Lake water eutrophication has become a global common problem accompanied with a phenomenon that the frequent outbreaks of cyanobacterial bloom. With the advantages of large monitoring range, fast speed, strong periodicity and relatively cheap cost, remote sensing technology can make up for what common water quality monitoring lacks and save lots of manpower and material, which is one of the best options of monitoring cyanobacterial bloom. In recent years, the research in remote sensing monitoring for type-II water bloom has made great progress, however, the optical component of water body in Taihu Lake is complex, and the atmospheric correction of remote sensing image is difficult etc. restrictions, it is still the most difficult problem that obtain long time series of cyanobacteria quantitative retrieval data. Co-funded by National 863 Program, National science Foundation of China and so on projects, Nanjing Institute of Geography and Limnology Lake Environmental Remote Sensing Ma Ronghua Research Team obtained important progress in terms of remote sensing quantitative retrieve for inland lake water body phycocyanin concentration.
Phycocyanin (PC) is the unique pigment carried by cyanobacteria and has the particular absorption characteristic spectrum. Using the absorption characteristics of PC, the research designs and establishes a new PC retrieval model. In theory, the research deduce, analyze and simulate the feasibility of carrying out PC remote sensing retrieval by the method, use the measured data to verify and obtain the PC retrieval model based on remote sensing reflectance. Use the radiation-transmission equation of simulation to deduce the model onto Rayleigh-corrected reflectance (Rrc), and apply it to Rrc data of MERIS long time series obtained PC distribution results. A series of scientific analysis method like spectral analysis, image contrast and histogram contrast prove that the proposed algorithm is not sensitive to interferences such as aerosols, light cloud, solar flare and suspended sediment. Therefore, it makes MERIS effective data of Taihu Lake increased from 1% to 50%. The developed PC data set of long time series (2002-2012) based on MERIS reveals the diversity among seasonal variation, interannual variation and different lake regions. By trying out the proposed algorithm idea to other lakes like Dian Lake, Chaohu Lake etc., it shows that the idea has preferable portability, which provides the important theoretical basis for extending to the mid-lower Yangtze lakes.
The achievement has been accepted by the journal Remote Sensing of Environment (2014, 154:298-317). This is another remarkable achievement of Nanjing Institute of Geography and Limnology Lake Environmental Remote Sensing Research Team in terms of lake water bloom quantitative retrieval research, since published Inland Lake Water Body PC Remote Sensing Retrieval Algorithm Research on the journal. The achievement pushes the monitoring of lake cyanobacteria from the ground to outer space, which realizes the quantitative monitoring and estimation of cyanobacteria by satellite. Remote Sensing of Environment is the top journal in environment, also the one that has the highest impact factor in remote sensing field (the impact factor of 2013 is 4.769).
Link to the paper: http://www.sciencedirect.com/science/article/pii/S003442571400323X
