The Optical Remote Sensing In China Eastern Coastal Zone And Application In The Global Changes

In this paper, Bohai Sea, Yellow Sea and East China Sea (BYES) are taken as thestudy areas. Based on2003-2012field data of Bohai Sea, Yellow Sea and East ChinaSea and NOMAD data sets, an in-depth analysis is carried out to discuss theatmospheric correction model of turbid water in BYES sea, the intrinsic opticalremote-sensing observation model, the remote-sensing observation models ofchlorophyll a and suspended matter concentration as well as seawater diffuseattenuation coefficient. According to the1997-2013monthly average remote-sensingreflectance observation data of SeaWiFS and MODIS satellite, bio-optical componentremote-sensing observation model established in this paper is combined for retrievalto obtain the spatiotemporal change trend information of bio-optical component inglobal oceans, BYES seas. Combined with global sea level anomalies, temperatureanomalies, mixed layer depth and other auxiliary data, the spatiotemporal distributioncharacteristics of key bio-optical component and environmental effect in BYES seasare systematically analyzed and discussed. Through the study of this paper, theconclusions can be achieved as follows.(1) Two accurately atmospheric correction models were developed for retrievingremote sensing reflectance from BYES seas. On one hand, for cross-calibration-basedshortwave infrared (SWIR) atmospheric correction model, the random noise at SWIRband is minimized using the5×5box meaning approach, while the systematic noiseis minimized using the cross-calibration between near-infrared and SWIR bands. Onthe other hand, to account for the violation of “black” assumption at1240nm in theextreme turbid waters, a linear model is proposed for filling the black strips of theMODIS1640nm band, and then the1640&2130nm band combination is used toremove the atmospheric effects on remote sensing data. Compared with the fieldmeasurements, cross-calibration-based and1640&2130nm band combination-basedatmospheric correction models have a superior performance to the traditional SWIRatmospheric correction model.(2) A semi-analytical model is developed for deriving diffuse attenuationcoefficient from MODIS data in BYES seas. The two-stream radiative transfer modelis employed for establishing the relationship between diffuse attenuation coefficientand remote sensing reflectance and absorption coefficient. Then, a two band-basedsemi-analytical model is constructed for isolating the absorption coefficient from theremote sensing reflectance. Finally, the diffuse attenuation coefficient could beisolated from the remote sensing reflectance using the two-stream model and twoband semi-analytical model. By comparing with the in situ measurements, use of thesemi-analytical model developed in this study could decrease by>12%uncertainty tothe traditional models.(3) Three accurately neural network models are developed for derivingchlorophyll-a concentration, suspended sediment concentration, absorption andbackscattering coefficients from the remote sensing reflectance in the BYES seas. In this study, the inputs of neural network models are optimized using analyticalapproaches, then the neural network technology is utilized to regress the relationshipbetween the optical parameters and remote sensing reflectance. A big dataset collectedfrom the global oceanic and coastal waters is used to initialize and evaluate theperformance of neural network and analytical coupled model for optical parametersestimation. By comparison, our models had a superior to the traditional models inderiving optical parameters from the global oceanic and coastal waters.(4) Due to the physical mechanisms such as the cold resistance of marinephytoplankton better than heat resistance, since global average temperature rises witha rate of0.001℃mn-1in1997, the chlorophyll a concentration of global oceans isreduced year by year. The dynamic balance between Kd(490) and algae growth haseffects on the regulation of marine ecosystem, which could help mitigate the rate ofglobal warming, but cannot change the overall trend of global climate change. TheBYES seas are affected by human activities closely. The chlorophyll-a concentrationand suspended sediment concentration in the global oceans strong covaried with thespatial and temporal changes of these in BYES seas.