江西定南北部地区稀土矿矿山开发状况与环境效应遥感研究
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摘要
矿产资源是不可再生资源,其有效的开发利用对于我国工业化、城市化、现代化进程都具有特殊的重要作用。遥感技术以其快速、同步、多时相等特点成为矿山开采调查过程中的一种有力手段。本研究以国土资源部和赣州市政府联合委托中国地质大学(北京)开展的“江西赣南地区矿产资源开发状况遥感监测研究”项目为依托,利用先进的遥感技术对研究区稀土矿矿山开发状况进行了探索性调查研究。为进一步大范围采用遥感技术进行矿产资源开发状况调查研究提供了依据,对有关政府部门维护正常的矿产资源管理秩序以及矿区环境的综合整治具有十分重要的意义。
本研究以江西赣州定南北部地区为研究区,以QuickBird、SPOT、ETM+和TM卫星影像数据为主要信息源,结合相关资料,对研究区矿山开发现状和动态变化情况进行了调查分析。
经过各种图像预处理和增强处理,包括正射校正及其误差评价、数据融合及其评价和最佳波段组合等其他图像增强的方法,提高目标地物在遥感图像上的表现,有利于目标地物的判读和分析。
采用2005年的QuickBird融合影像,通过人机交互目视解译的方式提取现状信息,提取的现状信息主要有:三种稀土矿开采方式(池浸法、原地堆浸法、原地浸矿法)所包括的各地物面积。利用GIS软件统计研究区内总的矿区面积、合法开采和非法开采的各目标地物的面积,根据各统计数据对研究区稀土矿开发现状进行了综合分析,并提出可持续发展建议。
采用1991年的TM数据、1999年的ETM~+数据和2005年的SPOT数据,通过计算机自动信息提取技术,本研究采用最大似然监督分类法对三期遥感数据进行分类,对分类数据进行精度评价,结果满足研究所需。使用分类数据对研究区稀土矿14年间的开发状况变化情况进行调查分析。
Mineral resource is non-renewable resource .Its effective development and use have the special function to the industrialization, the urbanization and the modernized advancement of our country. The remote sensing technology combining with its fast, synchronization, multi-temporal characteristics becomes one of the powerful method in mine investigation process .this research was supported by the project -- "The remote sensing monitor research of mineral resource development condition of Jiangxi Gannan area ", which was taken by China University of Geosciences (Beijing) and entrusted by National Territory ResourcesDepartment and Ganzhou Municipal Government .The research uses the remote sensing technology for conducting the mineral resource development condition investigation. The research also provides vital significance to the related government department which maintains the normal mineral resource management order as well as the mining area environment synthesis renovates.
The research aims the north area of Dingnan county as its research area, and adopts QuickBird, SPOT, ETM+ and the TM satellite image data as the main information sources, It give a diagnosis about the research area in mine development of the present situation and the dynamic change situation basing on the satellite image data as well as other relation data.
This research uses kinds of image pretreatment and enhancement processing to remote sensing image including ortho-rectify and its erroneous appraisal, data fusion and its appraisal, best bands combination and other Image enhancement methods. The research take advantage of QuickBird fusion image of 2005 for the present situation analysis by the way of man-machine interactional visual interpretation. The features of three rare-earth mineral exploitation ways was concluded in the present situation information . Then we analyzed the present developing situation of the rare-earth mineral in study area.
TM data of 1991, ETM+ data of 1999 and SPOT data of 2005 were applied to analyse dynamic change situation of the research area through computer automatic information extraction technology in this research. The research uses the maximum likelihood method for the classification to three periods of remote sensing data. Theresearch carries on the precision assessment to the class results, and finally satisfies the need of research. And then the research uses the class results to analyse the dynamic change within 14 years of the study area.
