长白山天池火山喷发物遥感影像特征研究
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摘要
长白山天池火山位于中朝边界,地势复杂,天池湖2/3的水体和天池火山锥体大约1/4的部分隶属于朝鲜民主主义共和国,用常规手段难以从大区域来研究火山喷发物的分布范围。尽管前人对长白山天池火山一直在进行着较全面的地质调查和岩石学等方面的研究工作,已经在火山喷发期次的确定、喷发物岩性及边界的确定等方面取得了不少研究成果。但从大区域来研究天池火山喷发物的空间分布一直处于较为薄弱的环节。遥感技术具有快速获取大范围数据但受条件限制少的特点,可为解决这一问题提供了帮助。而长白山天池火山植被发育好,遥感影像受植被影响大,使仅仅利用可见光遥感影像去判别喷发物的空间分布范围存在了难度。因此,本文引入DEM的地形分析技术,研究了长白山天池火山喷发物的地形地貌学特征,再结合遥感影像的光谱分析和纹理分析技术,研究了ASTER及IKONOS影像的长白山天池火山喷发物的光谱特征以及纹理特征,最后利用了提取的影像特征来推测了前人未涉及地区的喷发物空间分布范围。本研究成果为开展长白山天池火山的大比例尺火山地质填图,特别是对于某些全新世火山喷发物范围和界限的厘定提供了遥感学依据。
利用DEM的地形分析技术,得到了长白山天池火山锥体附近范围地区的立体地形图,经过解译得到了研究区内的火山口及小火山锥的分布图和水系河谷的分布图,通过对天池火山锥体地区更新世粗面岩以及全新世喷发物地形地貌特征分析,得出初步结论:1)天池火山更新世造锥时期不同阶段的粗面岩呈垄状分布,四个喷发阶段的分布范围有明显的层次性,后一阶段的造锥喷发物往往堆积在前一阶段喷发物之上。总体来说,喷发年代越早,则分布距火口越远,其坡度越缓,高程也越低。通过由中国境内造锥粗面岩的上述分布特点,推测了研究区内位于朝鲜境内的造锥喷发物分布范围;2)天池火山全新世喷发物有着显著的地形地貌上特征,如气象站期的碱流质碎成熔岩呈长垄状分布,流动单元的整体特征明显;锥体附近全新世的滑坡堆积,其分布范围主要受控于于地形坡度;火山泥石流主要限于河谷低洼地带,其流动向在由DEM所生成的三维透视图中表现明显。故利用DEM数据进行地形地貌分析对于确定形貌特征突出的喷发物分布范围很有帮助,如更新世的几次造锥喷发物以及全新式的泥石流。
对遥感影像定量化处理,通过公式反演了Aster影像的辐射率,由于在反演反射率上方法很多,但没有非常公认的方法,故采用了Log Residuals反演和FLAASH模块反演两种方法,并用K-Means非监督分类法对以上三种反演的影像进行分类,经检验发现两个反射率图像的分类精度均不如辐射率图像,因此在使用光谱分析时应用了辐射率影像。通过光谱分析提取了粗面岩和浮岩的光谱特征曲线,但由于植被覆盖程度高,只确定了喷发物中裸露粗面岩和浮岩的分布范围,但也可以使用间接方法来确定喷发物分布范围,如火口内壁凹兜是已经风化成土壤的近代的喷发物堆积物,故凹兜内苔原带植被的分布范围就是近代的喷发物堆积物的范围。同时研究了粗面岩及浮岩在坡度,坡向上的特征,发现裸露岩石有暗色调与亮色调两种的原因,一方面可能为前者主要在向阳面,后者主要在背阳面,引起同物异谱,另一方面可能因为前者大都位于火口的东南方向,而这个方向浮岩覆盖程度高,可能是粗面岩和少量浮岩混合而成。
由于所用IKONOS影像为真彩色影像,对照野外实际的照片和长白山植被分布带,建立了初步解译标志,据此选取了八种训练样本类别,并使用使用波谱角技术(SAM)进行分类,经过混淆矩阵评价分类结果不理想,可能是其在合成过程忠光谱信息丢失严重,但纹理信息好,引入了ENVI的二阶概率矩阵法的纹理分析,并利用差异性(Dissimilarity)纹理特征图对地物建立了纹理解译标志,并解译形成了火口附近近代火山泥石流的分布区域。利用光谱和纹理结合的方法进行分类,提高了分类精度,确定了浮岩的分布范围,并做出其厚度分布图,同时分析了不同厚度浮岩的地形特征。
长白山天池火山地区地势复杂且植被覆盖多,仅利用地质或可见光遥感手段往往较难从大区域确定准确火山喷发物的空间分布范围,结合DEM的地形分析会在一定程度上弥补这一缺陷。利用高空间分辨率影像IKONOS及多光谱影像ASTER并结合了DEM分析技术,得到了更新世以来喷发物的地形地貌特征和光谱特征和纹理特征,对火山喷发物的空间分布范围边界确定提供了辅助依据,在今后的工作中,需要进一步加强不同类型喷发物地形地貌特征的野外调查和复核,使其真正成为编制火山地质图和进行火山灾害危险性评价的重要工具之一。
The terrain of the Changbaishan Tianchi volcano on the border between china and North Korea is complex, and traffic is not very convenient. The two third of the Tianchi Lake and one fourth of the cone of the Tianchi volcano belong to the Democratic Republic of Korea. In the present conditions, it’s hard to study the spatial distribution of the volcanic eruptive products by conventional means from a large regional scope. In the Changbaishan Tianchi volcano, the predecessors are continuously carrying on the research work of the comprehensive geological investigation and petrology, and they have already obtained many research results in the determination of volcanic effusive stages and the volcanic eruptive products lithology and the boundary, but the studies in the spatial distribution of the eruptive products have been a weak link. The remote sensing technology can gain the wide range data with little limit, so it might help solve this problem. But the vegetation of the Changbaishan mountains grows well, which affects the quality of the remote sensing images, causes the difficulty to use the visible spectral remote sensing image to distinguish spatial distribution of the volcanic eruptive products. Therefore, by the technology of DEM terrain analysis, this thesis studies the geomorphologic characteristics of the Changbaishan Tianchi volcanic eruptive products, then, by the technology of remote sensing spectral analysis and texture analysis, studies the spectral and texture characteristics of the Changbaishan Tianchi volcanic eruption on the ASTER and IKONOS images. Finally, this work uses these image characteristics to speculate the spatial distribution of the volcanic eruptive products where the predecessors did not work. These results can provide a remote sensing basis for making the large-scale volcanic geological maps of the Tianchi volcano, in the Changbai Mountains, and especially for determining the scope and limits of some Holocene volcanic eruptive products.
