【摘要】：隨著遙感技術(shù)突飛猛進(jìn)的發(fā)展，遙感數(shù)據(jù)的獲取呈現(xiàn)出多平臺(tái)、多傳感器、多分辨率（多空間分辨率、多光譜分辨率、多時(shí)間分辨率）的新階段。由于數(shù)據(jù)種類不斷增多，質(zhì)量不斷提高，基于高分辨率遙感影像的變化檢測研究也日趨頻繁，，應(yīng)用領(lǐng)域甚廣。目前各種破壞性極強(qiáng)的自然災(zāi)害頻繁發(fā)生，造成巨大的財(cái)產(chǎn)損失和人員傷亡。利用多時(shí)相高分辨遙感影像進(jìn)行災(zāi)害分析也成為時(shí)下研究熱點(diǎn)，本文主要研究地震后建筑物的變化狀況，該項(xiàng)研究將會(huì)為震后應(yīng)急救援、災(zāi)后重建工作發(fā)揮重要作用，具體研究內(nèi)容體現(xiàn)在以下幾點(diǎn)： 1）本文首先對高分辨率遙感影像的特性進(jìn)行了分析總結(jié)，找出了適合本研究的影像方面的相關(guān)特性，并對常用遙感變化檢測方法的原理、優(yōu)缺點(diǎn)進(jìn)行了詳細(xì)分析和闡述，包括影像算術(shù)運(yùn)算法、植被指數(shù)差值法、主成分分析法以及分類后比較法。 2）面向?qū)ο蟮膶ο蠓诸惣夹g(shù)研究，包括多尺度影像分割原理和影像模糊分類方法。 3）提出了一種逐級多特征方向的變化檢測方法，該方法的主要步驟是：首先進(jìn)行像元級變化檢測，獲取包含建筑物變化在內(nèi)的大的候選區(qū)域；其次在大候選區(qū)域上進(jìn)行紋理特征的變化檢測；最后在紋理特征檢測的基礎(chǔ)上進(jìn)行色調(diào)特征的變化檢測，這樣逐級進(jìn)行不但縮小了變化檢測范圍，還降低了其他地物的干擾。為了提高該方法的效率，在進(jìn)行變化檢測之前必須進(jìn)行數(shù)據(jù)預(yù)處理工作，本文也詳細(xì)介紹了輻射校正和幾何精校正的方法和原理。 4）類間疊置分析統(tǒng)計(jì)法，利用了面向?qū)ο蟮挠跋裉幚砑夹g(shù)和矢量數(shù)據(jù)空間分析中疊置分析的方法，即首先通過影像分類把建筑物類提取出來，再利用疊置分析的方法找出受損的建筑物區(qū)域，并根據(jù)相關(guān)系數(shù)對建筑物受損狀況進(jìn)行了評估，得到損失程度信息。 最后本文對2010年青海省玉樹藏族自治州玉樹縣發(fā)生的7.1級大地震的部分受災(zāi)區(qū)域的數(shù)據(jù)進(jìn)行了實(shí)驗(yàn)，實(shí)驗(yàn)結(jié)果表明，本文提出的兩種方法均有效提高了建筑物變化檢測的正確率，降低了漏檢和虛檢的情況。
[Abstract]:With the rapid development of remote sensing technology, the acquisition of remote sensing data presents a new stage of multi-platform, multi-sensor, multi-resolution (multi-spatial resolution, multi-spectral resolution, multi-time resolution). Because of the increasing variety of data and the improvement of quality, the research on change detection based on high resolution remote sensing image is becoming more and more frequent, and the application field is very wide. At present, a variety of destructive natural disasters occur frequently, resulting in huge property losses and casualties. Disaster analysis using multitemporal high-resolution remote sensing images has become a hot topic. This paper mainly studies the changes of buildings after earthquake, which will play an important role in post-earthquake emergency rescue and post-disaster reconstruction. The specific research contents are as follows: 1) the characteristics of high-resolution remote sensing images are analyzed and summarized in this paper, and the relevant characteristics of the images suitable for this study are found out, and the principle of common remote sensing change detection methods is also discussed. The advantages and disadvantages are analyzed and expounded in detail, including image arithmetic method, vegetation index difference method, principal component analysis method and post-classification comparison method. 2) object-oriented object classification technology, including multi-scale image segmentation principle and image fuzzy classification method. 3) A change detection method is proposed in this paper. The main steps of this method are as follows: firstly, pixel level change detection is carried out to obtain large candidate areas including building changes; Secondly, the change detection of texture feature is carried out on the large candidate region. Finally, the change detection of tone feature is carried out on the basis of texture feature detection, which not only reduces the range of change detection, but also reduces the interference of other ground objects. In order to improve the efficiency of the method, data preprocessing must be carried out before the change detection. The methods and principles of radiation correction and geometric precision correction are also introduced in detail in this paper. 4) the statistical method of inter-class superposition analysis, which uses the object-oriented image processing technology and the method of overlay analysis in vector data space analysis, that is, the class of buildings is extracted by image classification. Then the damaged building area is found by the method of overlay analysis, and the damage degree information is obtained by evaluating the damage condition of the building according to the correlation coefficient. Finally, the data of the area affected by the magnitude 7.1 earthquake occurred in Yushu County, Yushu Autonomous Prefecture, Qinghai Province, in 2010 have been tested. The experimental results show that, The two methods proposed in this paper can effectively improve the correct rate of building change detection and reduce the situation of missed and false detection.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P237

【參考文獻(xiàn)】

相關(guān)博士學(xué)位論文 前1條

1 孟磊;采煤驅(qū)動(dòng)下平原小流域生態(tài)演變規(guī)律及評價(jià)[D];中國礦業(yè)大學(xué);2010年

本文編號(hào)：2392524