MODIS图像论文利用MODIS图像反演水色三要素的方法研究.docVIP

MODIS图像论文：利用MODIS图像反演水色三要素的方法研究 【中文摘要】叶绿素a、悬浮泥沙和黄色物质是反映水体水质的三个重要参数,对海洋环境和水体的富营养化有着重要的作用。水色遥感是依据水体的光谱特征,经过大气校正,并依据生物光学特性来反演水质参数的一种方法。国内外学者通常把水体划分为I类水体和II类水体,目前,I类水体的水色反演方法已经很成熟,而II类水体由于受其本身水体的复杂性和地域性的影响,很难得到通用的反演算法来反演II类水体三要素的含量。因此,对II类水体反演算法的研究已成为热门课题。论文在珠江口区域现场实测的水体反射率、叶绿素a、悬浮泥沙和黄色物质浓度的基础上,依据MODIS图像不同水色通道的遥感反射率组合,研究利用神经网络方法反演叶绿素a、悬浮泥沙和黄色物质的浓度,并利用多对实测数据对建立的水色三分量模型进行检验。通过检验表明,利用BP (Back Propagation)神经网络方法建立的单独反演方法,叶绿素a反演的相对误差为28.59%,相关系数为0.987,悬浮泥沙含量反演的相对误差为27.34%,相关系数为0.931,黄色物质反演的相对误差为26.72%,相关系数为0.831;利用BP神经网络方法建立的同时反演水色三要素方法,叶绿素a平均相对误差为35.52%,相关系数为0.982,悬浮泥沙平均相对误差为34.07%,相关系数为0.877,黄色物质平均相对误差为34.19%,相关系数为0.689;利用GRNN(广义回归神经网络)方法建立的反演悬浮泥沙含量方法,其平均相对误差为17.01%,相关系数为0.965。最后结合MODIS图像,通过对MODIS图像进行预处理和大气校正得到水体的真实反射率,将反射率代入反演模式,得到叶绿素a、悬浮泥沙和黄色物质浓度图。 【英文摘要】Chlorophyll_a, suspended sediment and yellow substance are three important water quality parameters, they play an important role in the marine environment and eutrophication of water. Ocean Color Remote sensing is a method to derive water quality parameters based on the optical properties of biological in use of the spectral characteristics of the three components of ocean color. Waters are divided into case I waters and case II waters. Now, The research on case I waters is very Mature. Because of its complexity and regional, the research on case II waters is very hard. Consequently, there is considerable interest in the use of remotely sensed data to research case II waters.This theesis makes use of MODIS data and measured data about remote sensing reflectance and three components concentrations to establish several neural network models, and the actual data was obtained from the Ocean Color Experiments in Pearl River Estuary. The models were established and validated with the measured data. The Back Propagation neural network model is established to derive three components concentrations Separately. It is shown that the averaged relative error of chlorophyll-a is 28.59% and the correction coefficient is 0.987. The aver