本文選題：無人機(jī)　切入點(diǎn)：應(yīng)急災(zāi)害　出處：《西南交通大學(xué)》2013年碩士論文

【摘要】：汶川地震發(fā)生后,災(zāi)區(qū)地面交通遭到破壞,阻礙了救援隊(duì)伍進(jìn)入災(zāi)區(qū),使本可以通過及時(shí)救助還可以生存的傷員失去被救助的機(jī)會(huì)。因此,道路交通線的快速搶通決定了救援工作能否高效地開展。如果在震后應(yīng)急期間可以對道路損毀情況快速評估,決策者根據(jù)評估結(jié)果制定相應(yīng)的政策使救援工作順利開展,對抗震救災(zāi)具有十分重要的意義。 在5·12救災(zāi)工作中,因受陰雨云霧天氣和衛(wèi)星重訪周期交叉因素的制約,遙感衛(wèi)星和常規(guī)航空攝影飛機(jī)無法及時(shí)獲取災(zāi)區(qū)影像,而無人機(jī)系統(tǒng)憑借其機(jī)動(dòng)靈活、云下作業(yè)的特性及時(shí)獲取災(zāi)區(qū)遙感影像。獲取災(zāi)區(qū)影像,只是初步工作,如何在震后應(yīng)急期間,利用現(xiàn)有資料對畸變大、數(shù)量多的無人機(jī)影像快速處理,提取震害信息,為救災(zāi)決策者提供科學(xué)依據(jù),是亟待解決的問題。 本文以安縣茶坪鄉(xiāng)B35縣道的震后無人機(jī)影像和震前DEM為實(shí)驗(yàn)數(shù)據(jù),首先,借助攝影測量軟件采用航帶法自由網(wǎng)平差對無人機(jī)影像快速處理,得到正射影像鑲嵌圖能夠?yàn)椴杵亨l(xiāng)的災(zāi)情提供及時(shí)有效的宏觀信息,滿足一定的災(zāi)情監(jiān)測和評估需求,但本文的道路損毀度評估是基于DEM的空間分析,需要具有實(shí)際高程信息的DEM。因此,從Google Earth影像上采取控制點(diǎn),在自由網(wǎng)平差的基礎(chǔ)上進(jìn)行絕對定向,得到震后的DEM及DOM；對正射影像鑲嵌圖目視解譯判別災(zāi)害體和道路并勾繪,通過ArcGIS的疊加分析功能得到道路損毀區(qū)的范圍,獲取各損毀路段的長度及道路總長度；通過OpenCV和GDAL實(shí)現(xiàn)基于特征提取的DEM自適應(yīng)匹配算法,將震前與震后的DEM進(jìn)行無控制點(diǎn)匹配；以道路損毀區(qū)的范圍和震后DEM為數(shù)據(jù)源,利用ArcGIS的空間分析功能提取道路損毀區(qū)的DEM數(shù)據(jù)；然后,通過C++語言編寫程序?qū)p毀區(qū)各路段震前與震后的DEM范圍,基于優(yōu)化的設(shè)定閾值細(xì)分三棱柱的體積法實(shí)現(xiàn)土方量的計(jì)算；最后,以道路總長度、損毀長度、掩埋體的成分為因素,對損毀比例、損毀規(guī)模、受損系數(shù)進(jìn)行量化,形成損毀度的評價(jià)指標(biāo)；以土方量、掩埋體的成分與機(jī)械性能為因素,對搶險(xiǎn)工期進(jìn)行估算,為救災(zāi)決策者提供定量數(shù)據(jù),對搶險(xiǎn)救災(zāi)的順利開展具有重要的理論和實(shí)際意義。
[Abstract]:After the Wenchuan earthquake, ground transportation in the disaster area was damaged, which prevented the rescue teams from entering the disaster area, so that the wounded who could have survived through timely rescue lost the opportunity to be rescued. The rapid grabbing of the road traffic line determines whether the rescue work can be carried out efficiently. If the road damage can be assessed quickly during the post-earthquake emergency period, the decision makers will formulate corresponding policies according to the assessment results to enable the rescue work to proceed smoothly. It is of great significance for earthquake relief. In 5 / 12 disaster relief work, owing to the intersecting factors of cloudy, rainy and fog weather and satellite re-visit cycle, remote sensing satellites and conventional aerial photography aircraft were unable to obtain images of disaster areas in time, and the UAV system was flexible by virtue of its mobility. The characteristics of cloud operations in time to obtain remote sensing images of disaster areas. To obtain images of disaster areas is only a preliminary work. How to use existing data to quickly process large and large amount of UAV images and extract earthquake damage information during the post-earthquake emergency period, It is an urgent problem to provide scientific basis for disaster relief decision makers. In this paper, the post-earthquake UAV images and pre-earthquake DEM images of B35 County Road in Chapingxiang, an County, are taken as experimental data. Firstly, the UAV images are processed quickly by using the aerial belt free net adjustment with the help of photogrammetry software. The orthophoto mosaic can provide timely and effective macroscopical information for the disaster situation in Chapingxiang and meet the needs of disaster monitoring and assessment. However, the road damage degree assessment in this paper is based on the spatial analysis of DEM. Therefore, the control point is taken from Google Earth image, and the absolute orientation is carried out on the basis of free net adjustment to obtain DEM and DOM after earthquake, and the orthophoto mosaic image is visually interpreted to distinguish the disaster body and road, and the road is drawn. Through the superposition analysis function of ArcGIS, the range of road damage area is obtained, and the length of each damaged road and the total length of road are obtained. The DEM adaptive matching algorithm based on feature extraction is implemented by OpenCV and GDAL. The DEM before and after the earthquake is matched without control points, and the DEM data of the damaged road area is extracted by using the spatial analysis function of ArcGIS, taking the range of the damaged road area and the DEM after the earthquake as the data source. The volume method of subdividing triangular prism based on optimized threshold is used to calculate the earthwork volume of each section of damaged area before and after the earthquake, and finally, the total length of road, damage length, damage length are used to calculate the volume of earthwork. The damage ratio, damage scale and damage coefficient are quantified to form the evaluation index of damage degree, and the earthwork quantity, the composition and mechanical properties of the burial body are taken as the factors to estimate the period of emergency. It is of great theoretical and practical significance to provide quantitative data for disaster relief decision makers.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P237;P315.9

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