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  本文選題：植被覆蓋區(qū) + 歸一化植被指數(shù)�。� 參考：《中南大學》2014年碩士論文

【摘要】：摘要：植被覆蓋區(qū)是遙感蝕變信息提取的難點之一,本文以貴州省北部務(wù)正道地區(qū)為研究區(qū),使用ETM多光譜數(shù)據(jù)進行實驗研究,取得了比較滿意的效果。首先對遙感影像進行預處理和增強處理；其次結(jié)合基礎(chǔ)地質(zhì)資料進行遙感地質(zhì)解譯；再次采用“抑制中低植被覆蓋區(qū)+掩膜高植被覆蓋區(qū)及其他干擾因素區(qū)+主成分分析+密度分割”的方法提取了鐵染蝕變異常信息和羥基蝕變異常信息；最后基于研究區(qū)地質(zhì)條件和成礦規(guī)律的研究,進行遙感綜合成礦預測,圈定出找礦遠景區(qū)。主要取得了以下成果： 1.通過圖像預處理和增強處理解決了研究區(qū)遙感影像輻射誤差和幾何畸變,提高了影像紋理清晰度,有利于遙感目視解譯；結(jié)合研究區(qū)已有的基礎(chǔ)地質(zhì)資料,總結(jié)出各類地層與構(gòu)造的影像特征,對遙感影像的地層和構(gòu)造進行了解譯。 2.研究區(qū)內(nèi)影響蝕變信息提取的干擾因素包括植被、水系、陰影和第四系等。本文引入歸一化植被指數(shù)(NDVI)確定了高植被覆蓋區(qū)和中低植被覆蓋區(qū),對于中低植被覆蓋區(qū)采用植被抑制算法抑制植被信息,對于高植被覆蓋區(qū)和水系、陰影與第四系采用分別建立掩膜、相乘取得合膜的方法進行了去干擾操作。 3.在去除干擾因素的基礎(chǔ)上,采用主成分分析的方法提取了研究區(qū)鐵染蝕變和羥基蝕變,通過密度分割的方法分別劃分為三個異常等級,制作出務(wù)正道地區(qū)鐵染蝕變異常圖和羥基蝕變異常圖。最后將提取到的蝕變異常圖斑與研究區(qū)內(nèi)已知的礦體分布圖進行疊加分析,發(fā)現(xiàn)能夠很好地重合,說明提取的鐵染蝕變和羥基蝕變比較好地反映了區(qū)內(nèi)礦化蝕變信息。 4.結(jié)合研究區(qū)遙感地質(zhì)解譯成果、礦化蝕變信息提取成果、已知礦床(點)的分布情況和區(qū)域地質(zhì)條件及成礦規(guī)律,進行了遙感綜合成礦預測,圈定出若干個找礦遠景區(qū)。
[Abstract]:Absrtact: vegetation cover area is one of the difficulties in extracting alteration information from remote sensing. In this paper, the ETM multispectral data are used as the research area in the north of Guizhou Province, and satisfactory results have been obtained. Firstly, the remote sensing image is preprocessed and enhanced, and then the remote sensing geological interpretation is combined with the basic geological data. Thirdly, the iron-stained alteration anomaly information and hydroxyl alteration anomaly information were extracted by the principal component analysis (PCA) density segmentation method of masked high vegetation cover area and other interference factors in the middle and low vegetation cover area. Finally, based on the study of geological conditions and metallogenic rules of the study area, remote sensing comprehensive metallogenic prediction is carried out to delineate the prospecting area. The following results have been achieved: 1. The radiative error and geometric distortion of the remote sensing image in the study area are solved by image preprocessing and enhancement processing, and the texture clarity of the image is improved, which is beneficial to the visual interpretation of remote sensing. The image features of various strata and structures are summarized and the strata and structures of remote sensing images are interpreted. 2. The factors affecting the extraction of alteration information in the study area include vegetation, water system, shadow and Quaternary system. In this paper, the normalized vegetation index (NDVI) is introduced to determine the high vegetation cover area and the middle and low vegetation cover area. For the middle and low vegetation cover area, the vegetation information is suppressed by vegetation suppression algorithm, and for the high vegetation cover area and the water system, the vegetation information is suppressed by vegetation suppression algorithm. The shadow and Quaternary system were operated by establishing mask and multiplying the mask to obtain the composite film. 3. On the basis of removing interference factors, iron stain alteration and hydroxyl group alteration were extracted by principal component analysis (PCA). The abnormal map of iron stain alteration and hydroxyl group alteration in Wuzhengdao area was made. Finally, by superposition analysis of the extracted alteration anomaly pattern and the known orebody distribution map in the study area, it is found that the extracted iron-stained alteration and hydroxyl alteration can well coincide with each other, indicating that the extracted iron-stained alteration and hydroxyl alteration reflect the mineralization alteration information in the area. 4. Combined with the results of remote sensing geological interpretation, the extraction of mineralization alteration information, the distribution of known deposits (points), the regional geological conditions and metallogenic rules, the comprehensive metallogenic prediction of remote sensing is carried out, and several prospecting areas are delineated.
【學位授予單位】：中南大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP751

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本文編號：1917340