| Different scales of green tide(Macroalgae-Ulva prolifera)disaster have run rampantly in the Yellow Sea annually in recent years and causing huge losses to local aquaculture,tourism,transportation,marine ecological environment.In view of the characteristics of long duration,large scale and fixed position,it is very important to use remote sensing to monitor green tide.However,the current remote sensing data which is used for monitoring has all kinds of limitations: either the spatial resolution is too low,the monitoring accuracy can't be guaranteed,or the time resolution is too low,the time series of monitoring is too sparse.Therefore,in order to make up for this deficiency,this paper takes the Yellow Sea as the research area,comprehensive using a variety of satellite remote sensing data(GF-1 WFV,HJ-1A/1B CCD,CBERS-04 WFI,Landsat-7 ETM+,Landsta-8 OLI,MODIS SST-8day),as well as UAV data and ship-measured data to monitor the green tide disaster in the Yellow Sea from 2014 to 2016.On this basis,some relevant researches are also carried on in this paper.The main research contents are listed as follows:(1)By using different atmospheric correction methods to correct the same image,calculating and analyzing a number of statistics,the best atmospheric correction method is confirmed when extracting green tide information by NDVI index.(2)Analyze the temporal and spatial distribution characteristics of green tide disaster in the Yellow Sea from 2014 to 2016;Compare the monitoring results from different data sources.(3)By taking the sea surface temperature data of the Yellow Sea and the monitoring results in 2016 as an example to analyze their correlation;Discuss the prevention and control strategy of green tide disaster from the perspective of remote sensing.The results prove that:(1)When NDVI threshold method is used to extract the green tide information,the extraction effect is the best after the image is corrected by COST method,and followed by FLAASH and 6S correction methods.But the adaptability of COST atmospheric correction in other green tide extraction algorithms is still need further investigation.(2)From a macro point of view,the spatial and temporal distribution of the green tide in the Yellow Sea is basically the same in the three years.It firstly appeared in the radial submarine sand ridges system off Jiangsu Province from late April to early May,and then continuously grew and drifted to northward,broke out in June and went extinct in July,and finally ended in August.By comparing the monitoring results of different data sources,the mixed pixel effect caused by spatial resolution is the main reason of monitoring errors.(3)There is a significant correlation between the outbreak of the green tide and the SST of the Yellow Sea;In order to prevent and control the green tide,in the long run,we should reduce the degree of eutrophication of the sea from the source,for the recent outbreak of green tide,we can take strategy of pre salvage and timely warning to reduce the disaster caused by green tide.In summary,by using multi-resource data,the dynamic monitoring of the green tide in the Yellow Sea is given and the monitoring results are compared in this paper.It improves the monitoring accuracy and confidence,therefore this study has a certain innovation in the field.Besides,this paper conduct research from aspects of atmospheric correction factors affecting the extraction of green tide information,spatial and temporal distribution characteristics,comparison of monitoring results,correlation between temperature factors and outbreak of green tide,prevention and control strategy.To some extent,it enriches the understanding of the green tide,and be of important practical significance for preventing and controlling the green tide disaster and reducing the loss. |
PDF Full Text Request