本研究以江西赣州定南北部地区为研究区,以QuickBird、SPOT、ETM+和TM卫星影像数据为主要信息源,结合相关资料,对研究区矿山开发现状和动态变化情况进行了调查分析。
经过各种图像预处理和增强处理,包括正射校正及其误差评价、数据融合及其评价和最佳波段组合等其他图像增强的方法,提高目标地物在遥感图像上的表现,有利于目标地物的判读和分析。
采用2005年的QuickBird融合影像,通过人机交互目视解译的方式提取现状信息,提取的现状信息主要有:三种稀土矿开采方式(池浸法、原地堆浸法、原地浸矿法)所包括的各地物面积。利用GIS软件统计研究区内总的矿区面积、合法开采和非法开采的各目标地物的面积,根据各统计数据对研究区稀土矿开发现状进行了综合分析,并提出可持续发展建议。
采用1991年的TM数据、1999年的ETM~+数据和2005年的SPOT数据,通过计算机自动信息提取技术,本研究采用最大似然监督分类法对三期遥感数据进行分类,对分类数据进行精度评价,结果满足研究所需。使用分类数据对研究区稀土矿14年间的开发状况变化情况进行调查分析。
Mineral resource is non-renewable resource .Its effective development and use have the special function to the industrialization, the urbanization and the modernized advancement of our country. The remote sensing technology combining with its fast, synchronization, multi-temporal characteristics becomes one of the powerful method in mine investigation process .this research was supported by the project -- "The remote sensing monitor research of mineral resource development condition of Jiangxi Gannan area ", which was taken by China University of Geosciences (Beijing) and entrusted by National Territory ResourcesDepartment and Ganzhou Municipal Government .The research uses the remote sensing technology for conducting the mineral resource development condition investigation. The research also provides vital significance to the related government department which maintains the normal mineral resource management order as well as the mining area environment synthesis renovates.
The research aims the north area of Dingnan county as its research area, and adopts QuickBird, SPOT, ETM+ and the TM satellite image data as the main information sources, It give a diagnosis about the research area in mine development of the present situation and the dynamic change situation basing on the satellite image data as well as other relation data.
This research uses kinds of image pretreatment and enhancement processing to remote sensing image including ortho-rectify and its erroneous appraisal, data fusion and its appraisal, best bands combination and other Image enhancement methods. The research take advantage of QuickBird fusion image of 2005 for the present situation analysis by the way of man-machine interactional visual interpretation. The features of three rare-earth mineral exploitation ways was concluded in the present situation information . Then we analyzed the present developing situation of the rare-earth mineral in study area.
TM data of 1991, ETM+ data of 1999 and SPOT data of 2005 were applied to analyse dynamic change situation of the research area through computer automatic information extraction technology in this research. The research uses the maximum likelihood method for the classification to three periods of remote sensing data. Theresearch carries on the precision assessment to the class results, and finally satisfies the need of research. And then the research uses the class results to analyse the dynamic change within 14 years of the study area.
引文
[1] 陈述彭,童庆禧,郭华东.遥感信息机理研究.北京:科学出版社,1998,84～113
[2] 赵祥,刘素红,王安建等.基于卫星遥感数据的江西德兴铜矿开采环境影响动态监测分析.中国环境监测,2005,21(2):68～73
[3] 李雨法.江西稀土产业发展思路探析. 江西有色金属,2004,18(1):5～7
[4] 侯宗林. 我国稀土资源利用现状及存在的问题. 稀土信息,2005,4:6～7
[5] Chevral St. Assessing and monitoring the environmental impact of mining activities in Europe using most advanced Earth Observation Techniques. 2000
[6] 伍东森.江西有色地勘局稀土矿产勘查回顾. 矿产与地质,2001,15(S1):526～530
[7] 刘毅. 稀土开采工艺改进后的水土流失现状和水土保持对策.水利发展研究,2002,2(2):30～32
[8] 汤洵忠,李茂楠.离子吸附型稀土矿原地浸析采矿法.矿业研究与开发,1997,17(2):1～4
[9] 刘权衡.建议改革“采矿许可证”制度. 西部资源,2005,7:16
[10] 张增祥.我国资源环境遥感监测技术及其进展.中国水利,2004,11:52～55
[11] Friedl M. A., Brodley C. E. & Strahler H,1999,Maximizing land cover classification accuracies produced by decision trees at continental to global scales,IEEE Trans.Geosci. Remote Sens,37(2):969～977
[12] 姜庆娟,谭景信.象素级融合方法与选择.计算机工程与应用,2003,25:116～120
[13] Mausel P W and Kramber J W .Optimum band selection for supervised classification of multispectral data. Photogrammetric Engineering & Remote Sensing,1990,56::55～60.
