Mineral Spectrum Change Analysis under the Conditions of Different Particle Size
WANG Yan-xia1,2, WU Jian2, ZHOU Liang-guang2,HOU Lan-gong2, WANGDong2, CAO Min3,4*
1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China 2. Geography Information and Tourism College, Chuzhou University, Chuzhou 239000, China 3. School of Geography Science, Nanjing Normal University, Nanjing 210023, China 4. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development, Nanjing 210023, China
Abstract：Mineral particle size is an important factor affecting mineral spectrum characteristics, so to explore the changes of the mineral spectrum curves under different particle sizes and the spectrum difference of different minerals under the same particle size are the keys of hyperspectral remote sensing information mineralidentification and the theoretical basis of research on spectral differences ofdifferent particle sizes. Six kinds of collected minerals were observed by spectrometer to get the reflectivity spectrum curve and first order differential spectral curve under different particle sizes, and the spectral characteristics of various kinds of minerals under different particle sizes were analyzed. At the same time, spectrum difference of different mineral under the same particle size was compared to explore possible wavelengths of hyperspectral remote sensing mineral identify. Results show that the spectrum curves of various minerals have a larger difference with the change of the particle size, but change law is not the same. The whole spectrum curve of hypersthene will be decreased with the increase of particle size, and the spectrum curve at a specific wavelength range of antigorite, hematite, kaolinite and chlorite will be decreased with the increase of particle size, and there is no direct correlation between the spectrum of olivine and the particle size. Under the same size, different mineral spectral reflectance change a lot in most band range and it provides the possibility for highprecision identification of mineral. Antigorite, kaolinite and chlorite all have more absorption peaks of narrow width and smaller intensity than the other minerals. Spectrum curves of hematite, olivine and hypersthene are relatively smooth, and the number of the absorption and reflection peaks is relatively small. This study aims at providing basic data and theoretical support for mineral spectral library construction and mineral hyperspectral identification technology.
Key words：Spectral analysis;Mineral;Particle size;First order differential
王延霞1,2，吴 见2，周亮广2，侯兰功2，王 岽2，曹 敏3,4* . 不同粒度条件下矿物光谱变化分析 [J]. 光谱学与光谱分析, 2015, 35(03): 803-808.
WANG Yan-xia1,2, WU Jian2, ZHOU Liang-guang2,HOU Lan-gong2, WANGDong2, CAO Min3,4* . Mineral Spectrum Change Analysis under the Conditions of Different Particle Size. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(03): 803-808.
[1] Ariana D P, Lu R F. Computers and Electronics in Agriculture, 2010, 74(1): 137. [2] Rajkumar P, Wang N, Elmasry G, et al. Journal of Food Engineering, 2012, 108(1): 194. [3] Zhang R, Ying Y, Rao X, et al. Journal of the Science of Food and Agriculture, 2012, 92(12): 2397. [4] Li Guiying，Lu Dengsheng，Emilio M，et al. Int. J. Remote Sens.，2011，32(23)：8207. [5] Wang W, Li C, Tollner E W, et al. Journal of Food Engineering, 2012, 109(1): 38. [6] Zhang X L, Liu F, He Y, et al. Sensors, 2012, 12(12): 17234. [7] Kuang B, Mouazen A M. European Journal of Soil Science, 2012, 63(3): 421. [8] Yucel Tekin, Zeynal Tumsavas, Abdul Mounem Mouazen.Soil Science Society of America, 2012, 76(1): 188. [9] Huang M, Wan X M, Zhang M, et al. Journal of Food Engineering, 2013, 116(1): 45. [10] WAN Yu-qing, ZHANG Feng-li, YAN Yong-zhong(万余庆，张凤丽，闫永忠). Geo-information Science(地球信息科学), 2001，(3): 54. [11] Gong A P, Qiu Z J, He Y, et al. Spectrochimica Acta Part A-Molecular and Biomolecular Spectroscopy, 2012, 99: 7. [12] Jiang H, Zhu W X. Food Analytical Methods, 2013, 6(2): 569. [13] Marco Nocita, Antoine Stevens, Carole Noon, et al. Geoderma, 2013，(199): 37. [14] Ramirez-Lopez L, Behrens T, Schmidt K, et al. Geoderma, 2013，(199):43. [15] Summers D, Lewis M, Ostendorf B, et al. Ecological Indicators, 2011, 11(1): 123.
