Remote Sensing Monitoring Of Cyanobacteria Bloom In Typical Inland Lakes

In recent years,with the development of socioeconomic and the intensification of human activities in lake basins,too much domestic sewage of industry is discharge into the water.Therefore,water eutrophication and cyanobacterial bloom are becoming more and more serious.Remote sensing could acquire the information of large area quickly,which is becoming more and more significant in monitoring the location,area and dynamic change of algae.At present,a variety of different resolution optical remote sensing sensors have been applied to the monitoring of cyanobacterial blooms in inland waters.It is difficult for optical remote sensing to extract algal bloom information which could not meet the acquirement of accuracy and timeliness in algal bloom monitoring using remote sensing.Therefore,it is very important for cyanobacteria bloom monitoring developing the study of automatic extraction of cyanobacteria bloom distribution which is applicable for the different resolution sensors.In this paper,the optical remote sensing image of cyanobacteria bloom is analyzed,the maximum gradient complexity method is used to obtain the threshold to realize the automatic segmentation of remote sensing image and the extraction of the bloom region.Based on the maximum gradient complexity method,cyanobacterial bloom automated extraction process.Based on the above research,a dynamic gradient complexity method is proposed,and based on this,an automated extraction process of algal blooms suitable for high-resolution images is established.This method was applied to Taihu Lake,Dianchi Lake and Yuqiao Reservoir using remote sensing images with different spatial resolution.The distribution of algal blooms was extracted automatically and the spatial and temporal distribution of algal bloom was analyzed.Combined with the meteorological,economic and water quality data,the impact of various factors on the bloom was analyzed.The main conclusions are as follows:(1)The automated extraction process of blue algae bloom in inland water has been established.In this paper,we use the largest gradient complexity method to achieve the automatic extraction of blue algae blooms in inland water bodies.We have automated the processing,including data preprocessing,spectral index calculations,threshold segmentation,and distribution of cyanobacterial water blooms,which reduces the error caused by artificially extracting water blooms and achieves rapid extraction and monitoring of blue-green algae blooms.In this paper,a dynamic gradient complexity method is developed based on the largest gradient complexity method.The dynamic gradient complexity method is used in high-resolution satellite imagery.Since high-resolution images will show more of the distribution of small water blooms in small waters,the dynamic gradient complexity method can extract the distribution of sporadic blooms better and can more accurately reflect the true distribution of bloom distribution.(2)Extraction of algal blooms in Taihu Lake and influence of meteorological factors on algal blooms in 2017 based on MODIS images.The cyanobacterial bloom in Taihu Lake began to burst from January in 2017.The earliest date was January 13.From January to March,the outbreak of bloom in Taihu Lake was relatively small.It mainly occurred in the northwestern lake area of Taihu Lake.In April,the bloom began to spread.The number of outbreaks in lakes increased,and the outbreak of algal blooms was more serious between April and November.The meteorological factors,including wind speed,temperature,and sunshine duration,have influence on the algal bloom in Taihu Lake to some extent.The,sufficient sunshine and relatively small wind speed on the day of the outbreak of the bloom are conducive to the formation of algal blooms.(3)Spatial and Temporal Distribution of algal bloom in Dianchi Lake and itsaffecting factors based on Landsat TM / ETM + / OLI data in recent 30 years.Landsat satellites detected the first outbreak of algal bloom in Dianchi Lake in 1987.After 1990,large outbreaks of bloom occurred in the northern part of the Dianchi Lake.The phenomenon of algal bloom in Dianchi Lake deteriorated year by year before 2000,and algal bloom phenomenon slowed down after 2000.The frequency of blooms is high from June to November every year.The frequency of blooms in Longmen Village,Fubao Bay,Huiwan Bay,Panlong Lake Entrance,etc.in the northern part of Dianchi Lake is relatively high.It is a high-yielding area of algal bloom,and the occurrence of blooms in the center of the lake is relatively low.The interannual changes in the water bloom of Dianchi Lake before 2000 were closely related to population growth and economic development,and the occurrence frequency of algal bloom increased with social and economic development.After 2000,the development of blooms in Dianchi Lake has slowed down,and it has not deteriorated with the development of society.This shows that Dianchi Lake has achieved some success in its vigorous management since 1996,and the impact of man-made factors on algal blooms has become smaller.Meteorological factors also have a certain influence on the occurrence and development of blooms.A large amount of precipitation and a small wind speed will promote the occurrence of water blooms.(4)Analysis of algae extract and its influencing factors in Yuqiao Reservoir based on GF data.In recent years,algae blooms were detected for the first time at Yuqiao Reservoir in 2015,and the outbreaks of algal blooms in recent years were mainly concentrated from July to September.The spatial distribution of algal blooms at the Yuqiao Reservoir mostly occurred at the bank edge.When large algae bloom occurs,it will spread to the central area of the reservoir.Yuqiao Reservoir has a small amount of rainfall and increased sunshine duration before the occurrence of algal blooms,and the promotion of small winds is conducive to algal blooms.