Making use of the terrain analysis technology of DEM, this work can gets the three-dimensional topographical map of the vicinity of the Changbaishan Tianchi volcanic cone, and through the interpretation of the study area it gains the distribution of the crater and volcanic cone and the distribution of the water systems and valleys. Through the landscape feature analysis of the rough areas of Pleistocene and Holocene rock eruption of the Tianchi volcano cone, this work comes to the preliminary conclusion: at the different stages of the Pleistocene , the Tianchi volcano cone had a ridge-like distribution of the rough rock, and the distribution of the four stages of the eruption had obvious levels, and often the cone eruption of a later stage accumulated on the previous stage of eruption. Generally speaking, the earlier eruption was located far away from the Burner and the ease of its slope, and the lower elevation. From the distributing character of the Chinese-made cone rough rocks mentioned above, this thesis speculates the Korean-made cone eruption of distribution in the study area. Tianchi volcano eruption of the Holocene has significant characteristics of the topography, such as the weather station of the base crumbled into liquid lava has a long ridge-like distribution, the overall flow unit features obviously; the Holocene landslide accumulation near the cone whose distribution mainly controlled by the terrain gradient; volcanic debris flow mainly confined to low-lying valley, of which flows have a significant performance in the 3-D perspective generated by the DEM . Therefore, using the DEM topography data to analyze the physiognomy is useful to determine the distribution of prominent morphology of the eruption, such as several cones produced in the Pleistocene and the eruption of new-style mud-rock flow.
Processing the remote sensing image, inversing the radiation rate of Aster image by the formula, there are many ways to inverse the rate of reflection, but no very acceptable methodology. So this work takes advantage of the Log Residuals inversion and the FLAASH inversion two methods module ,and using the K-Means of unsupervised classification to class the above three inversion of the image. The inspection found that the classification accuracy rate of two reflectivity images is worse than the radiation images, so the radiance image is used in the spectral analysis. By the spectral analysis the characteristic curve of the rough and pumice spectra is obtained. Due to a high degree of vegetation coverage, only the range of the bare rock and the rough rocks in the eruption is identified, but the indirect method can be used to determine the eruption range, like the concave wall had already air slaked into the soil of the modern eruption deposits, so the distribution of the tundra vegetation is namely the distribution scope of the accumulation of the modern eruptions. At the same time researching the rough rock and pumice on the slope, the characteristics of the upward slope , it found out the reasons that a bare rock has dark and bright two tones. On the one hand the former was likely to face the sun, the latter mainly in the back-face, causing the different Spectrums of the same. On the other hand, probably because most of the former are located to the southeast of Burner , and the high degree of coverage of floating rock in the direction, may be the mixture of rough rocks and a small amount of pumice.
