【摘要】：水深測(cè)量是湖泊調(diào)查中的重要工作之一,了解有關(guān)區(qū)域水深的變化狀況對(duì)水資源利用、洪澇監(jiān)測(cè)、防災(zāi)治災(zāi)等方面都至關(guān)重要。目前達(dá)里諾爾湖的水體監(jiān)測(cè)方法中,水深指標(biāo)的測(cè)量仍然使用傳統(tǒng)測(cè)深手段,利用遙感技術(shù)實(shí)現(xiàn)大范圍同步測(cè)深的研究還未見報(bào)道,本文首次嘗試運(yùn)用3S技術(shù),利用3種遙感衛(wèi)星共6景影像進(jìn)行對(duì)比分析來(lái)反演達(dá)里諾爾湖深度,構(gòu)建水下湖底地形。得到了以下結(jié)論:(1)可見光波段中,紅光波段為對(duì)達(dá)里諾爾湖水深變化較敏感的波段;不可見光波段中,熱紅外波段在秋末冬初表現(xiàn)出與湖水深度較好的相關(guān)關(guān)系,分析原因與秋季上下層湖水的熱對(duì)流現(xiàn)象有關(guān);在對(duì)達(dá)里諾爾湖水深反演遙感應(yīng)用中,使用OLI數(shù)據(jù)比使用ETM+數(shù)據(jù)或MS數(shù)據(jù)更加適合。(2)利用了彩色合成法和改進(jìn)的歸一化水體指數(shù)法兩種水陸分離方法對(duì)5副Landsat衛(wèi)星影像進(jìn)行了達(dá)里諾爾湖湖面的提取,發(fā)現(xiàn)2013年湖面面積比2012年湖面面積有所增加,2014年開始慢慢減少,到2016年,達(dá)里諾爾湖湖面積恢復(fù)到2012年的面積大小;經(jīng)計(jì)算在2012年至2016年,達(dá)里諾爾湖湖面面積約為189km2,年變化范圍在1%左右。(3)建立了 152個(gè)單因子模型,和12個(gè)多因子模型,并進(jìn)行對(duì)比篩選。在單因子模型中,2015年遙感影像作為數(shù)據(jù)源,以B1*B10作為反演因子的指數(shù)模型為最佳反演模型;在多因子模型中,2015年單波段+波段組合形式的多元回歸模型為最優(yōu)。在三種數(shù)據(jù)源的對(duì)比中,反演精度由大到小的順序?yàn)镺LIMSETM+,說明在對(duì)水深反演的相關(guān)研究中并非遙感影像的分辨率越高越好,合適的波段設(shè)置會(huì)取得精度較好的結(jié)果。(4)通過多次對(duì)比分析,篩選出2015-10-16多因子模型為最優(yōu)反演模型,利用該模型對(duì)影像中每個(gè)像元點(diǎn)進(jìn)行水深計(jì)算,并繪制等水深線圖、3D格網(wǎng)圖和剖面圖,分析了湖底地形變化情況,并計(jì)算了達(dá)里諾爾湖庫(kù)容量約為13.1億立方米。
[Abstract]:Bathymetric survey is one of the most important tasks in lake survey. It is very important to understand the variation of regional water depth in water resources utilization, flood monitoring, disaster prevention and treatment, and so on. At present, in the water monitoring method of Darinole Lake, the traditional bathymetric method is still used in the measurement of the water depth index, and the study of using remote sensing technology to realize the large-scale synchronous sounding has not been reported. This paper first tries to use 3s technology. The depth of Darinole Lake is inversed by comparing and analyzing the six images of three remote sensing satellites, and the underwater lake bottom topography is constructed. The conclusions are as follows: (1) in the visible light band, the red band is the one sensitive to the water depth variation of Darinol Lake, and the thermal infrared band in the invisible wave band shows a good correlation with the depth of the lake water at the end of autumn and the beginning of winter. The causes are related to the phenomenon of thermal convection in the upper and lower layers of lake water in autumn, and in the application of remote sensing in inversion of water depth of Darinole Lake, Using OLI data is more suitable than using ETM data or MS data. (2) five sets of Landsat satellite images are extracted from Lake Darinole Lake by using color synthesis method and improved normalized water body index method. The lake area was found to have increased in 2013 over that in 2012, and began to decrease slowly in 2014, before returning to its 2012 size by 2016; calculated from 2012 to 2016, The lake area of Darinole Lake is about 189km2, and the annual variation range is about 1%. (3) 152 single factor models and 12 multi-factor models have been established and compared with each other. In the single factor model, the 2015 remote sensing image is used as the data source, the index model with B1*B10 as the inversion factor is used as the best inversion model, and the multivariate regression model with single band combination in 2015 is the best in the multi-factor model. In the comparison of three data sources, the order of inversion accuracy from large to small is OLIMSETM, which shows that the higher the resolution of remote sensing image, the better the resolution of the remote sensing image in the related research of depth inversion. The appropriate band setting can get better results. (4) by comparing and analyzing several times, the 2015-10-16 multi-factor model is selected as the optimal inversion model, and the depth of each pixel in the image is calculated by using this model. At the same time, the 3D grid map and section map are drawn, the topographic variation of the lake bottom is analyzed, and the capacity of Darinole Lake reservoir is calculated to be about 1.31 billion cubic meters.
【學(xué)位授予單位】：內(nèi)蒙古農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P332

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