Analysis and extraction of takyr solonetzs salinization information based on hyperspectral indices

Guan Hong; Jia Keli; Zhang Zhinan

In the present study, Pingluo of Ningxia Province in China was taken as the study area, and spectral data obtained by Unispec-SC, the value of soil salt content measured by experiment were taken as the basic data. Hyper-spectral data processing method was used to analyze spectral characteristics of different levels of salinization area vegetation. Spectral data were transformed in 16 different approaches, including logarithm, root mean squares, and first order differentiation. Correlation analysis was carried out between the obtained spectra and soil salinity. The most sensitive bands was selected, soil index and vegetation index were built. Nonlinear regression was employed to establish soil salinization remote sensing monitoring model. The results show that by comparing various spectral transformations, the first order differential of soil spectral was the most sensitive to soil salinization degrees. The model was based on the spectral index, including SI and MSAVI, and it could monitor soil salinization accurately. The correlation between simulated values and measured values was 0.758 9. The soil salinization could be achieved rapidly in the area.

1. College of Resource and Environment,Ningxia University,Yinchuan 750021,China;

2. Ningxia Key Laboratory of Intelligent Sensing for Desert Information,Yinchuan 750021,China

Received Date: 2014-04-05

Rev Recd Date: 2014-05-03

Publish Date: 2014-12-25

Key words:

Abstract: In the present study, Pingluo of Ningxia Province in China was taken as the study area, and spectral data obtained by Unispec-SC, the value of soil salt content measured by experiment were taken as the basic data. Hyper-spectral data processing method was used to analyze spectral characteristics of different levels of salinization area vegetation. Spectral data were transformed in 16 different approaches, including logarithm, root mean squares, and first order differentiation. Correlation analysis was carried out between the obtained spectra and soil salinity. The most sensitive bands was selected, soil index and vegetation index were built. Nonlinear regression was employed to establish soil salinization remote sensing monitoring model. The results show that by comparing various spectral transformations, the first order differential of soil spectral was the most sensitive to soil salinization degrees. The model was based on the spectral index, including SI and MSAVI, and it could monitor soil salinization accurately. The correlation between simulated values and measured values was 0.758 9. The soil salinization could be achieved rapidly in the area.

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[1]	Weng Yongling, Gong Peng. A review on remote sensing technique for Sali-affected soils [J]. Scientia Geographica Sinica, 2006, 3: 369-375. (in Chinese) 翁永玲, 宫鹏. 土壤盐渍化遥感应用研究进展[J]. 地理科学, 2006, 3: 369-375.
[2]
[3]
[4]	Yao Yuan, Ding Jianli, Ardak-Kelimu, et al. Reasearch on remote sensing monitoring of soil salinization based on measured hyperspertral and EM38 date [J]. Spectroscopy and Spectral Analysis, 2013, 33(7): 1917-1921. (in Chinese) 姚远, 丁建丽, 阿尔达-克里木, 等. 基于实测高光谱和电磁感应数据的区域土壤盐渍化遥感监测研究[J]. 光谱学与光谱分析, 2013, 33(7): 1917-1921.
[5]
[6]	Zhang Fang, Xiong Heigang, Luan Fuming, et al. Characteristics of field-measured spectral response to akalinization soil [J]. Journal of Infrared and Millimeter Waves, 2011, 30(1): 55-60. (in Chinese) 张芳, 熊黑钢, 栾福明, 等. 土壤碱化的实测光谱响应特征[J]. 红外与毫米波学报, 2011, 30(1): 55-60.
[7]	Jia Keli, Zhang Junhua. Prediction of the salinity information of Takyr Solonetzs based on the spectral characteristics of rice Canopy Indexes [J]. Chinese Journal of Soil Sscience, 2012, 43(2): 281-285. (in Chinese) 贾科利, 张俊华. 基于水稻冠层植被指数的龟裂碱土盐碱化信息预测研究[J]. 土壤通报, 2012, 43(2): 281-285.
[8]
[9]
[10]	Qiong Yurong, Jia Zhenhong, Yu Jiong,et al. Application of BP-ANN to classification of hyperspectral grassland in desert[J]. Computer Engineering and Applications, 2011, 47(12): 225-228. (in Chinese) 钱育蓉, 贾振红, 于炯, 等. BP-ANN 在荒漠草地高光谱分类研究中的应用[J]. 计算机工程与应用, 2011, 47(12): 225-228.
[11]
[12]	Yang Kai, Shen Weishou, Liu Bo, et al. Reasearch on spectral reflectance characteristics for Naqu typical grassland[J]. Remote Sensing Technology and Application, 2014, 29(1): 40-45. (in Chinese) 杨凯, 沈渭寿, 刘波, 等. 那曲典型草地植被光谱特征分析[J]. 遥感技术与应用, 2014, 29(1): 40-45.
[13]
[14]	Qian Yurong, Yang Feng, Li Jianlong, et al. Estimation of photosynthetic pigment of Festuca arundinacea using hyperspectral date [J]. Acta Prataculturae Sinica, 2009, 18 (4): 94-102. (in Chinese) 钱育蓉, 杨峰, 李建龙, 等. 利用高光谱数据快速估算高羊茅牧草光合色素的研究[J]. 草业学报, 2009, 18(4): 94-102.
[15]	Li Ziyang, Qian Yonggang,Shen Qingfeng,et al. Leaf area index retrieval from remotely sensed hyper spectral date [J]. Infrared and Laser Engineering, 2014, 43 (3): 944-949. (in Chinese) 李子扬, 钱永刚, 申庆丰, 等. 基于高光谱数据的叶面积指数遥感反演[J]. 红外与激光工程, 2014, 43(3): 944-949.
[16]
[17]	Lei Lei, Tiyip T, Ding Jiangli,et al. Soil salinization information extraction by using hyperspectral date of HJ-1A HIS:A case study in the Oasis of Ugan and Kuqa,Xinjiang, China[J]. Journal of Desert Research, 2013, 33(4): 1104-1109. (in Chinese) 雷磊, 塔西普拉提特依拜, 丁建丽, 等. 基于HJ-1A 高光谱影响的盐渍化土壤信息提取--以渭干河原库车河绿洲为例[J]. 中国沙漠, 2013, 33(4): 1104-1109.

Analysis and extraction of takyr solonetzs salinization information based on hyperspectral indices

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