光谱学与光谱分析 |
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Simulation of Image Multi-Spectrum Using Field Measured Endmember Spectrum |
ZHANG Ting1,2, DING Jian-li1,2,3*,WANG Fei1,2 |
1. College of Resource and Environmental Science, Xinjiang University, Urumqi 830046, China 2. Lab for Oasis Ecosystem,Ministry of Education, Urumqi 830046, China 3. Key Laboratory of Oasis Ecology and Desert Environment, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China |
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Abstract The characteristic of landscape spectrum is the basic of application of remote sensing and plays an important role in quantitative analysis of remote sensing. However, in spectrum-based application of remote sensing, because the difference of measuring scale and instrument resolution yield serious error in spectral curve and reflectance for the same landscape, there exists difficulty in quantitative retrieval of special information extraction of remote sensing. Firstly, the imaging simulation principles of the optics image was described and proposed A method using field measured endmember spectrum with higher spectrum resolutions to simulate spectrum of Multi-spectrum images with lower spectrum resolution was proposed. In the present paper, the authors take the delta oasis of Weigan and Kuqa rivers ocated in the North of Tarim Basin as study area, and choose vegetation and soil as study object. At first, we accomplished the simulation from field measured endmember for multi-spectrum by using the spectral response function of AVNIR-2, and found the large correlation between simulated multi-spectrum and pixel spectrum of AVNIR-2 by using the statistical analyse. Finally, the authors set up the linear model to accomplish the quantitative transformation from edmember scale to pixel scale. The result of this study has the realistic meaning for the quantitative application of remote sensing.
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Received: 2009-12-08
Accepted: 2010-03-08
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Corresponding Authors:
DING Jian-li
E-mail: watarid@xju.edu.cn
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[1] Li X W, Wang J D, Gao F, et al. In proceedings of The First International Symposium on Recent Advances in Quantitative Remote Sensing. Spain, 2002. [2] WANG Jin-di, LI Xiao-wen, ZHANG Li-xin, et al(王锦地, 李小文, 张立新, 等). Journal of Remote Sensing(遥感学报), 2003, 7(增刊): 13. [3] WAN Hua-wei, WANG Jin-di, et al(万华伟, 王锦地, 等). Journal of Remote Sensing(遥感学报), 2008, 12(4): 538. [4] CHEN Shu-peng, TONG Ting-xi, GUO Hua-dong(陈述彭, 童庆禧, 郭华东). The Study of Remote Sensing Information(遥感信息机理研究). Beijing: Science Press(北京: 科学出版社), 1998. [5] MEI An-xin, PENG Wang-lu, QIN Qi-ming, et al(梅安新, 彭望琭, 秦其明, 等). Introductory to Remote Sensing(遥感导论). Beijing: Higher Education Press(北京: 高等教育出版社), 2001. [6] YE Ze-tian, GU Xing-fa(叶泽田, 顾行发). Acta Geodaetica of Cartographica Sinca(测绘学报), 2000, 29(3): 235. [7] Shunlin Liang. Remote Sensing of Environment, 2000, 76: 213. [8] Verhoef W, Bach H. Remote Sensing of Environment, 2003, 87: 23. [9] CHEN Fang, NIU Zheng, FU An-min(陈 方, 牛 铮, 付安民). Acta Scientiarum Naturalium Universitatis Pekinensis(北京大学学报·自然科学版), 2006, 42(4): 478. [10] GU You-lin, ZHANG Dong-ying, et al(顾有林, 张冬英, 等). Journal of System Simulation(系统仿真学报), 2008, 20(14): 3730. [11] CHEN Fang, NIU Zheng, et al(陈 方, 牛 铮, 等). Opto-Electronic Engineering(光电工程), 2007, 34(5): 89. [12] QIAO Yan-li, ZHENG Xiao-bing, et al(乔延利, 郑小兵, 等). Journal of Remote Sensing(遥感学报), 2006, 10(5): 616. [13] Liu L Y, Wang J H, Huang W J, et al. International Journal of Remote Sensing, 2004, 25(17): 3331.
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