本文關鍵詞：基于遙感的黃海滸苔漂移速度與驅動機制研究　出處：《南京大學》2016年碩士論文　論文類型：學位論文

  更多相關文章： 滸苔 遙感 漂移速度 風場 流場 變化特征

【摘要】：自2007年以來,黃海滸苔綠潮已連續(xù)多年爆發(fā),漸成常態(tài)化之勢,給有關區(qū)域的海洋生態(tài)環(huán)境和經(jīng)濟發(fā)展帶來了一定的影響。黃海滸苔綠潮的生消過程伴隨著大規(guī)模漂移,對其漂移速度和驅動機制的研究可為防災減災提供信息支撐。本文基于衛(wèi)星遙感數(shù)據(jù)開展了滸苔綠潮漂移速度提取方法、黃海滸苔綠潮漂移速度時空分布特征及驅動機制等研究工作,具體如下：(1)發(fā)展了基于假彩色增強影像(ERGB)和目視解譯的滸苔綠潮漂移速度遙感提取方法,基于極軌(MODIS)和靜止軌道(GOCI)衛(wèi)星數(shù)據(jù)進行了方法測試和提取結果對比,分析了提取結果的不確定性；(2)利用MODIS、GOCI等衛(wèi)星遙感數(shù)據(jù),制作了2013-2015年共計57天的黃海滸苔綠潮漂移速度遙感監(jiān)測產(chǎn)品,在此基礎上,從空間分布以及日、月、年等不同時間尺度分析了漂移速度的時空分布特征；(3)結合黃海流場、風場數(shù)據(jù),針對不同時段和區(qū)域,開展了黃海滸苔綠潮漂移驅動機制分析。主要研究結論如下：(1)本文提出的綠潮漂移速度衛(wèi)星遙感提取方法具有較高的精度和普適性�；贛ODIS和GOCI數(shù)據(jù)的測試結果表明,采用不同衛(wèi)星數(shù)據(jù)源提取的滸苔綠潮漂移速度具有較好的一致性,相對偏差約17%。(2)黃海滸苔綠潮漂移速度(0.01-0.98 m/s,0.34±0.18 m/s)存在空間差異性,漂移速度的高值區(qū)(0.34-0.98 m/s,0.50±0.12 m/s,N=303)主要分布在121°E、35°N以南和以西海域(主要分布在30m以淺海域),漂移速度的低值區(qū)(0.01-0.34 m/s,0.21±0.08 m/s,N=379)主要分布在121°E、35°N以北和以東海域。(3)黃海滸苔綠潮漂移速度存在明顯的時變特征：①基于一天8景GOCI影像(2014年6月28日)的個例研究發(fā)現(xiàn),滸苔綠潮漂移速度的日變幅可達0.30m/s；②從不同月份的對比來看,5月下旬速度較小(均值0.23±0.17m/s,N=39),6月上旬顯著增加(均值0.57±0.22 m/s,N=44),6月中旬到7月下旬在0.30 m/s附近波動；③從2013年到2015年,黃海滸苔漂移速度均值逐年遞減(2013年：0.38±0.16 m/s,N=135；2014年：0.34±0.18 m/s,N=310；2015年0.30±0.17 m/s,N=235)。(4)海面風場和海表流場是黃海滸苔綠潮漂移的重要驅動因素,但漂移驅動機制存在時空差異性。①從時間上看,5-7月,黃海滸苔綠潮漂移速度的北向分量與風場、流場北向分量都具有相關性；滸苔綠潮漂移速度的東向分量在5月份與風場東向分量顯著相關(r=0.34,N=35),在6月份與流場東向分量顯著相關(r=0.32,N=230)；②35°N以南海域,風場東向分量的影響主要體現(xiàn)在滸苔漂移速度東向分量上(r=0.79,N=48);35°N以北海域,風場北向分量與滸苔漂移速度北向分量有關(r=0.65,N=380)；121°E以西,流場的北向分量與滸苔漂移速度北向分量的相關(r=0.30,N=74);121°E以東,風場北向分量與滸苔北向漂移速度分量相關(r=0.64,N=354)。
[Abstract]:Since 2007, the Yellow Sea has been for many years the outbreak of green tide Enteromorpha, gradually become the norm of the potential, bring some impact to the marine ecological environment on regional and economic development. The Yellow Sea Hu moss green tide dissipation process with large drift, can provide information support for disaster prevention and mitigation of the drift velocity and driving mechanism. The satellite remote sensing data based on the Hu moss green tide drift velocity extraction method, the Yellow Sea Hu moss green tide drift velocity distribution and driving mechanism research work as follows: (1) the development of the image based on false color enhancement (ERGB) and Hu moss green tide drift velocity extraction method of visual interpretation, based on polar orbit (MODIS) and geostationary orbit (GOCI) satellite data for the test method and extraction results, analyzed the extraction results of uncertainty; (2) using MODIS and GOCI satellite remote sensing data, making the the Yellow Sea Hu moss green tide drift velocity of remote sensing products 2013-2015 a total of 57 days, on this basis, from the the spatial distribution and the date, month and year of different time scale analysis of spatial distribution characteristics of drift velocity; (3) combined with