrieve the three element concentration simultaneously from remote sensing reflectance based on moderate-resolution imaging spectroradiometer(MODIS) data. The measured ocean color data was obtained in Pearl River esturay in 2003 and 2004. According to the model, the map of the concentrations of the three elements was drawn and its forming reason was analyzed. The study demonstrates that the model can get the better prediction accuracy based on the reflectance at band combination of 443nm, 488nm, 531nm, 551nm, 667nm, 678nm and 748nm than the other band combinations. The algorithm has good accuracy.
出处
《激光技术》
CAS
CSCD
北大核心
2011年第5期639-643,共5页
Laser Technology
基金
国家自然科学基金资助项目(40701132)
安徽省自然科学基金资助项目(070412042)
安徽师范大学博士启动基金联合资助项目
关键词
大气与海洋光学
中分辨率成像光谱仪
三要素浓度
遥感反射率
神经网络
珠江口
atmospheric and ocean optics
moderate-resolution imaging speetroradiometer
three-element concentration
remote sensing reflectance
neural network
Pearl River esturay