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国土资源遥感  2012, Vol. 24 Issue (4): 138-145    DOI: 10.6046/gtzyyg.2012.04.23
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
典型地物光谱空间结构特征与基本统计参数分析
王冬寅1,2, 朱谷昌1,3, 张远飞2
1. 中南大学,长沙 410083;
2. 有色金属矿产地质调查中心,北京 100012;
3. 中色地科矿产勘查股份有限公司,北京 100012
Spatial Structure Features and Basic Statistic Parameters of Typical Ground Object Spectral Data
WANG Dong-yin1,2, ZHU Gu-chang1,3, ZHANG Yuan-fei2
1. Central South University, Changsha 410083, China;
2. China Non-ferrous Metals Resource Geological Survey, Beijing 100012, China;
3. Sinotech Minerals Exploration Co., Ltd., Beijing 100012, China
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摘要 分别从光谱曲线及光谱特征空间入手,对内蒙古突泉与青海同仁研究区野外实测岩石、土壤和植被等3类典型地物的光谱数据进行了分析,发现研究区无论在光谱曲线空间,还是在光谱特征空间,同类地物的分布形态基本一致,而不同之处是由不同地区的地质地貌、生态环境与气候因素决定的,但不影响其空间分布形态的整体特征。通过分析与实验,发现了几种能够在光谱特征空间对上述3类特征地物进行较好区分的波段组合,可以利用这几种波段组合指导根据遥感图像生成的二维散点图对这3类地物的分类,有助于改进遥感蚀变信息提取方法。
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胡波
朱谷昌
张远飞
冷超
关键词 高斯混合模型(GMM)期望最大化(EM)算法模拟退火(SA)马尔科夫随机场(MRF)遥感信息提取    
Abstract:From the point of view of spectral curve and spectral feature space and through the analysis of the spectral data of three main ground objects measured in the field, i.e., rocks , soil and vegetation, in the two study areas of Tuquan in Inner Mongolia and Tongren in Qinghai, the authors found that the feature distribution forms are basically the same in the two study areas in both spectral curve space and spectral feature space, although there exist a bit difference caused by the geological environment, ecological environment and climate factors in different areas. Through the analysis and experiment, it is found that several new band combinations can better distinguish the three main ground objects in the spectral feature space and can also guide the classification of the three main ground objects based on the scatter plots of the remote sensing image. This research is helpful to improving the method for extraction of alteration information.
Key wordsGaussian mixture model(GMM)    expectation maximization(EM)algorithm    simulated annealing(SA)    Markov random field(MRF)    remote sensing information extraction
收稿日期: 2012-01-08      出版日期: 2012-11-13
: 

TP 79

 
引用本文:   
王冬寅, 朱谷昌, 张远飞. 典型地物光谱空间结构特征与基本统计参数分析[J]. 国土资源遥感, 2012, 24(4): 138-145.
WANG Dong-yin, ZHU Gu-chang, ZHANG Yuan-fei. Spatial Structure Features and Basic Statistic Parameters of Typical Ground Object Spectral Data. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(4): 138-145.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2012.04.23      或      https://www.gtzyyg.com/CN/Y2012/V24/I4/138
[1] 胡波,朱谷昌,张远飞,等.空间U统计量法在遥感蚀变信息提取中的应用研究[J].国土资源遥感,2011(3):71-76.

Hu B,Zhu G C,Zhang Y F,et al.The Application of Spatial U-static Method to the Extraction of Alteration Anomalies[J].Remote Sensing for Land and Resources,2011(3):71-76(in Chinese with English Abstract).

[2] 张远飞,吴健生.基于遥感图像提取矿化蚀变信息[J].有色金属矿产与勘查,1999,8(6):604-606.

Zhang Y F,Wu J S.Extraction of Mineralization and Alteration Information from Remote Sensing Images[J].Geological Exploration for Non-ferrous Metals,1999,8(6):604-606(in Chinese with English Abstract).

[3] 张宗贵,王润生,郭小方,等.基于地物光谱特征的成像光谱遥感矿物识别方法[J].地学前缘,2003,10(2):437-443.

Zhang Z G,Wang R S,Guo X F,et al.Mineral Recognition Method by Spectrometry Remote Sensing Based on Material Spectral Characteristics[J].Earth Science Frontiers,2003,10(2):437-443(in Chinese with English Abstract).

[4] 吴德文,朱谷昌,张远飞,等.多元数据分析与遥感矿化蚀变信息提取模型[J].国土资源遥感,2006(1):23-25.

Wu D W,Zhu G C,Zhang Y F,et al.The Multivariate Data Analysis and the Model for Extracting Remote Sensing Mineralization and Alteration Information[J].Remote Sensing for Land and Resources,2006(1):23-25(in Chinese with English Abstract).

[5] 张远飞,杨自安,张普斌,等.高(多)光谱数据的背景-异常子空间模型研究[J].地球信息科学学报, 2009,11(3):282-290.