[14] Tax T, Sxhistad A H and Solberg. Information Fusion in Remote Sensing.Vista in Astronomy,1997,41(3):337～342
[15] Ronald R and Yager. A framework for multi-source data fusion. Information Sciences,2004,163:175～200
[16] Lee J. B,Woodyatt S,and Berman M,1990,Enhancement of high spectral resolution remote-sensing data by a noise-adjust principal components transform, IEEE Trans. Geosci. Remote Sens.28(3):295～304
[17] 贾永红,李德仁.多源遥感影像像素级融合分类与决策级分类融合法的研究.武汉大学 报(信息科学版),2001,26 (5) :430～433
[18] Rabel J V.Multispectral Imagery Advanced Band Sharpening Study. Photogrammetrie Engineering and Remote Sensing, 2000, 66(1):73～79
[19] 韩玲,吴汉宁,杜子涛. 多源遥感影像数据融合方法在地学中的应用. 地球科学与环境学报,2005,27(3):78～81
[20] 李弼程,魏俊,彭天强.遥感影象融合效果的客观分析与评价[J].计算机工程与科学,2004(1):42～46.
[21] 王海晖,彭嘉雄,吴巍,等.多源遥感图像融合效果评价方法研究[J].计算机工程与应用,2003(25):33～37
[22] 东野长磊,王志强. QuickBird卫星影像处理技术实践. 微计算机信息,2005,20:109～110
[23] 刘云峰,李若.不同 DEM 数据对卫星遥感影像纠正精度的影响[J].测绘通报,2002,7:26～28
[24] 丰茂森.遥感数字图像处理.北京:地质出版社,2001
[25] Agustin Ifarraguerri and Michael W Prairie. Visual Method for Spectral Band Selection. IEEE Geoscience and Remote Sensing Letters,2004,1(2):101
[26] Dai Changda and Lei Liping. The information characteristics of thematic mapper data and the optional band combination. Remote Sensing of Environment China.1989,4( 4):282～292
[27] 张志敏,张天桥,康冬舟等.遥感图像多光谱假彩色合成处理及其在环境地学中的应用.影像技术,2002(1):33～36
[26] 胡著智,王慧麟,陈钦峦编著.遥感技术与地学应用.南京:南京大学出版社,1999
[27] 肖洪.基于高分辨率卫星影像的县级土地利用调查研究:[硕士论文]长沙:湖南师范大学.2004
[28] Congalton P G. Mapping and monitoring agricultural crops and other land cover in the lower Colorado River Rasin.1998,64(11):1107～1113
[29] 孙静,赵伟,赵鲁全.土地利用遥感动态监测技术方法介绍.山东国土资源遥感,2005,21(4):38～41
[30] 赵英时等编著.遥感应用分析原理与方法.北京:科学出版社,2003
[31] Johann K. Land use dynamics and landscape change patern in a typical watershed in the hillside region of central Honduras. Agriculture Ecosystem and Environment,1999,75:93～100
[32] 梅安新等.遥感导论.北京:高等教育出版社,2001
[33] Jensen J.R.,2004,Introductory Digital Image Processing-A Remote Sensing Perspective,Second Ed.Upper Saddle River,NJ:Prentice Hall,316
[34] Wang F and Fuzzy. supervised classification of remote sensing image .IEEE Transaction on Geoscience and Remote sensing,,1990,28(2):194～201
[35] Congalton R G. A review of assessing the accuracy of classifications of remotely sensed data Remote Sensing of Environment. 1991,37:35～46
[2] 赵祥,刘素红,王安建等.基于卫星遥感数据的江西德兴铜矿开采环境影响动态监测分析.中国环境监测,2005,21(2):68～73
[3] 李雨法.江西稀土产业发展思路探析. 江西有色金属,2004,18(1):5～7
[4] 侯宗林. 我国稀土资源利用现状及存在的问题. 稀土信息,2005,4:6～7
[5] Chevral St. Assessing and monitoring the environmental impact of mining activities in Europe using most advanced Earth Observation Techniques. 2000
[6] 伍东森.江西有色地勘局稀土矿产勘查回顾. 矿产与地质,2001,15(S1):526～530
[7] 刘毅. 稀土开采工艺改进后的水土流失现状和水土保持对策.水利发展研究,2002,2(2):30～32
[8] 汤洵忠,李茂楠.离子吸附型稀土矿原地浸析采矿法.矿业研究与开发,1997,17(2):1～4
[9] 刘权衡.建议改革“采矿许可证”制度. 西部资源,2005,7:16
[10] 张增祥.我国资源环境遥感监测技术及其进展.中国水利,2004,11:52～55
[11] Friedl M. A., Brodley C. E. & Strahler H,1999,Maximizing land cover classification accuracies produced by decision trees at continental to global scales,IEEE Trans.Geosci. Remote Sens,37(2):969～977
[12] 姜庆娟,谭景信.象素级融合方法与选择.计算机工程与应用,2003,25:116～120
[13] Mausel P W and Kramber J W .Optimum band selection for supervised classification of multispectral data. Photogrammetric Engineering & Remote Sensing,1990,56::55～60.