Since the purchase of 1 m of the IKONOS images are true color, contrasting the field photographs with the distribution of vegetation of the Changbaishan zone, establishing a preliminary interpretation symbol, which selected eight types of training samples are selected and the spectral angle technology (SAM) is used to get the classification. The result of classification after confusion matrix evaluation is not satisfactory, maybe a serious loss of spectrum information in the synthesizing process, but the texture information is enough. This work introduces the texture analysis of the ENVI probability matrix method taking advantage of dissimilarity texture feature pictures to establish the symbol of the texture interpretation and interpret the distributing area of formation the modern Burner volcanic debris flow. Using the combination of spectrum and texture to do the classification, this work enhances the accuracy of classification and determines the distributing of the pumice and a distribution of its thickness, and terrain characters of different thickness pumices.
The terrain of the Changbaishan Tianchi volcano is complex and highly vegetation-covered, it is often difficult to determine the precise spatial distribution region of the volcanic eruptive products only using the geological or visible remote sensing technology. The terrain analysis with DEM will be a certain extent compensate for this deficiency. Using high spatial resolution IKONOS images and multi-spectral imaging ASTER and combined with DEM analysis technology, this work obtains the terrain features and spectral characteristics and texture characteristics of eruptive products since the Pleistocen, and provides the support to determine the boundary of the spatial distribution of the volcanic eruptive products. In the future work, it is needed to further strengthen the field investigation and inspection of the terrain features of different types of eruptive products, so that it will truly become one of the tools which can be used to make a volcano geological map and evaluate volcanic hazards evaluation.
利用DEM的地形分析技术,得到了长白山天池火山锥体附近范围地区的立体地形图,经过解译得到了研究区内的火山口及小火山锥的分布图和水系河谷的分布图,通过对天池火山锥体地区更新世粗面岩以及全新世喷发物地形地貌特征分析,得出初步结论:1)天池火山更新世造锥时期不同阶段的粗面岩呈垄状分布,四个喷发阶段的分布范围有明显的层次性,后一阶段的造锥喷发物往往堆积在前一阶段喷发物之上。总体来说,喷发年代越早,则分布距火口越远,其坡度越缓,高程也越低。通过由中国境内造锥粗面岩的上述分布特点,推测了研究区内位于朝鲜境内的造锥喷发物分布范围;2)天池火山全新世喷发物有着显著的地形地貌上特征,如气象站期的碱流质碎成熔岩呈长垄状分布,流动单元的整体特征明显;锥体附近全新世的滑坡堆积,其分布范围主要受控于于地形坡度;火山泥石流主要限于河谷低洼地带,其流动向在由DEM所生成的三维透视图中表现明显。故利用DEM数据进行地形地貌分析对于确定形貌特征突出的喷发物分布范围很有帮助,如更新世的几次造锥喷发物以及全新式的泥石流。
对遥感影像定量化处理,通过公式反演了Aster影像的辐射率,由于在反演反射率上方法很多,但没有非常公认的方法,故采用了Log Residuals反演和FLAASH模块反演两种方法,并用K-Means非监督分类法对以上三种反演的影像进行分类,经检验发现两个反射率图像的分类精度均不如辐射率图像,因此在使用光谱分析时应用了辐射率影像。通过光谱分析提取了粗面岩和浮岩的光谱特征曲线,但由于植被覆盖程度高,只确定了喷发物中裸露粗面岩和浮岩的分布范围,但也可以使用间接方法来确定喷发物分布范围,如火口内壁凹兜是已经风化成土壤的近代的喷发物堆积物,故凹兜内苔原带植被的分布范围就是近代的喷发物堆积物的范围。同时研究了粗面岩及浮岩在坡度,坡向上的特征,发现裸露岩石有暗色调与亮色调两种的原因,一方面可能为前者主要在向阳面,后者主要在背阳面,引起同物异谱,另一方面可能因为前者大都位于火口的东南方向,而这个方向浮岩覆盖程度高,可能是粗面岩和少量浮岩混合而成。
由于所用IKONOS影像为真彩色影像,对照野外实际的照片和长白山植被分布带,建立了初步解译标志,据此选取了八种训练样本类别,并使用使用波谱角技术(SAM)进行分类,经过混淆矩阵评价分类结果不理想,可能是其在合成过程忠光谱信息丢失严重,但纹理信息好,引入了ENVI的二阶概率矩阵法的纹理分析,并利用差异性(Dissimilarity)纹理特征图对地物建立了纹理解译标志,并解译形成了火口附近近代火山泥石流的分布区域。利用光谱和纹理结合的方法进行分类,提高了分类精度,确定了浮岩的分布范围,并做出其厚度分布图,同时分析了不同厚度浮岩的地形特征。
长白山天池火山地区地势复杂且植被覆盖多,仅利用地质或可见光遥感手段往往较难从大区域确定准确火山喷发物的空间分布范围,结合DEM的地形分析会在一定程度上弥补这一缺陷。利用高空间分辨率影像IKONOS及多光谱影像ASTER并结合了DEM分析技术,得到了更新世以来喷发物的地形地貌特征和光谱特征和纹理特征,对火山喷发物的空间分布范围边界确定提供了辅助依据,在今后的工作中,需要进一步加强不同类型喷发物地形地貌特征的野外调查和复核,使其真正成为编制火山地质图和进行火山灾害危险性评价的重要工具之一。
The terrain of the Changbaishan Tianchi volcano on the border between china and North Korea is complex, and traffic is not very convenient. The two third of the Tianchi Lake and one fourth of the cone of the Tianchi volcano belong to the Democratic Republic of Korea. In the present conditions, it’s hard to study the spatial distribution of the volcanic eruptive products by conventional means from a large regional scope. In the Changbaishan Tianchi volcano, the predecessors are continuously carrying on the research work of the comprehensive geological investigation and petrology, and they have already obtained many research results in the determination of volcanic effusive stages and the volcanic eruptive products lithology and the boundary, but the studies in the spatial distribution of the eruptive products have been a weak link. The remote sensing technology can gain the wide range data with little limit, so it might help solve this problem. But the vegetation of the