Zhang Y F,Yang Z A,Zhang P B,et al.Research on Background-Anomaly Sub-space Model of Hyper(Multi)spectral Data[J].Geo-Information Science.2009,11(3):282-290(in Chinese with English Abstract).

[6] 张远飞,吴德文,袁继明,等.遥感蚀变信息多层次分离技术模型与应用研究[J].国土资源遥感,2011(4):6-13.

Zhang Y F,Wu D W,Yuan J M,et al.The Model and Application of Multi-level Detaching Technique of Remote Sensing Alteration Information[J].Remote Sensing for Land and Resources,2011(4):6-13(in Chinese with English Abstract).

[7] 高建阳.Hyperion高光谱数据在福建钟腾铜钼矿区的应用研究[J].国土资源遥感,2011(1):87-90.

Gao J Y.The Application of the Hypeion Hyper-spectral Image to the Zhongteng Cu-Mo Deposit in Pinghe County of Fujian Province[J].Remote Sensing for Land and Resources,2011(1):87-90(in Chinese with English Abstract).

[8] 余健,董玉森,张志,等.基于ASTER影像的蚀变异常提取方法研究——以赞比亚谦比希铜矿床地区为例[J].国土资源遥感,2011(3):54-60.

Yu J,Dong Y S,Zhang Z,et al.Research on the Methods for Extraction of Alteration Information by Using ASTER Data:A Case Study of the Chambishi Copper Deposit in Zambia[J].Remote Sensing for Land and Resources,2011(3):54-60(in Chinese with English Abstract).

[9] 李红,朱谷昌,张远飞,等.矿化蚀变区典型地物光谱特征分析与空间结构研究——以内蒙古突泉县-扎鲁特旗成矿带为例[J].国土资源遥感,2010(1):89-95.

Li H,Zhu G C,Zhang Y F,et al.Reflectance Spectral Characteristics and Spatial Structure of Typical Objects in Mineralization and Alteration Areas:A Case Study of the Tuquan-Jarud County Metallogenic Belt in Inner Mongolia[J].Remote Sensing for Land and Resources,2010(1):89-95(in Chinese with English Abstract).

[10] 童庆禧.中国典型地物波谱及其特征分析[M].北京:科学出版社,1990:602-604.

Tong Q X.Typical Object Spectrum Analysis of China[M].Beijing:Science Press,1990:602-604(in Chinese ).

[11] 黄家柱.遥感地学分析[M/CD].[2011-12-29].http://kc.njnu.edu.cn/ygdxfx/page/jiaoan/ch7.htm.

Huang J Z.Geography Remote Sensing Analysis[M/CD].[2011-12-29].http://kc.njnu.edu.cn/ygdxfx/page/jiaoan/ch7.htm(in Chinese).

[12] 刘伟东.高光谱遥感土壤信息提取与挖掘研究[D].北京:中国科学院遥感应用研究所,2002.

Liu W D.Study on Extraction of Soil Information and Data Mining by Hyperspectral Remote Sensing[D].Beijing:Institute of Remote Sensing Applications Chinese Academy of Sciences,2002(in Chinese with English Abstract).

[13] 中国知网.CNKI概念知识元库[DB/OL].[2011-12-29].http://define.cnki.net.

China National Knowledge Infrastructure.CNKI Conceptual Knowledge Library[DB/OL].[2011-12-29].http://define.cnki.net(in Chinese).

[14] 李红.地物光谱特征分析及其在矿化蚀变信息提取中的应用研究[D].长沙:中南大学,2010:31-32.

Li H.Research on Spectral Analysis and Its Application to Mineralization Information Extraction[D].Changsha:Central South University,2010:31-32(in Chinese with English Abstract).

[15] 周清.土壤有机质含量高光谱预测模型及其差异性研究[D].杭州:浙江大学,2004:13-18.

Zhou Q.Study on the Hyperspectral Prediction Models of Soil Organic Matter and Its Differences Among Soil Types[D].Hangzhou:Zhejiang University,2004:13-18(in Chinese with English Abstract).

[16] 何挺,王静,林宗坚,等.土壤有机质光谱特征研究[J].武汉大学学报:信息科学版,2006,31(11):975-979.

He T,Wang J,Lin Z J,et al.Spectral Features of Soil Organic Matter[J].Geomatics and Information Science of Wuhan University,2006,31(11):975-979(in Chinese with English Abstract).

[17] 李智勇,郁文贤,匡纲要,等.基于高维几何特性的高光谱异常检测算法研究[J].遥感技术与应用,2003,18(6):379-383.

Li Z Y,Yu W X,Kuang G Y,et al.The Research of Anomaly Detection Based on High-dimensional Geometrical Feature in Hyperspectral Imagery[J].Remote Sensing Technology and Application,2003,18(6):379-383(in Chinese with English Abstract).
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