本文選題：航天高光譜 + 航空高光譜��； 參考：《中國地質(zhì)大學(xué)(北京)》2017年碩士論文

【摘要】：高光譜遙感技術(shù)誕生后的幾十年里,已經(jīng)在眾多領(lǐng)域中投入實際應(yīng)用。其中,地質(zhì)勘查是應(yīng)用最為成功的領(lǐng)域之一。這是因為礦物填圖是地質(zhì)勘查工作中極為重要的一環(huán),而高光譜遙感超高的光譜分辨率對提高礦物填圖精度意義重大。國內(nèi)外已經(jīng)進行了許多高光譜礦物填圖技術(shù)及應(yīng)用研究,但在不同尺度高光譜數(shù)據(jù)、不同填圖方法的填圖效果對比研究方面還很少,本文在此基礎(chǔ)上,以新疆和布克賽爾縣白楊河地區(qū)為試驗區(qū),開展基于Hyperion衛(wèi)星高光譜和SASI航空高光譜數(shù)據(jù)的礦物填圖方法對比研究,完成的主要工作量和取得的主要成果如下:1.通過對Hyperion數(shù)據(jù)與SASI數(shù)據(jù)的預(yù)處理,包括輻射校正、幾何校正、大氣校正、壞像元去除等,獲取了礦物填圖方法對比研究所需的反射率數(shù)據(jù)。2.綜合利用PPI與SMACC兩種算法對航天Hyperion數(shù)據(jù)與航空SASI數(shù)據(jù)進行端元提取,建立了研究區(qū)圖像端元光譜庫,為本文開展礦物填圖對比研究奠定了基礎(chǔ)。3.通過對SAM、MTMF、SFF等三種礦物填圖方法的原理及基于Hyperion數(shù)據(jù)和基于SASI數(shù)據(jù)的高光譜礦物填圖效果的對比研究并經(jīng)野外驗證與樣品光譜測量,認(rèn)為對于Hyperion數(shù)據(jù),MTMFF填圖效果好于SAM和SFF算法。對于SASI航空高光譜數(shù)據(jù),SAM與MTMF礦物填圖也好于SFF算法;其中,對于高鋁絹云母、中鋁絹云母、低鋁絹云母等光譜特征十分相似的礦物,SAM與MTMF礦物效果相近,但在綠泥石與綠簾石礦物填圖方面,SAM填圖效果更好;在葉臘石與碳酸鹽等分布范圍都較小,且光譜吸收特征明顯的礦物來說,MTMF方法填圖效果更好,精度更高。4.通過對兩種不同尺度的高光譜數(shù)據(jù)的礦物填圖效果對比研究認(rèn)為SASI航空高光譜數(shù)據(jù)礦物填圖種類和精度明顯高于Hyperion數(shù)據(jù)。但兩種數(shù)據(jù)的礦物填圖結(jié)果在礦物大類和空間分布上具有較好的一致性,表明Hyperion數(shù)據(jù)在實際應(yīng)用中能滿足對蝕變礦物大類的檢出率要求。
[Abstract]:Hyperspectral remote sensing technology has been applied in many fields in recent decades. Among them, geological exploration is one of the most successful applications. This is because mineral mapping is a very important part of geological exploration, and hyperspectral remote sensing is of great significance to improve the precision of mineral mapping. Many hyperspectral mineral mapping techniques and applications have been carried out at home and abroad, but there are few comparative studies on the mapping effects of different scale hyperspectral data and different mapping methods. Taking the Baiyang River area of Xinjiang and Bukeser County as the experimental area, a comparative study of mineral mapping methods based on Hyperion satellite hyperspectral data and SASI aerial hyperspectral data is carried out. The main workload and the main results obtained are as follows: 1. By preprocessing Hyperion data and SASI data, including radiation correction, geometric correction, atmospheric correction and bad pixel removal, the reflectivity data of mineral mapping method is obtained. End-component extraction of aerospace Hyperion data and aeronautical SASI data was carried out by using PPI and SMACC algorithms, and the end-component spectral database of the study area was established, which laid a foundation for the comparative study of mineral mapping in this paper. Based on the principle of three mineral mapping methods, such as Hyperion data and SASI data, the comparative study on the effect of hyperspectral mineral mapping based on SASI data and field verification and sample spectral measurement, it is concluded that the mapping effect of Hyperion data is better than that of SAM and SFF algorithms. For SASI aerial hyperspectral data, the mineral mapping of SAM and MTMF is also better than that of SFF algorithm, among which, for the minerals with very similar spectral characteristics, such as high alumina sericite, medium aluminum sericite and low alumina sericite, the effect of MTMF mineral is similar. However, the mapping effect of SAM is better in the mineral mapping of chlorite and verdant, and the mapping effect of MTMF is better and the precision is higher for minerals with smaller distribution range of pyrophyllite and carbonate and obvious spectral absorption characteristics. By comparing the mineral mapping effects of two kinds of hyperspectral data of different scales, it is concluded that the types and accuracy of mineral mapping of SASI aerial hyperspectral data are obviously higher than those of Hyperion data. However, the mineral mapping results of the two kinds of data are in good agreement with each other in the mineral classification and spatial distribution, which indicates that the Hyperion data can meet the requirements for the detection rate of altered minerals in practical applications.
【學(xué)位授予單位】：中國地質(zhì)大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：P627
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本文編號：1778150