[14] Tax T, Sxhistad A H and Solberg. Information Fusion in Remote Sensing.Vista in Astronomy,1997,41(3):337～342
[15] Ronald R and Yager. A framework for multi-source data fusion. Information Sciences,2004,163:175～200
[16] Lee J. B,Woodyatt S,and Berman M,1990,Enhancement of high spectral resolution remote-sensing data by a noise-adjust principal components transform, IEEE Trans. Geosci. Remote Sens.28(3):295～304
[17] 贾永红,李德仁.多源遥感影像像素级融合分类与决策级分类融合法的研究.武汉大学 报(信息科学版),2001,26 (5) :430～433
[18] Rabel J V.Multispectral Imagery Advanced Band Sharpening Study. Photogrammetrie Engineering and Remote Sensing, 2000, 66(1):73～79
[19] 韩玲,吴汉宁,杜子涛. 多源遥感影像数据融合方法在地学中的应用. 地球科学与环境学报,2005,27(3):78～81
[20] 李弼程,魏俊,彭天强.遥感影象融合效果的客观分析与评价[J].计算机工程与科学,2004(1):42～46.
[21] 王海晖,彭嘉雄,吴巍,等.多源遥感图像融合效果评价方法研究[J].计算机工程与应用,2003(25):33～37
[22] 东野长磊,王志强. QuickBird卫星影像处理技术实践. 微计算机信息,2005,20:109～110
[23] 刘云峰,李若.不同 DEM 数据对卫星遥感影像纠正精度的影响[J].测绘通报,2002,7:26～28
[24] 丰茂森.遥感数字图像处理.北京:地质出版社,2001
[25] Agustin Ifarraguerri and Michael W Prairie. Visual Method for Spectral Band Selection. IEEE Geoscience and Remote Sensing Letters,2004,1(2):101
[26] Dai Changda and Lei Liping. The information characteristics of thematic mapper data and the optional band combination. Remote Sensing of Environment China.1989,4( 4):282～292
[27] 张志敏,张天桥,康冬舟等.遥感图像多光谱假彩色合成处理及其在环境地学中的应用.影像技术,2002(1):33～36
[26] 胡著智,王慧麟,陈钦峦编著.遥感技术与地学应用.南京:南京大学出版社,1999
[27] 肖洪.基于高分辨率卫星影像的县级土地利用调查研究:[硕士论文]长沙:湖南师范大学.2004
[28] Congalton P G. Mapping and monitoring agricultural crops and other land cover in the lower Colorado River Rasin.1998,64(11):1107～1113
[29] 孙静,赵伟,赵鲁全.土地利用遥感动态监测技术方法介绍.山东国土资源遥感,2005,21(4):38～41
[30] 赵英时等编著.遥感应用分析原理与方法.北京:科学出版社,2003
[31] Johann K. Land use dynamics and landscape change patern in a typical watershed in the hillside region of central Honduras. Agriculture Ecosystem and Environment,1999,75:93～100
[32] 梅安新等.遥感导论.北京:高等教育出版社,2001
[33] Jensen J.R.,2004,Introductory Digital Image Processing-A Remote Sensing Perspective,Second Ed.Upper Saddle River,NJ:Prentice Hall,316
[34] Wang F and Fuzzy. supervised classification of remote sensing image .IEEE Transaction on Geoscience and Remote sensing,,1990,28(2):194～201
[35] Congalton R G. A review of assessing the accuracy of classifications of remotely sensed data Remote Sensing of Environment. 1991,37:35～46