Font Size: a A A

Long-term Monitoring Of Algal Blooms In Chaohu Lake Based On Domestic High-resolution Optical And Domestic High-resolution Radar Remote Sensing

Posted on:2020-01-15Degree:MasterType:Thesis
Country:ChinaCandidate:S Y HeFull Text:PDF
GTID:2381330575471072Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
In the past few decades,the issue of eutrophication has gradually attracted widespread attention worldwide,and the ensuing cyanobacteria bloom has not only keep increased in frequency and area,but also posed a serious threat to the ecological environment and human health.With the rapid development of Hefei’s urban economy in the past decades,the problem of chaohu lake bloom has become increasingly serious.Therefore,studying the spatial and temporal variation characteristics of Chaohu lake algal blooms and its influencing factors has important guiding significance for the control and treatment of the algal blooms and the improvement of the ecological environment.This study is based on domestic high-scoring data,combined with multi-source optics and full-polarization SAR remote sensing as data sources,giving full play to the advantages of optical remote sensing methods,large amount of information and all-weather weathering of radar remote sensing;using spatio-temporal fusion technology to generate The long-time remote sensing image dataset of the Chaohu area from 2008 to 2017 improves the temporal resolution on the basis of ensuring high spatial resolution;and then uses the normalized vegetation index and the Wishart supervised classification method to image the optical and radar remote sensing images.Identification and extraction;qualitative and quantitative analysis of the spatial and temporal variation characteristics of Chaohu Lake water bloom and the migration law of water bloom,and the influence of major meteorological factors on Chaohu Lake water bloom,and using principal component analysis method to analyze the influencing factors.It aims to provide a research basis for remote sensing monitoring of domestic water and body water blooms,and provide reference for the control and treatment of water blooms.The specific conclusions are as follows:(1)spatial and temporal variation characteristics of Chaohu algal blooms:In time scale,in the past ten years,algal blooms area of Chaohu lake is higher in summer than in winner,2nd and 3rd quarters than 4th.And the peak area in the last five years was significantly lower than that the previous five years.The growth cycle of the last five years was also significantly delayed compared with the previous five years.In spatial scale,the most serious algal blooms occurred in the northwest corner of Chaohu lake,and less in the east.The coastal algal blooms are more serious than that in the center of the lake.The frequency of algal bloom outbreaks in the latter five years was better than that in the previous five years.Except for some years,due to the wind direction in the Chaohu area,it generally showed a trend of moving from the north to the south,and from the east to the west.(2)relationship between precipitation,temperature,wind speed and Chaohu algal blooms:Precipitation is not conducive to the production of algal blooms.The larger the precipitation,the smaller the area of algal blooms,the smaller the precipitation,the larger of the algal blooms.The higher the daily average temperature,the larger the algal bloom area.Suitable temperature is conducive to the formation of algal blooms,and the algal blooms are suppressed when the temperature is higher than 30 ℃.The higher the average wind speed,the smaller the algal blooms area.The influence is mainly related to the relationship between wind speed and critical wind speed.Combined with several meteorological factors,the principal component analysis of algal bloom area change in Chaohu Lake is mainly presented as follows:When the temperature,wind speed and sunshine duration increase,the probability of blooms increases accordingly.
Keywords/Search Tags:Domestic GF satellite, Chaohu algal blooms, Radar remote sensing, Spatio-temporal fusion, Spatio-temporal variation characteristics
PDF Full Text Request
Related items