干旱区生态环境知识资源中心(Arid): 基于分数阶微分的荒漠土壤铬含量高光谱检测

Arid

	基于分数阶微分的荒漠土壤铬含量高光谱检测
其他题名	Spectral Detection of Chromium Content in Desert Soil Based on Fractional Differential
	王敬哲; 塔西甫拉提·特依拜; 张东
来源期刊	农业机械学报
ISSN	1000-1298
出版年	2017
卷号	48 期号:5 页码:152-158
中文摘要	为解决高光谱检测土壤中痕量级重金属含量存在的困难,提高土壤重金属铬含量检测的准确度,利用新疆准东煤田周边168个荒漠土壤样本的重金属铬含量及其对应的高光谱数据,运用分数阶微分算法进行光谱数据预处理,最后利用全部波段进行偏最小二乘建模并进行可视化分析,旨在探讨分数阶微分预处理在高光谱数据估算荒漠土壤重金属铬含量的可能性。结果表明:原始光谱与吸光率变换的分数阶微分模型均在1.8阶微分处达到了最好的精度效果。吸光率变换1.8阶微分模型为最优模型,模型的校正均方根误差为7.68 mg/kg, R_c~2=0.83,预测均方根误差为8.39 mg/kg, R_p~2=0.78,相对分析误差为2.14。最后利用铬含量实测值与光谱预测值通过反距离加权法插值获得研究区土壤重金属铬含量的空间分布,说明利用该方法对土壤重金属铬含量定量检测并进行大尺度的空间分布反演在一定程度上是可行的,为荒漠土壤重金属污染状况的高光谱检测提供了一定的科学依据和技术支持。
英文摘要	To solve the problem in prediction of soil heavy metal content at trace levels by hyperspectral data and improve the accuracy of prediction in soil chromium (Cr) content, fractional order differential algorithm was brought in to preprocess hyperspectral data. With 168 samples of soil taken from the open coalmine area in Eastern Junggar Basin, China, the soil heavy metal Cr contents and the reflectance of these samples were measured by indoors experiments. The hyperspectral data were preprocessed by using fractional order differential algorithm, all of the wavelengths among 401~2 400 nm were used to calibrate the hyperspectral estimation models of soil Cr content by partial least squares regression (PLSR) and the predicted values were used in visualization analysis. Finally, the possibility of prediction of chromium content in soil with hyperspectral data preprocessed by fractional differential in coalmine area was discussed. The results showed that fractional order differential model of the raw reflectance and the absorption rate transform both achieved the best performance at the 1.8-order derivative. Among all of the models through fractional order differential preprocessing, the model based on 1.8-order derivative of absorbance transform (RMSEC was 7.68 mg/kg, R_c~2=0.83, RMSEP was 8.39 mg/kg, R_p~2=0.78,RPD was 2.14) was much better than others, and had better performance in predicting Cr content in desert soil. Then the spatial distribution of the actual Cr content and its estimation values in soil of the study area were obtained by inverse distance weighted (IDW) algorithm. Moreover, the spatial distributions showed the same trend. The results showed that quantitative inversion of soil Cr content and the spatial distribution of large scale were feasible by this method. This research would provide scientific basis and technical support for the application in monitoring heavy metal contamination by hyperspectral data.
中文关键词	荒漠土壤 ; 重金属 ; 铬 ; 分数阶微分 ; 高光谱
英文关键词	desert soil heavy metal chromium fractional differential hyperspectral
语种	中文
国家	中国
收录类别	CSCD
WOS类目	ENVIRONMENTAL SCIENCES
WOS研究方向	Environmental Sciences & Ecology
CSCD记录号	CSCD:5991881
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/236352
作者单位	新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国
推荐引用方式 GB/T 7714	王敬哲,塔西甫拉提·特依拜,张东. 基于分数阶微分的荒漠土壤铬含量高光谱检测[J]. 新疆大学,2017,48(5):152-158.
APA	王敬哲,塔西甫拉提·特依拜,&张东.(2017).基于分数阶微分的荒漠土壤铬含量高光谱检测.农业机械学报,48(5),152-158.
MLA	王敬哲,et al."基于分数阶微分的荒漠土壤铬含量高光谱检测".农业机械学报 48.5(2017):152-158.