Changbaishan mountains grows well, which affects the quality of the remote sensing images, causes the difficulty to use the visible spectral remote sensing image to distinguish spatial distribution of the volcanic eruptive products. Therefore, by the technology of DEM terrain analysis, this thesis studies the geomorphologic characteristics of the Changbaishan Tianchi volcanic eruptive products, then, by the technology of remote sensing spectral analysis and texture analysis, studies the spectral and texture characteristics of the Changbaishan Tianchi volcanic eruption on the ASTER and IKONOS images. Finally, this work uses these image characteristics to speculate the spatial distribution of the volcanic eruptive products where the predecessors did not work. These results can provide a remote sensing basis for making the large-scale volcanic geological maps of the Tianchi volcano, in the Changbai Mountains, and especially for determining the scope and limits of some Holocene volcanic eruptive products.
Making use of the terrain analysis technology of DEM, this work can gets the three-dimensional topographical map of the vicinity of the Changbaishan Tianchi volcanic cone, and through the interpretation of the study area it gains the distribution of the crater and volcanic cone and the distribution of the water systems and valleys. Through the landscape feature analysis of the rough areas of Pleistocene and Holocene rock eruption of the Tianchi volcano cone, this work comes to the preliminary conclusion: at the different stages of the Pleistocene , the Tianchi volcano cone had a ridge-like distribution of the rough rock, and the distribution of the four stages of the eruption had obvious levels, and often the cone eruption of a later stage accumulated on the previous stage of eruption. Generally speaking, the earlier eruption was located far away from the Burner and the ease of its slope, and the lower elevation. From the distributing character of the Chinese-made cone rough rocks mentioned above, this thesis speculates the Korean-made cone eruption of distribution in the study area. Tianchi volcano eruption of the Holocene has significant characteristics of the topography, such as the weather station of the base crumbled into liquid lava has a long ridge-like distribution, the overall flow unit features obviously; the Holocene landslide accumulation near the cone whose distribution mainly controlled by the terrain gradient; volcanic debris flow mainly confined to low-lying valley, of which flows have a significant performance in the 3-D perspective generated by the DEM . Therefore, using the DEM topography data to analyze the physiognomy is useful to determine the distribution of prominent morphology of the eruption, such as several cones produced in the Pleistocene and the eruption of new-style mud-rock flow.
Processing the remote sensing image, inversing the radiation rate of Aster image by the formula, there are many ways to inverse the rate of reflection, but no very acceptable methodology. So this work takes advantage of the Log Residuals inversion and the FLAASH inversion two methods module ,and using the K-Means of unsupervised classification to class the above three inversion of the image. The inspection found that the classification accuracy rate of two reflectivity images is worse than the radiation images, so the radiance image is used in the spectral analysis. By the spectral analysis the characteristic curve of the rough and pumice spectra is obtained. Due to a high degree of vegetation coverage, only the range of the bare rock and the rough rocks in the eruption is identified, but the indirect method can be used to determine the eruption range, like the concave wall had already air slaked into the soil of the modern eruption deposits, so the distribution of the tundra vegetation is namely the distribution scope of the accumulation of the modern eruptions. At the same time researching the rough rock and pumice on the slope, the characteristics of the upward slope , it found out the reasons that a bare rock has dark and bright two tones. On the one hand the former was likely to face the sun, the latter mainly in the back-face, causing the different Spectrums of the same. On the other hand, probably because most of the former are located to the southeast of Burner , and the high degree of coverage of floating rock in the direction, may be the mixture of rough rocks and a small amount of pumice.
