Song Yu, Song Xiao-Dong, Jiang Hong, Guo Zhao-Bing, Guo Qing-Hai
Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2010 Apr;30(4):1075-9.
Chlorophyll is a very important indictor for the eutrophication status of lake water body. Using remotely sensed data to achieve real-time dynamic monitoring of the spatial distribution of chlorophyll has great importance. This paper aims to find the best band for the hyperspectral ratio model of chlorophyll-a, and take advantage of this model to implement remote sensing retrieval of algae in Taihu Lake. By the analysis of the spectral reflectance and water quality sampling data of the surface water body, the regression model between the ratio of reflectance and chlorophyll-a was built, and it was showed that the ratio model between the wavelengths around 700 and 625 nm had a relatively high coefficient value of determination (R2), while the ratio model constructed with 710 nm and visible wavelengths showed a descended R2 following with the increment of the visible wavelengths. Combined with in-situ water samplings analysis and spectral reflectance measurement, the results showed that it's possible to retrieve algae water body using the MODIS green index (GI). The spatial distributions of chlorophyll-a and algae in Taihu Lake were extracted successfully using MODIS data with the algorithm developed in this paper.
叶绿素是湖泊水体富营养化状况的一个非常重要的指标。利用遥感数据实现对叶绿素空间分布的实时动态监测具有重要意义。本文旨在寻找叶绿素a高光谱比值模型的最佳波段，并利用该模型实现太湖藻类的遥感反演。通过对地表水光谱反射率和水质采样数据的分析，建立了反射率比值与叶绿素a之间的回归模型，结果表明，700nm左右与625nm左右波长的比值模型具有较高的决定系数（R2），而由710nm与可见光波段构建的比值模型随着可见光波段的增加R2呈下降趋势。结合现场水样分析和光谱反射率测量，结果表明利用MODIS绿度指数（GI）反演藻华水体是可行的。利用本文开发的算法成功提取了太湖叶绿素a和藻类的空间分布。
