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REMOTE SENSING FOR LAND & RESOURCES    2012, Vol. 24 Issue (1) : 22-27     DOI: 10.6046/gtzyyg.2012.01.05
Technology and Methodology |
The Methodology of Lithologic Information Extraction by Using ASTER Data in West Kunlun Mountains
YU Jian1, ZHANG Zhi1, LI Min-jia2, CHEN Teng1, HE Wen-xi1
1. The Faculty of Earth Science, China University of Geosciences, Wuhan 430074, China;
2. The Faculty of Computer, China University of Geosciences, Wuhan 430074, China
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Abstract  Based on an analysis of mineral composition and spectral characteristics of samples collected in Bulunkou area of West Kunlun Mountains,the authors extracted the end-member spectra of lithologic units by using ASTER data of the study area,and the ASTER VNIR and SWIR data of the study area were processed by matched filtering method, and then nine important litholigic units in the study area were extracted. These lithologic units include biotite quartzite,biotite plagioclase gneiss,biotite quartz schist and biotite hornblende plagioclase gneiss which belong to Palaeoproterozoic Bulunkuole Group (Pt1) and chlorite sericite slate,black phyllite and sericite quartz schist that belong to Silurian Wenquangou Group (SW) as well as quartz diorite and tonalite. An analysis of geological data available and field survey results demonstrate that the method adopted by the authors can extract credible information and supply references to lithologic mapping and mineral exploration.
Keywords Guanzhong area      Land use/land cover change(LUCC)      Service value of ecosystem      Index of ecosystem’s capacity for supporting economy      RS      GIS     
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Issue Date: 07 March 2012
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HAO Hui-mei
HAO Yong-li
TIAN Dang-sheng
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HAO Hui-mei,HAO Yong-li,TIAN Dang-sheng. The Methodology of Lithologic Information Extraction by Using ASTER Data in West Kunlun Mountains[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(1): 22-27.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2012.01.05     OR     https://www.gtzyyg.com/EN/Y2012/V24/I1/22
[1] Rowan L C,Goetz A F H,Ashley R P.Discrimination of Hydrothermally Altered and Unaltered Rocks in Visible and Near Infrared Multispectral Images[J].Geophysics,1977,42(3):522-535.
[2] Goetz A F H,Rock B N,Rowan L C.Remote Sensing for Exploration:an Overview[J].Economic Geology,1983,78(4):573-590.
[3] Sultan M,Arvidson R E,Sturchio N C,et al.Lithologic Mapping in Arid Regions with Landsat Thematic Mapper data:Meatiq Dome,Egypt[J].Geological Society of America Bulletin,1987,99(6):748-762.
[4] Podwysocki M H,Mimms D L,Salisbury J W,et al.Analysis of Landsat-4 TM Data for Lithologic and Image Mapping Purpose[C]//Barker J.Landsat 4 Science Investigations Summary,Greenbelt,1984.
[5] Okada K,Segawa K,Hayashi I,et al.Removal of the Vegetation Effect from LANDSAT TM and GER Imaging Spectroradiometer Data[J].ISPRS Journal of Photogrammetry and Remote Sensing,1993,48(6):16-27.
[6] Abdelsalam M G,Stern R J,Berhane W G.Mapping Gossans in Arid Regions with Landsat TM and SIR-C Images:the Beddaho Alteration Zone in Northern Eritrea[J].Journal of African Earth Sciences,2000,30(4):903-916.
[7] Hubbard B E,Crowley J K.Mineral Mapping on the Chilean—Bolivian Altiplano Using Co-orbital ALI,ASTER and Hyperion Imagery:Data Dimensionality Issues and Solutions[J].Remote Sensing of Environment,2005,99(1/2):173-186.
[8] Rowan L C,Mars J C.Lithologic Mapping in the Mountain Pass,California Area Using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data[J].Remote Sensing of Environment,2003,84(3):350-366.
[9] 时丕龙,付碧宏,二宫芳树.基于ASTER VNIR—SWIR多光谱遥感数据识别与提取干旱地区岩性信息——以西南天山柯坪隆起东部为例[J].地质科学,2010,45(1):333-347.
[10] 朱黎江,秦其明,陈思锦.ASTER遥感数据解读与应用[J].国土资源遥感,2003(2):59-63.
[11] Yamaguchi Y,Kahle A B,Tsu H,et al.Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)[J].IEEE Transaction on Geoscience and Remote Sensing,1998,36(4):1062-1071.
[12] 张玉君,姚佛军.应用多光谱ASTER数据对ETM遥感异常的定性判别研究——以东昆仑五龙沟为例[J].岩石学报,2009,25(4):963-970.
[13] Gad S,Kusky T.ASTER Spectral Ratioing for Lithological Mapping in the Arabian-Nubian Shield,the Neoproterozoic Wadi Kidarea,Sinai,Egypt[J].Gondwana Research,2007,11(3):326-335.
[14] Ninomiya Y,Fu B H.Extracting Lithologic Information from ASTER Multispectral Thermal Infrared Data in the Northeastern Pamirs[J].Xinjiang Geology,2003,21(1):22-30.
[15] 关剑宇,赵祖应.新疆西昆仑地区切列克其—卓木吉勒尕富铁富铜矿床地质特征及成因类型探讨[J].新疆有色金属,2002(2):1-4.
[16] Iwasaki A,Fujisada H,Akao H,et al.Enhancement of Spectral Separation Performance for ASTER/SWIR[C]//The International Society for Optical Engineering.Proceedings of SPIE,2001:1-35.
[17] Hunt G R,Ashley R P.Spectra of Altered Rocks in the Visible and Near Infrared[J].Economy Geology,1979,74(7):1613-1629.
[18] Lyon R J P,Burns E A.Analysis of Rocks and Minerals by Reflected Infrared Radiation[J].Economic Geology,1963,58(2):274-284.
[19] Vincent R K,Thomson F.Spectral Compositional Imaging of Silicate Rocks[J].Journal of Geophysical Research,1972,77(14):2465-2472.
[20] Clark R N,King T V V,Klejwa M,et al.High Spectral Resolution Reflectance Spectroscopy of Minerals[J].Journal Geophysical Research,1990,95(B8):12653-12680.
[21] Grove C I,Hook S J,Paylor E D.Laboratory Reflectance Spectra of 160 Minerals,0.4 to 2.5 Micrometers[D].SUA:JPL Publication,1992.
[22] Hunt G R,Salisbury J W,Lenhoff C J,et al.Visible and Near Infrared Spectra of Minerals and Rocks:V.Halides,Phosphates,Arsenates,Vanadates and Borates[J].Modern Geology,1972(3):121-132.
[23] Knipling E B.Physical and Physiological Basis for the Reflectance of Visible and Near-infrared Radiation from Vegetation[J].Remote Sensing of Enviroment,1970(1):155-159.
[24] Roberts D A,Smith M O,Adams J B.Green Vegetation,Nonphotosynthetic Vegetation,and Soils in AVIRIS Data[J].Remote Sensing of Enviroment,1993,44(2/3):255-269.
[25] Boardman J W,Kruse F A.Automated Spectral Analysis:a Geological Example Using AVIRIS Data,North Grapevine Mountains,Nevada[C]//ERIM.Tenth Thematic Conference on Geologic Remote Sensing.Environmental Research Institute of Michigan,1994:1407-1418.
[26] Harsanyi J C,Chang C.Hyperspectral Image Classification and Dimensionality Reduction:an Orthogonal Subspace Projection Approach[J].IEEE Transactions on Geosience and Remote Sensing,1994,32(4):770-785.
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