本文關(guān)鍵詞： ETM 蝕變信息提取 空間分析 遙感成礦預(yù)測 找礦信息量　出處：《中南大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：新疆托里縣阿勒吞扎瓦提地區(qū)蘊含豐富的金礦資源,本論文在對該區(qū)成礦地質(zhì)背景、典型礦床特征、ETM遙感影像特征分析與金礦化信息提取的基礎(chǔ)上,建立區(qū)內(nèi)進行成礦預(yù)測所需的多源地學(xué)信息數(shù)據(jù)庫。利用該數(shù)據(jù)庫,結(jié)合GIS的空間分析功能對區(qū)內(nèi)的已知金礦點(床)與地質(zhì)異常、遙感異常進行統(tǒng)計,總結(jié)成礦規(guī)律,建立該區(qū)金礦資源預(yù)測模型。以空間分析統(tǒng)計的結(jié)果結(jié)合建立預(yù)測模型的基礎(chǔ)上,利用遙感成礦預(yù)測與找礦信息量法,定性結(jié)合定量對該區(qū)進行成礦預(yù)測,圈定找礦遠景區(qū),并進行對比。本論文主要包括以下幾方面內(nèi)容： (1)結(jié)合研究區(qū)成礦地質(zhì)背景,對ETM影像進行遙感解譯；利用主成分分析方法與比值法對該區(qū)進行金礦化遙感異常信息提取,包括泥化異常、鐵化異常與硅化異常。 (2)根據(jù)地質(zhì)異常、遙感異常信息,建立本區(qū)多源地學(xué)信息數(shù)據(jù)庫,包括基礎(chǔ)地理數(shù)據(jù)、地質(zhì)數(shù)據(jù)、遙感數(shù)據(jù)。 (3)利用MAPGIS軟件將研究區(qū)的等高線數(shù)據(jù)生成DEM模型,結(jié)合ETM遙感影像、基礎(chǔ)地理數(shù)據(jù)形成研究區(qū)的三維可視化模型。 (4)利用MAPGIS、MORPAS、ArcGIS軟件對該區(qū)的已知金礦點與地質(zhì)異常數(shù)據(jù)、遙感異常數(shù)據(jù)進行空間分析,總結(jié)各控礦因素的成礦作用. (5)利用ArcGIS軟件對研究區(qū)進行遙感成礦預(yù)測,主要將各控礦因素圖層進行空間疊加分析,最后形成的預(yù)測圖層所顯示的區(qū)域即為該區(qū)找礦最有利地段,根據(jù)成礦理論,圈定4處找礦遠景區(qū),其中A級2處,B級2處。 (6)利用MORPAS軟件對研究區(qū)進行找礦信息量計算,圈定5處找礦遠景區(qū),其中A級3處,B級2處；將其結(jié)果與遙感成礦預(yù)測結(jié)果進行對比,發(fā)現(xiàn)兩種方法圈定的找礦遠景區(qū)十分吻合,證明兩種方法成礦預(yù)測的可行性與可靠性。圖41幅,表20個,參考文獻65篇
[Abstract]:The Aletanzavati area of Tori County, Xinjiang contains abundant gold resources. In this paper, the metallogenic geological background, the characteristics of typical deposits and the characteristics of ETM remote sensing images and the extraction of gold mineralization information are analyzed. This paper establishes a multi-source information database for metallogenic prediction in this area. By using the database, combined with the spatial analysis function of GIS, the known gold points (deposits) and geological anomalies and remote sensing anomalies in the area are counted, and the metallogenic rules are summarized. On the basis of the results of spatial analysis and statistics combined with the establishment of prediction model, this paper uses the method of remote sensing metallogenic prediction and prospecting information, qualitatively and quantitatively to carry out metallogenic prediction in this area, and delineates the prospecting area. This paper mainly includes the following aspects:. 1) combining the metallogenic geological background of the study area, the ETM image is interpreted by remote sensing, and the information of gold mineralization remote sensing anomaly is extracted by principal component analysis and ratio method, including muddy anomaly, iron anomaly and silicification anomaly. 2) according to the geological anomaly and remote sensing anomaly information, the database of multi-source science information in this area is established, including basic geographical data, geological data and remote sensing data. Using MAPGIS software, the contour data of the study area are generated into DEM model, and the 3D visualization model of the research area is formed by combining the ETM remote sensing image and the basic geographic data. (4) using MAPGIS-MORPAS-ArcGIS software, the data of known gold deposits and geological anomalies and remote sensing anomalies in this area are analyzed in space, and the mineralization of various ore-controlling factors is summarized. 5) using ArcGIS software to carry out remote sensing metallogenic prediction in the study area, mainly analyzing the spatial superposition of each ore-controlling factor map layer. The area shown in the final prediction layer is the most favorable area for prospecting in this area, according to the metallogenic theory, Delineate 4 ore-prospecting scenic spots, among which A class 2, B class 2. (6) using MORPAS software to calculate the amount of ore-prospecting information in the study area, and delineating 5 ore-prospecting areas, of which A class 3 places and B grade 2 places, the results are compared with the results of remote sensing metallogenic prediction, the results of which are compared with those of remote sensing ore-forming prediction results. It was found that the prospecting areas delineated by the two methods were in good agreement with each other, which proved the feasibility and reliability of the two methods for metallogenic prediction. Figure 41, table 20, references 65
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P618.51;P208

【參考文獻】

相關(guān)期刊論文 前10條

1 陳勇敢;劉桂閣;王美娟;常春郊;馬德錫;;甘肅陽山金礦區(qū)遙感地質(zhì)特征及成礦預(yù)測[J];黃金科學(xué)技術(shù);2009年01期

2 白朝軍,陳瑞保;遙感技術(shù)在青藏高原空白區(qū)地質(zhì)填圖中的應(yīng)用[J];河南地質(zhì);2001年02期

3 李西,高建國,念紅良,陳仕炎;基于GIS礦區(qū)圖文綜合管理信息系統(tǒng)的構(gòu)建[J];昆明理工大學(xué)學(xué)報(理工版);2004年01期

4 念紅良,高建國,李西,陳仕炎;招遠金礦集中區(qū)遙感影像特征及綜合預(yù)測[J];昆明理工大學(xué)學(xué)報(理工版);2004年02期

5 劉燕君;遙感圖象中礦產(chǎn)信息的再現(xiàn)及其意義[J];科學(xué)通報;1983年16期

6 平仲良;萊州南部地區(qū)黃金資源遙感勘探[J];青島大學(xué)學(xué)報(自然科學(xué)版);1995年02期

7 曹烈,呂正祥,唐文清,尹福光;新疆西準噶爾哈圖-薩爾托海金成礦區(qū)成礦系列及成礦模式探討[J];特提斯地質(zhì);1998年00期

8 宋國耀,張曉華,肖克炎,朱裕生;礦產(chǎn)資源潛力評價的理論和GIS技術(shù)[J];物探化探計算技術(shù);1999年03期

9 廖崇高,楊武年,劉登忠,陳建平;基于GIS空間分析進行多源信息成礦預(yù)測[J];物探化探計算技術(shù);2002年02期

10 張建龍,游麗君,秦舉禮,蘭俊,劉智,李麗華;利用GIS空間分析功能進行礦產(chǎn)資源評價的方法研究[J];物探化探計算技術(shù);1997年03期

，

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