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遥感技术与应用  2019, Vol. 34 Issue (3): 540-546    DOI: 10.11873/j.issn.1004-0323.2019.3.0540
城市遥感专栏     
城市居民区土壤重金属含量高光谱反演研究
李琼琼1,柳云龙1,2
(1.上海师范大学城市生态与环境研究中心,上海 200234;
2.上海师范大学地理系,上海 200234)
Soil Heavy Metals Estimation based on Hyperspectral in Urban Residential
Li Qiongqiong1,Liu Yunlong1,2
(1.Research Center of Urban Ecology and Environment,Shanghai Normal University,Shanghai 200234,China;
2.Geography Department,Shanghai Normal University,Shanghai 200234,China)
 全文: PDF(2411 KB)  
摘要:

为探讨运用土壤光谱估算城市居民区土壤重金属含量的可能性,以上海闵行居民区土壤重金属Cu、Pb、Zn元素为研究对象,通过采集土壤样本,分析土壤光谱信息,构建基于高光谱的土壤重金属多元线性逐步回归(MLSR)和偏最小二乘回归(PLSR)模型。结果表明:通过倒数一阶和对数一阶微分变换能有效增强土壤重金属的光谱特征;土壤Cu、Pb和Zn元素最优波段分别出现在1 042.7 nm、706.84 nm和1 404.8 nm处;从模型稳定性和精确性来看,PLSR模型较优于MLSR模型。土壤Cu、Zn元素验证RMSE值仅为研究区该重金属含量均值的10%左右,拟合精度高。与Cu、Zn元素相比,Pb元素决定系数R2在0.64~0.88,模型稳定性较好。通过对光谱数据的预处理,采用偏最小二乘回归模型可有效提高估算城市居民区土壤重金属含量的精度。

关键词: 城市居民区土壤重金属高光谱多元线性逐步回归模型偏最小二乘回归模型    
Abstract: To explore the possibility of using soil spectral reflectance to estimate soil heavy metal content in urban residential area,this study chooses 30 soil samples of Cu,Pb and Zn in Minhang Residential area,Shanghai Province.Through the spectral factor transform to highlight its eigenvalues,constructed Multiple Linear Stepwise Regression(MLSR) model and Partial Least Squares Regression(PLSR) model based on spectral reflectance of soil heavy metals.The results show that the reciprocal first-order and the logarithmic first-order differential transformation can effectively enhance the heavy metal soil spectral characteristics.The best characteristic bands of Cu,Pb and Zn are 1 042.7 nm、706.84 nm and 1 404.8 nm.In terms of model stability and accuracy,PLSR model is better than MLSR model.The RMSE of Cu and Zn were only about 10% of the mean value of heavy metals in the study area,and the accuracy of the model was high.Compared with Cu and Zn,the R2 of Pb is between 0.64~0.88 which with higher model stability.By preprocessing the spectral data,the partial least-squares regression can effectively improve the accuracy of estimating the heavy metal content in urban residential areas.
〖WTHZ〗Key words:〖WT〗
Urban residential area;Soil heavy metals;Hyperspectral;Multivariate Linear Stepwise Regression(MLSR) model;Partial Least Squares Regression(PLSR) model
〖HT〗〖ST〗〖HJ〗〖WT〗〖JP〗〖LM〗
收稿日期: 2018-08-28 出版日期: 2019-07-01
ZTFLH:  O657.3  
基金资助: 国家自然科学基金项目“城市植物滞尘效应高光谱遥感探测方法与模型研究”(41571047),上海市教委重点学科建设项目(J50402)资助。
作者简介: 李琼琼(1992-),女,安徽阜阳人,硕士研究生,主要从事城市环境与生态研究。E-mail:llpa0716@163.com。
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引用本文:

李琼琼, 柳云龙. 城市居民区土壤重金属含量高光谱反演研究[J]. 遥感技术与应用, 2019, 34(3): 540-546.

Li Qiongqiong, Liu Yunlong. Soil Heavy Metals Estimation based on Hyperspectral in Urban Residential. Remote Sensing Technology and Application, 2019, 34(3): 540-546.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.3.0540        http://www.rsta.ac.cn/CN/Y2019/V34/I3/540

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