Since the purchase of 1 m of the IKONOS images are true color, contrasting the field photographs with the distribution of vegetation of the Changbaishan zone, establishing a preliminary interpretation symbol, which selected eight types of training samples are selected and the spectral angle technology (SAM) is used to get the classification. The result of classification after confusion matrix evaluation is not satisfactory, maybe a serious loss of spectrum information in the synthesizing process, but the texture information is enough. This work introduces the texture analysis of the ENVI probability matrix method taking advantage of dissimilarity texture feature pictures to establish the symbol of the texture interpretation and interpret the distributing area of formation the modern Burner volcanic debris flow. Using the combination of spectrum and texture to do the classification, this work enhances the accuracy of classification and determines the distributing of the pumice and a distribution of its thickness, and terrain characters of different thickness pumices.
The terrain of the Changbaishan Tianchi volcano is complex and highly vegetation-covered, it is often difficult to determine the precise spatial distribution region of the volcanic eruptive products only using the geological or visible remote sensing technology. The terrain analysis with DEM will be a certain extent compensate for this deficiency. Using high spatial resolution IKONOS images and multi-spectral imaging ASTER and combined with DEM analysis technology, this work obtains the terrain features and spectral characteristics and texture characteristics of eruptive products since the Pleistocen, and provides the support to determine the boundary of the spatial distribution of the volcanic eruptive products. In the future work, it is needed to further strengthen the field investigation and inspection of the terrain features of different types of eruptive products, so that it will truly become one of the tools which can be used to make a volcano geological map and evaluate volcanic hazards evaluation.
引文
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刘诚,阚瑞峰,Hiroaki KUZE2,等.2006.从ASTER和Landsat/TM卫星数据反演日本千叶地区地表反射率和气溶胶光学厚度分布[J].遥感学报,10(5):756-761.
李建华. 1996.利用卫星图像研究华北平原北西向隐伏活动断裂[J].国土资源遥感.(1): 29-35.
刘德富罗灼礼.1997.强烈地震前的OLR异常现象[J].地震,17(2): 126-132.
刘若新,魏海泉,李继泰,等. 1995.长白山天池火山[C].火山作用与人类环境:地震出版社, 1-13.
刘若新,樊祺诚,郑祥身等. 1998.长白山天池火山岩浆演化.中国科学(D辑), 28(3): 226-231.
刘若新. 2000.中国的活火山[M].北京:地震出版社, 22-23.
刘若新等译. 2001.火山监测与减灾/(意大利)R.Scarpa,(美)R.I.Tilling著.地震出版社.
刘若新,魏海泉,李继泰. 1998.长白山天池火山近代喷发[M].北京:科学出版社.
刘龙飞,陈云浩,李京.2003.遥感影像纹理分析方法综述与展望[J].遥感技术与应用,18(6):441-447.
刘龙飞.2004.纹理分析在高分辨率遥感影像分类中的应用——以城郊结合带IKONOS影像为例.硕士论文.北京师范大学.
马金清. 2000.火山构造组合研究和地质填图方法—以福建闽清测区1:5万区域地质调查为例[J].中国区域地质, 19(2):198-204.
千葉達朗. 2006.活火山活断層赤色立体地図でみる日本の凸凹[M].日本:技術評論社.
全晓萍,宋志勇.2007.基于DEM数据的地形分析研究与实现[J].科技信息-计算机与信息技术,(28):53.
单新建,陈国光,叶洪. 2000.利用数字遥感图像研究长白山天池火山近代喷发规模[J].地震地质, 22(2):187-193.
单新建,叶洪,陈国光,等. 2001.利用多源数据融合研究长白山天池火山的喷发期次及空间分布[J].自然灾害学报, 10(2):107-112.
单新建,叶洪,陈国光. 2002.利用ERS2-SAR图像纹理分析方法揭示长白山天池火山近代喷发物空间分布特征[J].第四纪研究. 22(2):123-129.
宋秋艳,陈学工. 2007.利用DEM制作彩色晕渲图[J].湖南科技学院学报, 28(9):104-105.
汤国安,刘学军,房亮,等. 2006.DEM及数字地形分析中尺度问题研究综述[J].武汉大学学报·信息科学版,31[12]:1060-1066.