the the Yellow Sea field and wind field data, according to different time periods and regions, the the Yellow Sea Hu moss green tide Drift driving mechanism analysis. The main conclusions are as follows: (1) the method of Satellite Remote Sensing Extraction with green tide drift velocity proposed in this paper has high accuracy and universality. MODIS and GOCI data based test results showed that the Hu moss green tide drift velocity of different satellite data source extraction has good consistency, the relative deviation is about 17%. (2) the Yellow Sea Hu moss green tide drift velocity (0.01-0.98 m/s, 0.34 + 0.18 m/s) spatial difference, the high value area of drift velocity (0.34-0.98 m/s, 0.50 + 0.12 m/s, N=303) to the South and west of the main distribution area in 121 ~ E, 35 ~ N (mainly distributed in shallow waters of 30m) the low value area, drift velocity (0.01-0.34 m/s, 0.21 + 0.08 m/s, N=379) are mainly distributed in 121 ~ E, 35 ~ N to the north and east of the sea. (3) the Yellow Sea Hu moss green tide drift velocity has obvious time-varying characteristics: 1 day 8 GOCI images (June 28, 2014) based on a case study found that Hu moss green tide drift velocity, amplitude up to 0.30m/s; the comparison of different months, in late May the speed of the smaller (mean 0.23 + 0.17m/s, N=39). In early June, increased significantly (mean 0.57 + 0.22 m/s, N=44), from mid June to late July volatility in the vicinity of 0.30 m/s; and from 2013 to 2015, the Yellow Sea Enteromorpha mean drift velocity decreased year by year (2013: 0.38 + 0.16 m/s, N=135; 2014: 0.34 + 0.18 m/s, N=310; 2015 0.30 + 0.17 m/s, N=235). (4) sea surface wind and sea surface flow field is an important driving factor of the Yellow Sea Hu moss green tide drift, but the drift driving mechanism of temporal and spatial differences. From the time point of view, 5-7 month, the Yellow Sea Hu moss green tide drift velocity and the north component of wind field and flow field of the north component has correlation; Hu moss green tide drift velocity of the East component in May with the wind east component was significantly correlated (r=0.34, N=35), in June and the East component of significant flow related (r=0.32, N=230); the 35 ~ N in the south of the sea, the wind east component of the impact is mainly reflected in the East component on Enteromorpha drift velocity (r=0.79, N=48); 35 N to the North Sea, north wind drift velocity component and Enteromorpha North component related (r=0.65, N=380); 121 degrees west of E, the flow field and the north component of Enteromorpha north component of the drift velocity (r=0.30, N=74); 121 degrees east of E, the wind field north component and Enteromorpha north to drift velocity component correlation (r=0.64, N=354).
【學位授予單位】：南京大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：X55;X87

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