基于光谱特征参数组合的高光谱数据矿物填图方法

韦晶; 明艳芳; 刘福江

doi:10.3799/dqkx.2015.130

Volume 40 Issue 8

Aug. 2015

Turn off MathJax

Article Contents

Article Navigation > Earth Science > 2015 > 40(8): 1432-1440

Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130

Citation:

Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130

Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130

Citation:

Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130

PDF( 9261 KB)

Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination

doi: 10.3799/dqkx.2015.130

1.
College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2.
Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China

Received Date: 2015-04-02
Publish Date: 2015-08-01

Abstract

Abstract

Influenced by the atmospheric environment and other factors, the mineral recognition with hyperspectral remote sensing is difficult to achieve a high accuracy. To improve the accuracy of the mineral identification with such technology, a hyperspectral mineral recognition method based on spectral characteristic parameter combination, which can maintain relatively stable characteristics with the atmospheric changes, is proposed in this paper. Various spectral characteristic parameters are calculated, and the optimal combination of the parameters is selected through the optimum index factor (OIF), based on which, mineral identification is realized with pattern recognition method. Based on the above method, mineral type identification test is carried out in Cuprite mine of Nevada, with airborne visible infrared imaging spectrometer (AVIRIS) hyperspectral data. The results are compared with the work of previous mineral mapping, it shows that the combination of the spectral characteristic parameters, P-A-S₂ (P is absorption wave trough position, A is absorption area, S₂ is absorption right shoulder position) can get the highest identification precision, the overall accuracy can reach 74.68%.
- spectral characteristic parameter,
- remote sensing,
- mineral mapping,
- airborne visible infrared imaging spectrometer data,
- optimum index factor (OIF),
- Cuprite mining area

FullText(HTML)

References(44)

References

Baugh, W.M., Kruse, F.A., Atkinson, W.W., 1998. Quantitative Geochemical Mapping of Ammonium Minerals in the Southern Cedar Mountains, Nevada, Using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 65(3): 292-308. doi: 10.1016/s0034-4257(98)00039-x

Chavez, P.S., Berlin, G.L., Sowers, L.B., 1982. Statistical Method for Selecting Landsat MSS Ratios. Journal of Applied Photographic Engineering, 8(1): 23-30. http://ci.nii.ac.jp/naid/80001173869

Chen, X.F., Warner, T.A., Campagna, D.J., 2007. Integrating Visible, Near-Infrared and Short-Wave Infrared Hyperspectral and Multispectral Thermal Imagery for Geological Mapping at Cuprite, Nevada. Remote Sensing of Environment, 110(3): 344-356. doi: 10.1016/j.rse.2007.03.015

Clark, R.N., King, T.V.V., Klejwa, M., et al., 1990. High Spectral Resolution Reflectance Spectroscopy of Minerals. Journal of Geophysical Research, 95(B8): 12653-12680. doi: 10.1029/jb095ib08p12653

Clark, R.N., Swayze, G.A., 1995. Mapping Mineral, Amorphous Materials, Environmental Materials, Vegetation, Water, Ice and Snow, and Other Materials: The USGS Tricorder Algorithm. Summaries of the Fifth Annual JPL Airborne Earth Science Workshop, JPL Publication, 39-40.

Clark, R.N., Swayze, G.A., 1996. Evolution in Imaging Spectroscopy Analysis and Sensor Signal-to-Noise: An examination of How Far We Have Come. Summaries of the 6th Annual JPL Airborne Geosciences Workshop, JPL Publication, 96(4): 49-53. http://speclab.cr.usgs.gov/PAPERS.imspec.evol/aviris.evolution.html

Clark, R.N., Swayze, G.A., Livo, K.E., et al., 2003. Imaging Spectroscopy: Earth and Planetary Remote Sensing with the USGS Tetracorder and Expert Systems. Journal of Geophysical Research, 108(E12): 5131-5135. doi: 10.1029/2002je001847

Crowley, J.K., Brickey, D.W., Rowan, L.C., 1989. Airborne Imaging Spectrometer Data of the Ruby Mountains, Montana: Mineral Discrimination Using Relative Absorption Band-Depth Images. Remote Sensing of Environment, 29(2): 121-134. doi: 10.1016/0034-4257(89)90021-7

Friedl, M.A., McIver, D.K., Hodges, J.C.F., et al., 2002. Global Land Cover Mapping from MODIS: Algorithms and Early Results. Remote Sensing of Environment, 83(1-2): 287-302. doi: 10.1016/s0034-4257(02)00078-0

