干旱区生态环境知识资源中心(Arid): 干旱区绿洲耕层土壤重金属铬含量的高光谱估测

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	干旱区绿洲耕层土壤重金属铬含量的高光谱估测
其他题名	Hyperspectral Estimation of Heavy Metal Chromium Content in Arable Soil of Arid Area Oasis
	王雪梅; 玉米提·买明; 毛东雷; 梁婷
来源期刊	生态环境学报
ISSN	1674-5906
出版年	2021
卷号	30 期号:10 页码:2076-2084
中文摘要	土壤重金属铬含量的高光谱估测技术较传统测量方法具有无污染、方便快捷进行动态监测的优势。对新疆渭干河-库车河三角洲绿洲耕层土壤98个样品的原始光谱反射率R分别进行倒数1/R、对数lg(R)、倒数对数lg(1/R)以及微分变换。不同处理结果与实测土壤重金属铬含量进行相关分析从而筛选出具有极显著相关的特征波段(P<0.001)。以不同变换处理下的特征波段反射率作为自变量,土壤铬含量为因变量,采用多元线性逐步回归、偏最小二乘回归、BP神经网络和随机森林回归方法构建土壤重金属铬含量的高光谱估测模型,并对最优估测结果进行克里格空间插值。结果表明,(1)原始光谱反射率的微分变换处理可有效提升光谱与土壤重金属铬含量之间的敏感性,其中经微分变换后的土壤光谱反射率与铬含量的相关系数由0.487显著提高到0.669(P<0.001)。(2)综合比较各模型的训练集和验证集估测结果,经倒数对数一阶微分[lg(1/R)]'处理后的BP神经网络模型具有较高的估测精度和很强的稳定性,可作为研究区土壤重金属铬含量的最优估测模型,其决定系数(R_d~2)在0.8以上,均方根误差(RMSE)小于6.5,相对分析误差(RPD)大于2。(3)研究区土壤重金属铬含量具有中等空间变异性,低含量区域主要分布在新和县和沙雅县的外缘地带,而位于库车市东北部区域的耕层土壤铬含量达到最高水平。受人类活动影响该绿洲的土壤污染问题日趋严重,耕层土壤重金属铬含量呈现出较高含量的空间分布。
英文摘要	Compared with the traditional surveying method, the hyperspectral method for estimating the content of heavy metal chromium in soil has the advantages of non-pollution, convenient and rapid dynamic monitoring.The inverse 1/R, logarithm lg(R), logarithm lg(1/R)and differential transformation of the original spectral reflectance R of 98 soil samples from the delta oasis of Weigan- Kuqa River in Xinjiang were carried out respectively.Correlation analysis was conducted between the results of different treatments and the measured soil heavy metal of chromium content, so as to screen out the characteristic bands with extremely significant correlation(P<0.001).With the characteristics of band reflectance under different transformation processing as the independent variable, the soil chromium content as the dependent variable, using multiple linear stepwise regression, partial least-squares regression and BP neural network and regression method to build the random forest soil heavy metal chromium content of high spectral estimation model, and conduct the optimal estimate result Kriging interpolation space.The results showed that:(1)Differential transformation of original spectral reflectance could effectively improve the sensitivity between spectral reflectance and soil heavy metal chromium content, and the correlation coefficient between spectral reflectance and soil heavy metal chromium content after differential transformation was significantly increased from 0.487 to 0.669(P<0.001).(2)Comprehensively compare the estimation results of the training set and the validation set of each model, the inverse logarithms first-order differential [lg(1/R)]' after being processed of BP neural network model has high estimation precision and strong stability, can be used as the optimal estimate model of soil heavy metal chromium content in the study area, the decision coefficient(R_d~2)is over 0.8, the root mean square error(RMSE)is less than 6.5 and residual predictive deviation(RPD)is greater than 2.(3)Soil heavy metal chromium content in the study area is showed moderate spatial variability.The low-content areas were mainly distributed in the outer edge of Xinhe County and Shaya County, while the topsoil chromium content in the northeastern area of Kuqa City reached the highest level.Due to the influence of human activities, the soil pollution of the oasis has become more and more serious, and the content of heavy metal chromium in surface soil of farmland shows a relatively high spatial distribution.
中文关键词	土壤铬 ; 高光谱估测 ; 特征波段 ; 多元线性逐步回归 ; 偏最小二乘回归 ; BP神经网络 ; 随机森林回归
英文关键词	soil chromium hyperspectral estimation characteristic band multiple linear stepwise regression partial least squares regression BP neural network random forest regression
类型	Article
语种	中文
收录类别	CSCD
WOS类目	Environmental Sciences & Ecology
CSCD记录号	CSCD:7116181
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/377833
作者单位	王雪梅, 新疆师范大学地理科学与旅游学院;;新疆维吾尔自治区重点实验室(新疆干旱区湖泊环境与资源实验室), ;;新疆维吾尔自治区重点实验室(新疆干旱区湖泊环境与资源实验室), 乌鲁木齐;;乌鲁木齐, 新疆;;新疆 830054;;830054, 中国.; 毛东雷, 新疆师范大学地理科学与旅游学院;;新疆维吾尔自治区重点实验室(新疆干旱区湖泊环境与资源实验室), ;;新疆维吾尔自治区重点实验室(新疆干旱区湖泊环境与资源实验室), 乌鲁木齐;;乌鲁木齐, 新疆;;新疆 830054;;830054, 中国.; 玉米提·买明, 新疆师范大学地理科学与旅游学院, 乌鲁木齐, 新疆 830054, 中国.; 梁婷, 新疆师范大学科研处, 乌鲁木齐, 新疆 830054, 中国.
推荐引用方式 GB/T 7714	王雪梅,玉米提·买明,毛东雷,等. 干旱区绿洲耕层土壤重金属铬含量的高光谱估测[J],2021,30(10):2076-2084.
APA	王雪梅,玉米提·买明,毛东雷,&梁婷.(2021).干旱区绿洲耕层土壤重金属铬含量的高光谱估测.生态环境学报,30(10),2076-2084.
MLA	王雪梅,et al."干旱区绿洲耕层土壤重金属铬含量的高光谱估测".生态环境学报 30.10(2021):2076-2084.