汤国安,刘学军,闾国军.2005.数字高程模型及地学分析的原理与方法[M].北京:科学出版社.
汤国安,杨昕.2006.ArcGIS地理信息系统空间分析实验教程.北京:科学出版社.
田庆久,郑兰芬,童庆禧.1998.基于遥感影像的大气辐射校正和反射率反演方法[J].应用气象学报,9(4):456~461.
王青华,王润生.2000.高光谱遥感技术在岩石识别中的应用[J].国土资源遥感,(4): 39-43.
魏海泉,李春茂,金伯禄,等. 2005.长白山天池火山造锥喷发岩浆演化系列与地层划分[J].吉林地质, 24(1):22-27.
魏海泉,金伯禄,刘永顺. 2004.长白山天池火山地质学研究的若干进展与灾害分析[J].岩石矿物学杂志, 23(4):305-312.
吴昀昭,田庆久,金震宇等. 2004.ETM十数据绝对反射率反演方法分析[J].遥感信息,(2):9-12.
邬伦,刘瑜,等. 2001.《地理信息系统--原理、方法和应用》.北京:科学出版社.
徐文铎,何兴元,陈玮,等. 2004.长白山植被类型特征与演替规律的研究.生态学杂志, 23(5): 162-174
燕守勋. 2004.高光谱遥感岩矿识别填图的技术流程与主要技术方法综述[J].遥感技术与应用, 19(1):52-63.
杨淑莹,胡军,曹作良. 2001.基于图像纹理分析的目标物体识别方法.天津理工学院学报. 17(4):30-33.
尹功明,业渝光,万京林,等. 1999.长白山地区近代火山岩的ESR测年研究[J],地质论评, 45(增刊):287-293.
赵建华,杨树锋,陈汉林.2004.基于分形纹理的遥感图像岩性识别方法[J].遥感信息,(2): 2-4.
周军,高鹏,田勤虎,等. 2005.新疆巴里坤ETM数据遥感地质填图的探索[J].国土资源遥感, (3):57-65.
周云轩,王磊.2002.基于DEM的G I S地形分析的实现方法研究.计算机应用研究,(12): 50-53.
周廷刚,郭达志,盛业华. 2000.灰度矢量多波段遥感影像纹理特征及其描述.西安科技学院学报. 20(4):336-338.
周云轩,王磊.2001.基于DEM的GIS地形分析的实现方法研究.计算机应用研究,2002(12):50-53
朱亮璞,刘允良,张福祥,等.1994.遥感地质学[M].北京:地质出版社.
Bing Xu, Peng Gong, Edmund Seto,et al. 2003. Comparison of Gray level Reduction and Different Texture Spectrum Encoding Methods for Land-Use Classifiction Using a Panchromatic IKONOS Image ,University of Califonria, Berkeley.
Crowley J.K.1984.Symposium on remote Sensing of Environment,Third Thematic Conference:Remote Sensing for Exploration Geology:837-852.
G Onorati, R Ventura, M Poscolieri, et al.1992.The Digital Elevation Model of Italy forgeomorphology and structural geology[J].CATENA,19(2):147-178.
Gong P ,Mahler SA,Bing G S , et al. 2003.Vinyard identification in an oak woodland Landscape with airborne digital camera imagery,[J ].In tenrational Jounral of Remote Sensing,24(6),1303-1315
Hunt G R.1989.Spectroscopic Properties of Rocks and Minerals[A].In Practical Handbook of Physical Properties of Rocks and Minerals[C].Edited by Carmichael R C.Boca Raton Florid:C R C Press lnc: 599～669.
Kahle, A.B., D.P.Madura, J.M. Soha. 1980.Middle infrared multispectral aircraft scanner data: Analysis for geological applications[J].Appl. Optics, 19:2279-2290.
Kahle A B, Gillespie A R, Abbott E A, et a.1988.Relative dating of Hawaiian lava flows using multispectral thermal infrared images a newtool for geologic mapping of young volcanic terranes [M].Journal of Geophysical Research.
Kuhni A , Pfiffner O.A. 2001.The relief of the Swiss Alps and adjacent areas and its relation to lithology and structure: topographic analysis from a 250-m DEM[J]. Geomorphology, 41(4):285–307.
M W Matthew,S M Adler-Colden,A Berk.G Felde , et al.2003.Atmos-pheric correction of spectral imagery:Evaluation of the FLAASH algorithm with AVIRIS data[C].Presented at SPIE Proceeding,Algorithm and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery IX..