Felde, G.W., Anderson, G.P., Cooley, T.W., et al., 2003. Analysis of Hyperion Data with the FLAASH Atmospheric Correction Algorithm. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), (1): 90-92. doi: 10.1109/IGARSS.2003.1293688

Gan, F.P., Liu, S.W., Zhou, Q., 2004. Identification of Mining Pollution Using Hyperion Data at Dexing Copper Mine in Jiangxi Province, China. Earth Science—Journal of China University of Geosciences, 29(1): 119-126 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-DQKX200401020.htm

Gan, F.P., Wang, R.S., 2007. The Application of the Hyperspectral Imaging Technique to Geological Investigation. Remote Sensing for Land & Resources, 19(4): 57-60, 127-128 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GTYG200704014.htm

Gan, F.P., Wang, R.S., Ma, A.N., 2003. Spectral Identification Tree (SIT) for Mineral Extraction Based on Spectral Characteristics of Minerals. Earth Science Frontiers, 10(2): 445-454 (in Chinese with English abstract).

He, Z.H., He, B.B., 2011. Weight Spectral Angle Mapper (WSAM) Method for Hyperspectral Mineral Mapping. Spectroscopy and Spectral Analysis, 31(8): 2200-2204 (in Chinese with English abstract). http://www.cqvip.com/QK/90993X/201108/38715065.html

Hook, S.J., Gabell, A.R., Green, A.A., et al., 1992. A Comparison of Techniques for Extracting Emissivity Information from Thermal Infrared Data for Geologic Studies. Remote Sensing of Environment, 42(2): 123-135. doi: 10.1016/0034-4257(92)90096-3

Huang, X.M., Hsu, P.H., 2012. Comparisom of Wavelet-Based and HHT-Based Feature Extraction Methods for Hyperspectral Image Classification. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B7: 121-126. doi: 10.5194/isprsarchives-XXXIX-B7-121-2012

Huang, Z., Turner, B.J., Dury, S.J., et al., 2004. Estimating Foliage Nitrogen Concentration from HYMAP Data Using Continuum Removal Analysis. Remote Sensing of Environment, 93(1-2): 18-29. doi: 10.1016/j.rse.2004.06.008

Iordache, M.D., Bioucas-Dias, J.M., Plaza, A., 2014. Collaborative Sparse Regression for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 52(1): 341-354. doi: 10.1109/TGRS.2013.2240001

Kruse, F.A., Raines, G.L., Watson, K., 1985. Analytical Techniques for Extracting Geologic Information from Multichannel Airborne Spectroradiometer Airborne Imaging Spectrometer Data. Proceedings, International Symposium on Remote Sensing of Environment, Thematic Conference on Remote Sensing for Exploration Geology, 4th, Environmental Research Institute of Michigan, Ann Arbor.

Ma, N., Hu, Y.F., Zhuang, D.F., et al., 2010. Determination on the Optimum Band Combination of HJ-1A Hyperspectral Data in the Case Region of Dongguan Based on Optimum Index Factor and J-M Distance. Remote Sensing Technology and Application, 25(3): 358-365 (in Chinese with English abstract). http://www.oalib.com/paper/1468704

Robila, S.A., 2005. Using Spectral Distances for Speedup in Hyperspectral Image Processing. International Journal of Remote Sensing, 26(24): 5629-5650. doi: 10.1080/01431160500168728

Su, H.J., Du, P.J., 2006. Study on Feature Selection and Extraction of Hyperspectral Data. Remote Sensing Technology and Application, 21(4): 288-293 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-YGJS200604003.htm

Swayze, G.A., 1997. The Hydrothermal and Structural History of the Cuprite Mining District, Southwestern Nevada: An Integrated Geological and Geophysical Approach(Dissertation). University of Colorado at Boulder, USA.

van der Meer, F., Bakker, W., 1997. CCSM: Cross Correlogram Spectral Matching. International Journal of Remote Sensing, 18(5): 1197-1201. doi: 10.1080/014311697218674

van der Meer, F., 2000. Spectral Curve Shape Matching with a Continuum Removed CCSM Algorithm. International Journal of Remote Sensing, 21(16): 3179-3185. doi: 10.1080/01431160050145063

van der Meer, F., 2006. The Effectiveness of Spectral Similarity Measures for the Analysis of Hyperspectral Imagery. International Journal of Applied Earth Observation and Geoinformation, 8(1): 3-17. doi: 10.1016/j.jag.2005.06.001

