【摘要】：三峽庫區(qū)地質(zhì)條件復(fù)雜,同時(shí)年降雨量多在1000mm以上,多大雨、暴雨等強(qiáng)降水過程。古滑坡數(shù)量大,且自2003年三峽大壩蓄水以來新的滑坡體也在不斷增加,成為三峽庫區(qū)最為嚴(yán)重的地質(zhì)災(zāi)害之一。由于三峽庫區(qū)滑坡的突發(fā)性和隱蔽性等特點(diǎn),常規(guī)手段很難發(fā)現(xiàn)和監(jiān)測(cè),給生態(tài)和人類的生存、生活帶來了很大的危險(xiǎn)和隱患。雷達(dá)遙感技術(shù)由于其全天時(shí)、全天候、大范圍以及不受云雨等氣候影響,因此作為庫區(qū)滑坡監(jiān)測(cè)的新技術(shù)、新手段,InSAR技術(shù)越來越被重視和應(yīng)用。然而,由于三峽庫區(qū)地形起伏比較大,植被繁多,在實(shí)際的數(shù)據(jù)處理應(yīng)用中,受時(shí)間去相干、空間去相干及大氣擾動(dòng)等影響明顯,給滑坡的形變提取帶來很大的困惑。另外D-InSAR技術(shù)只能提取視線向上的形變信息,不能直觀反映真實(shí)的三維形變特征。針對(duì)這些問題,本文展開了系列的分析和探討,主要研究?jī)?nèi)容和貢獻(xiàn)包括:(1)本文利用干涉圖堆疊技術(shù)(Stacking)對(duì)三峽庫區(qū)秭歸地區(qū)大范圍區(qū)域滑坡進(jìn)行了探測(cè)與識(shí)別,獲取了年平均形變速率在15cm以上的緩慢形變區(qū)域共6處,其中5處為已知滑坡,1處為疑似滑坡。(2)利用SBAS技術(shù)獲取了樹坪滑坡2007年至2011年間的時(shí)間序列形變信息,揭示了樹坪滑坡東西兩個(gè)滑坡體的形變特征,并與水庫水位的變化進(jìn)行了相關(guān)性分析,為進(jìn)一步揭示形變機(jī)理提供了參考。(3)結(jié)合升降軌數(shù)據(jù),利用像素偏移量技術(shù)獲取方位向和距離向的二維形變信息。在此基礎(chǔ)上,分別采用等精度、不等精度和基于方差分量估計(jì)的三維形變信息提取。結(jié)果表明,基于方差分量估計(jì)的三維形變信息能很好地調(diào)整數(shù)據(jù)源的權(quán)比,擬合精度得到了較大的改善。(4)考慮到不同數(shù)據(jù)源間存有系統(tǒng)性誤差,嘗試附加系統(tǒng)參數(shù)的三維形變信息提取,擬合精度也得到了相應(yīng)的改善。
[Abstract]:The geological conditions in the three Gorges reservoir area are complicated, and the annual rainfall is more than 1000mm, heavy rain and heavy rain. The number of ancient landslides is large and the new landslide body has been increasing since the three Gorges Dam was impounded in 2003. It has become one of the most serious geological disasters in the three Gorges Reservoir area. Because of the sudden occurrence and concealment of landslide in the three Gorges Reservoir area, it is difficult to detect and monitor the landslide by conventional means, which brings great danger and hidden danger to the survival of ecology and human beings. Radar remote sensing technology is more and more important and applied as a new technique and means of landslide monitoring in reservoir area, because of its weather, wide range and no influence by cloud and rain. However, because of the large topographic fluctuation and various vegetation in the three Gorges Reservoir area, in the practical data processing application, it is obviously affected by time decoherence, spatial decoherence and atmospheric disturbance, which brings great confusion to the deformation extraction of landslide. In addition, the D-InSAR technique can only extract the deformation information of the line of sight upward, and can not reflect the true 3D deformation characteristics directly. Aiming at these problems, a series of analysis and discussion are carried out in this paper. The main research contents and contributions are as follows: (1) in this paper, the interference map stacking technique (Stacking) is used to detect and identify the landslide in a large area in Zigui area of the three Gorges Reservoir area. A total of 6 slow deformation regions with annual average deformation rate above 15cm are obtained, of which 5 are known landslides and 1 is suspected landslide. (2) time series deformation information of Shuping landslide from 2007 to 2011 is obtained by using SBAS technique. The deformation characteristics of the two landslide bodies in the east and west of Shuping landslide are revealed, and the correlation analysis with the change of reservoir water level is carried out, which provides a reference for further revealing the deformation mechanism. (3) combined with the data of ascending and descending rail, The two-dimensional deformation information of azimuth and distance is obtained by pixel offset technique. On this basis, three dimensional deformation information is extracted with equal precision, unequal precision and variance component estimation. The results show that the 3D deformation information based on variance component estimation can adjust the weight ratio of the data source very well, and the fitting accuracy is greatly improved. (4) considering the systematic error between different data sources, Three-dimensional deformation information extraction with system parameters is attempted and the fitting accuracy is improved accordingly.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P642.22

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