| 光谱学与光谱分析 |
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| Comparative Study on Hyperspectral Inversion Accuracy of Soil Salt Content and Electrical Conductivity |
| PENG Jie1, WANG Jia-qiang1, XIANG Hong-ying1, TENG Hong-fen2, LIU Wei-yang1, CHI Chun-ming1, NIU Jian-long1, GUO Yan2, SHI Zhou2* |
| 1. College of Plant Science, Tarim University, Alar 843300, China2. Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China |
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Abstract The objective of the present article is to ascertain the mechanism of hyperspectral remote sensing monitoring for soil salinization, which is of great importance for improving the accuracy of hyperspectral remote sensing monitoring. Paddy soils in Wensu，Hetian and Baicheng counties of the southern Xinjiang were selected. Hyperspectral data of soils were obtained. Soil salt content (St) an electrical conductivity of 1∶5 soil-to-water extracts (EC1∶5) were determined. Relationships between St and EC1∶5 were studied. Correlations between hyperspectral indices and St, and EC1∶5 were analyzed. The inversion accuracy of St using hyperspectral technique was compared with that of EC1∶5. Results showed that: significant (p<0.01) relationships were found between St and EC1∶5 for soils in Wensu and Hetian counties, and correlation coefficients were 0.86 and 0.45, respectively; there was no significant relationship between St and EC1∶5 for soils in Baicheng county. Therefore, the correlations between St and EC1∶5 varied with studied sites. St and EC1∶5 were significantly related with spectral reflectance, first derivative reflectance and continuum-removed reflectance, respectively; but correlation coefficients between St and spectral indices were higher than those between EC1∶5 and spectral indices, which was obvious in some sensitive bands for soil salinization such as 660, 35, 1 229, 1 414, 1 721, 1 738, 1 772, 2 309 nm, and so on. Prediction equations of St and EC1∶5 were established using multivariate linear regression, principal component regression and partial least-squares regression methods, respectively. Coefficients of determination, determination coefficients of prediction, and relative analytical errors of these equations were analyzed. Coefficients of determination and relative analytical errors of equations between St and spectral indices were higher than those of equations between EC1∶5 and spectral indices. Therefore, the responses of high spectral information to St were more sensitive than those of high spectral information to EC1∶5. Accuracy of St predicted from high spectral data was higher than that of EC1∶5 estimated from high spectral data. The results of this study can provide a theoretical basis to improve hyperspectral remote sensing monitoring accuracy of soil salinization.
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Received: 2013-05-02
Accepted: 2013-08-21
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Corresponding Authors:
SHI Zhou
E-mail: shizhou@zju.edu.cn
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[1] Dehaan R L, Taylor G R. Remote Sensing of Environment, 2002, 80: 406.
[2] Metternicht G I, Zinck J A. Remote Sensing of Environment, 2003, 85: 1.
[3] SHI Yu-lin. Ed(石玉林主编). Lomd Resources Data Sets of “1∶1 Million Map of Chinese Land Resources”(《中国1∶100万土地资源图》土地资源数据库). Beijing: China Renmin University Press(北京: 中国人民大学出版社), 1991.
[4] The National Soil Survey Office(全国土壤普查办公室). Soils of China(中国土壤). Beijing: China Agriculture Press(北京: 中国农业出版社), 1998.
[5] Chang C W, Laird D A. Soil Science, 2002, 167(2): 110.
[6] Metternicht G I, Zinck J A. Remote Sensing of Environment, 2003, 85(1): 1.
[7] LI Jian-guo, PU Li-jie, ZHU Ming, et al(李建国, 濮励杰, 朱 明, 等). Acta Geographica Sinica(地理学报), 2012, 67(9): 1233.
[8] WENG Yong-ling, QI Hao-ping, FANG Hong-bin, et al(翁永玲, 戚浩平, 方洪宾, 等). Acta Pedologica Sinica(土壤学报), 2009, 47(6): 1255.
[9] FAN Yan-guo, HOU Chun-ling, ZHU Hao, et al(樊彦国, 侯春玲, 朱 浩, 等). Geography and Geo-Information Science(地理与地理信息科学), 2010, 26(6): 24.
[10] PU Zhi, YU Rui-de, YIN Chang-ying, et al(蒲 智, 于瑞德, 尹昌应, 等). Bulletin of Soil and Water Conservation(水土保持通报), 2012, 32(6): 129.
[11] ZHAO Zhen-liang, Tashpolat Tiyip, ZHANG Fei, et al(赵振亮, 塔西甫拉提·特依拜, 张 飞, 等). Journal of Natural Disasters(自然灾害学报), 2012, 21(5): 72.
[12] LIU Ya, PAN Xian-zhang, WANG Chang-kun, et al(刘 娅, 潘贤章, 王昌昆, 等). Acta Pedologica Sinica(土壤学报), 2012, 49(4): 824.
[13] ZHANG Xiao-guang, HUANG Biao, JI Jun-feng, et al(张晓光, 黄 标, 季峻峰, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2012, 32(8): 2075.
[14] WANG Jing, LIU Xiang-nan, HUANG Fang, et al(王 静, 刘湘南, 黄 方, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2009, 25(12): 161.
[15] LU Xia(卢 霞). Bulletin of Soil and Water Conservation(水土保持通报), 2012, 32(5): 186.
[16] WANG Yan, WANG Zheng-xiang, LIAN Xiao-juan, et al(王 艳, 王正祥, 廉晓娟, 等). Tianjin Agricultural Sciences(天津农业科学), 2011, 17(2): 18.
[17] YIN Jian-dao, SUN Jia-jie, HAO Zhi-qiang, et al(尹建道, 孙佳杰, 郝志强, 等). Journal of Anhui Agricultural Sciences(安徽农业科学), 2010, 38(30): 16882. |
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