Wang, R.S., Gan, F.P., Yan, B.K., et al., 2010. Hyperspectral Mineral Mapping and Its Application. Remote Sensing for Land & Resources, (1): 1-13 (in Chinese with English abstract). http://www.gtzyyg.com/CN/article/downloadArticleFile.do?attachType=PDF&id=434

Wang, R.S., Yang, S.M., Yan, B.K., 2007. A Review of Mineral Spectral Identification Methods and Models with Imaging Spectrometer. Remote Sensing for Land & Resources, (1): 1-9 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GTYG200701000.htm

Wu, C.S., Murray, A.T., 2003. Estimating Impervious Surface Distribution by Spectral Mixture Analysis. Remote Sensing of Environment, 84(4): 493-505. doi: 10.1016/s0034-4257(02)00136-0

Wu, W., Shao, G.F., 2002. Optimal Combinations of Data, Classifiers, and Sampling Methods for Accurate Characterizations of Deforestation. Canadian Journal of Remote Sensing, 28(4): 601-609. doi: 10.5589/m02-050

Xu, N., Hu, Y.X., Lei, B., et al., 2011. Mineral Information Extraction for Hyperspectral Image Based on Modified Spectral Feature Fitting Algorithm. Spectroscopy and Spectral Analysis, 31(6): 1639-1643 (in Chinese with English abstract). http://www.ncbi.nlm.nih.gov/pubmed/21847949

Yu, X.C., Xiong, L.P., Xu, J.D., et al., 2014. Mineral Mapping Based on Secondary Scattering Mixture Model. Remote Sensing for Land & Resources, 26(2): 60-68 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GTYG201402011.htm

Zhang, X.B., Yuan, Y., Jing, J.J., et al., 2011. Spectral Discrimination Method Information Divergence Combined with Gradient Angle. Spectroscopy and Spectral Analysis, 31(3): 853-857 (in Chinese with English abstract). http://europepmc.org/abstract/MED/21595255

甘甫平, 刘圣伟, 周强, 2004. 德兴铜矿矿山污染高光谱遥感直接识别研究. 地球科学——中国地质大学学报, 29(1): 119-126. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200401020.htm

甘甫平, 王润生, 2007. 高光谱遥感技术在地质领域中的应用. 国土资源遥感, 19(4): 57-60, 127-128. doi: 10.3969/j.issn.1001-070X.2007.04.013

甘甫平, 王润生, 马蔼乃, 2003. 基于特征谱带的高光谱遥感矿物谱系识别. 地学前缘, 10(2): 445-454. doi: 10.3321/j.issn:1005-2321.2003.02.024

何中海, 何彬彬, 2011. 基于权重光谱角制图的高光谱矿物填图方法. 光谱学与光谱分析, 31(8): 2200-2204. doi: 10.3964/j.issn.1000-0593(2011)08-2200-05

马娜, 胡云峰, 庄大方, 等, 2010. 基于最佳波段指数和J-M距离可分性的高光谱数据最佳波段组合选取研究. 遥感技术与应用, 25(3): 358-365. https://www.cnki.com.cn/Article/CJFDTOTAL-YGJS201003010.htm

苏红军, 杜培军, 2006. 高光谱数据特征选择与特征提取研究. 遥感技术与应用, 21(4): 288-293. doi: 10.3969/j.issn.1004-0323.2006.04.004

王润生, 杨苏明, 阎柏琨, 2007. 成像光谱矿物识别方法与识别模型评述. 国土资源与遥感, (1): 1-9. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG200701000.htm

王润生, 甘甫平, 闫柏琨, 等, 2010. 高光谱矿物填图技术与应用研究. 国土资源遥感, (1): 1-13. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201001002.htm

许宁, 胡玉新, 雷斌, 等, 2011. 基于改进光谱特征拟合算法的高光谱数据矿物信息提取. 光谱学与光谱分析, 31(6): 1639-1643. doi: 10.3964/j.issn.1000-0593(2011)06-1639-05

余先川, 熊利平, 徐金东, 等, 2014. 基于二次散射非线性混合模型的矿物填图方法. 国土资源遥感, 26(2): 60-68. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201402011.htm

张修宝, 袁艳, 景娟娟, 等, 2011. 信息散度与梯度角正切相结合的光谱区分方法. 光谱学与光谱分析, 31(3): 853-857. doi: 10.3964/j.issn.1000-0593(2011)03-0853-05

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(5) / Tables(2)

Get Citation

PDF

XML

Article views (3636) PDF downloads(300)

Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination

doi: 10.3799/dqkx.2015.130

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Proportional views

Export File

Citation

Format

Content