【摘要】 文章提出了一种基于生物光学模型的二类水体叶绿素浓度反演算法。本算法根据生物光学模型,利用一系列已知各组分浓度的反射光谱计算各组分的吸收和后向散射系数,然后采用非负最小二乘法解得叶绿素浓度。研究是在实验室内进行了绿藻的培养,且在暗室内测定了具有不同叶绿素和非藻类悬浮物浓度的水体样本的反射光谱。并把实验室测得的反射光谱重采样到Landsat TM对应的波段以检验该算法在TM数据中的适用性,同时比较了利用不同TM波段组合反演叶绿素浓度和非藻类悬浮物浓度的精度。结果表明,对于绿藻而言,利用TM第二、三、四波段反射率数据的组合反演时的效果最好,叶绿素浓度反演结果的均方根误差为4.7μg.L-1,其精度明显优于传统的回归分析算法。更多还原

【Abstract】 In the present study,a novel retrieval method for estimating chlorophyll-a concentration in case Ⅱ waters based on bio-optical model was proposed and was tested with the data measured in the laboratory.A series of reflectance spectra,with which the concentration of each sample constituent(for example chlorophyll-a,NPSS etc.) was obtained from accurate experiments,were used to calculate the absorption and backscattering coefficients of the constituents of the case Ⅱ waters.Then non-negative least square method was applied to calculate the concentration of chlorophyll-a and non-phytoplankton suspended sediments(NPSS).Green algae was firstly collected from the Kasumigaura lake in Japan and then cultured in the laboratory.The reflectance spectra of waters with different amounts of phytoplankton and NPSS were measured in the dark room using FieldSpec Pro VNIR(Analytical Spectral Devises Inc.,Boulder,CO,USA).In order to validate whether this method can be applied in multispectral data(for example Landsat TM),the spectra measured in the laboratory were resampled with Landsat TM bands 1,2,3 and 4.Different combinations of TM bands were compared to derive the most appropriate wavelength for detecting chlorophyll-a in case Ⅱ water for green algae.The results indicated that the combination of TM bands 2,3 and 4 achieved much better accuracy than other combinations,and the estimated concentration of chlorophyll-a was significantly more accurate than empirical methods.It is expected that this method can be directly applied to the real remotely sensed image because it is based on bio-optical model.更多还原