Narasimha Rao P V, Sesha Sai M V R, Sreenvivas K. 2002.Textural analysis of IRS-1D panchromatic data for land cover classification[J ].International Journal of Remote Sensing, 23(17),3327-3345
Shahan M A and D iskshit O. 2001. Improvement of classification in urban areas by the use of Textural features:the case of Lucknow city,Uttar Pradesh[J ].International Journal of Remote Sensing, 22(4),565-593
Yoshiki Ninomiya, Bi-Hong Fu. 2003.EXTRACTING LITHOLOGIC INFORMATION FROM ASTER MULTISPECTRAL THERMAL INFRARED DATA IN THE NORTHEASTERN PAMIRS[J].XINJANG GEOLOGY,21(1): 22-30.
Walker R F,Jackeay P T,Longstaff I D. 1997. Recent developments in the use of the co-occurrence matrix for texture recognition. Proc of 13th Internation Conference on Digital Image Processing.Greece.
毕华兴,谭秀英,李笑吟.2005.基于DEM的数字地形分析[J].北京林业大学学报,27(2):49-53.
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黄昕,张良培. 2007.基于光谱变换与融合的IKONOS多光谱影像分类[J].武汉大学学报·信息科学版. 22(6)
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李军,黄敬峰. 2007.基于DEM的山地可照时间的空间分布[J].浙江大学学报(理学版), 34(3):346-350.
李轶平,吴泉源,邹敏,等. 2007.基于DEM的龙口市林地表面积调查[J].遥感信息,(3):67-70.
刘诚,阚瑞峰,Hiroaki KUZE2,等.2006.从ASTER和Landsat/TM卫星数据反演日本千叶地区地表反射率和气溶胶光学厚度分布[J].遥感学报,10(5):756-761.
李建华. 1996.利用卫星图像研究华北平原北西向隐伏活动断裂[J].国土资源遥感.(1): 29-35.
刘德富罗灼礼.1997.强烈地震前的OLR异常现象[J].地震,17(2): 126-132.
刘若新,魏海泉,李继泰,等. 1995.长白山天池火山[C].火山作用与人类环境:地震出版社, 1-13.
刘若新,樊祺诚,郑祥身等. 1998.长白山天池火山岩浆演化.中国科学(D辑), 28(3): 226-231.
刘若新. 2000.中国的活火山[M].北京:地震出版社, 22-23.
刘若新等译. 2001.火山监测与减灾/(意大利)R.Scarpa,(美)R.I.Tilling著.地震出版社.
刘若新,魏海泉,李继泰. 1998.长白山天池火山近代喷发[M].北京:科学出版社.
刘龙飞,陈云浩,李京.2003.遥感影像纹理分析方法综述与展望[J].遥感技术与应用,18(6):441-447.
刘龙飞.2004.纹理分析在高分辨率遥感影像分类中的应用——以城郊结合带IKONOS影像为例.硕士论文.北京师范大学.
马金清. 2000.火山构造组合研究和地质填图方法—以福建闽清测区1:5万区域地质调查为例[J].中国区域地质, 19(2):198-204.
千葉達朗. 2006.活火山活断層赤色立体地図でみる日本の凸凹[M].日本:技術評論社.
全晓萍,宋志勇.2007.基于DEM数据的地形分析研究与实现[J].科技信息-计算机与信息技术,(28):53.
单新建,陈国光,叶洪. 2000.利用数字遥感图像研究长白山天池火山近代喷发规模[J].地震地质, 22(2):187-193.
单新建,叶洪,陈国光,等. 2001.利用多源数据融合研究长白山天池火山的喷发期次及空间分布[J].自然灾害学报, 10(2):107-112.
单新建,叶洪,陈国光. 2002.利用ERS2-SAR图像纹理分析方法揭示长白山天池火山近代喷发物空间分布特征[J].第四纪研究. 22(2):123-129.
宋秋艳,陈学工. 2007.利用DEM制作彩色晕渲图[J].湖南科技学院学报, 28(9):104-105.
汤国安,刘学军,房亮,等. 2006.DEM及数字地形分析中尺度问题研究综述[J].武汉大学学报·信息科学版,31[12]:1060-1066.
汤国安,刘学军,闾国军.2005.数字高程模型及地学分析的原理与方法[M].北京:科学出版社.
汤国安,杨昕.2006.ArcGIS地理信息系统空间分析实验教程.北京:科学出版社.
田庆久,郑兰芬,童庆禧.1998.基于遥感影像的大气辐射校正和反射率反演方法[J].应用气象学报,9(4):456~461.
王青华,王润生.2000.高光谱遥感技术在岩石识别中的应用[J].国土资源遥感,(4): 39-43.
魏海泉,李春茂,金伯禄,等. 2005.长白山天池火山造锥喷发岩浆演化系列与地层划分[J].吉林地质, 24(1):22-27.
魏海泉,金伯禄,刘永顺. 2004.长白山天池火山地质学研究的若干进展与灾害分析[J].岩石矿物学杂志, 23(4):305-312.
吴昀昭,田庆久,金震宇等. 2004.ETM十数据绝对反射率反演方法分析[J].遥感信息,(2):9-12.
邬伦,刘瑜,等. 2001.《地理信息系统--原理、方法和应用》.北京:科学出版社.
徐文铎,何兴元,陈玮,等. 2004.长白山植被类型特征与演替规律的研究.生态学杂志, 23(5): 162-174
燕守勋. 2004.高光谱遥感岩矿识别填图的技术流程与主要技术方法综述[J].遥感技术与应用, 19(1):52-63.
杨淑莹,胡军,曹作良. 2001.基于图像纹理分析的目标物体识别方法.天津理工学院学报. 17(4):30-33.
尹功明,业渝光,万京林,等. 1999.长白山地区近代火山岩的ESR测年研究[J],地质论评, 45(增刊):287-293.
赵建华,杨树锋,陈汉林.2004.基于分形纹理的遥感图像岩性识别方法[J].遥感信息,(2): 2-4.
周军,高鹏,田勤虎,等. 2005.新疆巴里坤ETM数据遥感地质填图的探索[J].国土资源遥感, (3):57-65.
周云轩,王磊.2002.基于DEM的G I S地形分析的实现方法研究.计算机应用研究,(12): 50-53.
周廷刚,郭达志,盛业华. 2000.灰度矢量多波段遥感影像纹理特征及其描述.西安科技学院学报. 20(4):336-338.
周云轩,王磊.2001.基于DEM的GIS地形分析的实现方法研究.计算机应用研究,2002(12):50-53
朱亮璞,刘允良,张福祥,等.1994.遥感地质学[M].北京:地质出版社.
Bing Xu, Peng Gong, Edmund Seto,et al. 2003. Comparison of Gray level Reduction and Different Texture Spectrum Encoding Methods for Land-Use Classifiction Using a Panchromatic IKONOS Image ,University of Califonria, Berkeley.
Crowley J.K.1984.Symposium on remote Sensing of Environment,Third Thematic Conference:Remote Sensing for Exploration Geology:837-852.
G Onorati, R Ventura, M Poscolieri, et al.1992.The Digital Elevation Model of Italy forgeomorphology and structural geology[J].CATENA,19(2):147-178.
Gong P ,Mahler SA,Bing G S , et al. 2003.Vinyard identification in an oak woodland Landscape with airborne digital camera imagery,[J ].In tenrational Jounral of Remote Sensing,24(6),1303-1315
Hunt G R.1989.Spectroscopic Properties of Rocks and Minerals[A].In Practical Handbook of Physical Properties of Rocks and Minerals[C].Edited by Carmichael R C.Boca Raton Florid:C R C Press lnc: 599～669.
Kahle, A.B., D.P.Madura, J.M. Soha. 1980.Middle infrared multispectral aircraft scanner data: Analysis for geological applications[J].Appl. Optics, 19:2279-2290.
Kahle A B, Gillespie A R, Abbott E A, et a.1988.Relative dating of Hawaiian lava flows using multispectral thermal infrared images a newtool for geologic mapping of young volcanic terranes [M].Journal of Geophysical Research.
Kuhni A , Pfiffner O.A. 2001.The relief of the Swiss Alps and adjacent areas and its relation to lithology and structure: topographic analysis from a 250-m DEM[J]. Geomorphology, 41(4):285–307.
M W Matthew,S M Adler-Colden,A Berk.G Felde , et al.2003.Atmos-pheric correction of spectral imagery:Evaluation of the FLAASH algorithm with AVIRIS data[C].Presented at SPIE Proceeding,Algorithm and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery IX..
Narasimha Rao P V, Sesha Sai M V R, Sreenvivas K. 2002.Textural analysis of IRS-1D panchromatic data for land cover classification[J ].International Journal of Remote Sensing, 23(17),3327-3345
Shahan M A and D iskshit O. 2001. Improvement of classification in urban areas by the use of Textural features:the case of Lucknow city,Uttar Pradesh[J ].International Journal of Remote Sensing, 22(4),565-593
Yoshiki Ninomiya, Bi-Hong Fu. 2003.EXTRACTING LITHOLOGIC INFORMATION FROM ASTER MULTISPECTRAL THERMAL INFRARED DATA IN THE NORTHEASTERN PAMIRS[J].XINJANG GEOLOGY,21(1): 22-30.
Walker R F,Jackeay P T,Longstaff I D. 1997. Recent developments in the use of the co-occurrence matrix for texture recognition. Proc of 13th Internation Conference on Digital Image Processing.Greece.