[1]沈从旺,徐丽华.土壤pH值和全钾含量高光谱反演方法比较[J].江苏农业学报,2020,(01):92-98.[doi:doi:10.3969/j.issn.1000-4440.2020.01.013]
 SHEN Cong-wang,XU Li-hua.Comparison of hyperspectral inversion methods for soil pH value and total potassium content[J].,2020,(01):92-98.[doi:doi:10.3969/j.issn.1000-4440.2020.01.013]
点击复制

土壤pH值和全钾含量高光谱反演方法比较()
分享到:

江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年01期
页码:
92-98
栏目:
耕作栽培·资源环境
出版日期:
2020-02-29

文章信息/Info

Title:
Comparison of hyperspectral inversion methods for soil pH value and total potassium content
作者:
沈从旺 徐丽华
(西南大学资源环境学院,重庆400715)
Author(s):
SHEN Cong-wangXU Li-hua
(College of Resources and Environment, Southwestern University, Chongqing 400715, China)
关键词:
支持向量回归pH值全钾含量高光谱反演
Keywords:
support vector regressionpH valuetotal potassium contenthyperspectral inversion
分类号:
TP79
DOI:
doi:10.3969/j.issn.1000-4440.2020.01.013
文献标志码:
A
摘要:
为了预测土壤pH值和全钾含量,采集111个土壤样本的高光谱信息,采用小波变换后去包络的方法对原始光谱信息进行预处理,利用相关性分析法选择土壤光谱特征波段,进行偏最小二乘法回归(PLSR)、主成分分析回归(PCR)、支持向量回归(SVR)3种方法的土壤pH值和全钾含量高光谱反演精度的比较研究。结果显示,在水稻土和紫色土全钾含量和水稻土pH值的反演中,SVR方法都取得了比PLSR方法和PCR方法更好的反演效果。在紫色土pH值反演中,PLSR方法和PCR方法反演效果均优于SVR方法。比较不同类型土壤和不同土壤参数的反演效果发现,水稻土土壤pH值和全钾含量的反演效果均强于紫色土,全钾含量的反演效果优于pH值。本研究结果说明高光谱快速反演土壤pH值和全钾含量具有可行性。
Abstract:
In order to predict soil pH value and total potassium content, hyperspectral information of 111 soil samples was collected. The original spectral information was pretreated by continuum removal after wavelet transform. The characteristic bands of soil spectra were selected by correlation analysis method. A comparative study on hyperspectral inversion accuracy of soil pH and total potassium content was carried out by using partial least squares regression (PLSR), principal component analysis regression (PCR) and support vector regression (SVR). SVR method was better than PLSR method in the inversion of total potassium content of paddy soil and purple soil and pH value of paddy soil and PCR method in the inversion of total potassium content of paddy soil and purple soil and pH value of paddy soil. In the inversion of pH value of purple soil, the inversion results of PLSR method and PCR method were better than those of SVR method. Comparing the inversion models of different types of soil and different soil parameters, the inversion results of pH value and total potassium content of paddy soil were stronger than those of purple soil, and the inversion effect of total potassium content was better than that of pH value. THese results of this study indicate that it is feasible to retrieve soil pH value and total potassium content by hyperspectral method.

参考文献/References:

[1]尤承增,杨新源,束安,等. 土壤TK含量高光谱估测模型[J].遥感信息, 2017, 32(4): 92-97.
[2]李薇薇. 高光谱数据库的地物特征反演研究[D].武汉:华中师范大学, 2012.
[3]刘燕德,熊松盛,吴至境,等. 赣南脐橙园土壤全磷和TK近红外光谱检测[J].农业工程学报, 2013, 29(18) : 156-162.
[4]张东辉,赵英俊,秦凯,等. 高光谱土壤多元信息提取模型综述[J].中国土壤与肥料, 2018 (2): 22-28.
[5]刘秀英,石兆勇,常庆瑞,等. 黄绵土钾含量高光谱估算模型方法研究[J].土壤学报, 2018, 55(2): 325-337.
[6]陈红艳,赵庚星,李希灿,等. 小波分析用于土壤速效钾含量高光谱估测研究[J].中国农业科学, 2012, 45(7): 1425-1431.
[7]李诗朦,包妮沙,刘善军,等. 土壤电导率和pH值光谱特征及反演模型方法——以呼伦贝尔草原干旱半干旱土壤为例[J].测绘科学, 2018, 43(8): 14-22,44.
[8]魏雨露,刘金宝,李劲彬. 基于PLS的陕西关中地区土壤pH高光谱预测 [J].西部大开发(土地开发工程研究), 2018, 3(4): 51-57.
[9]王齐磊,江韬,赵铮,等.三峡库区典型农业小流域土壤溶解性有机质的紫外-可见及荧光特征[J].环境科学,2015,36(3):879-887
[10]杨剑虹,王成林,代亨林. 土壤农化分析与环境监测[M].北京:中国大地出版社, 2008:5-47.
[11]ASADZAEH S, ROBERTO C, FILHO D S. Iterative curve fitting: a robust technique to estimate the wavelength position and depth of absorption features from spectral data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(10): 5964-5974.
[12]陈红艳. 土壤主要养分含量的高光谱估测研究[D].泰安:山东农业大学, 2012.
[13]徐丽华. 土壤养分预测方法的比较研究[D].重庆:西南大学, 2012.
[14]WEBSTER R,LARK R M G P. Nason:wavelet methods in statistics with R[M]. New York: Springer, 2008:287-289.
[15]CHENG K P, GUO H F, SHEN H H, et al. An inversion method of leaf area index based on spectral absorption features[C]. Beihang University. Proceedings of the 36th chinese control conference. Beijing: Beihang University Press, 2017:1549-1554.
[16]彭小婷,高文秀,王俊杰. 基于包络线去除和偏最小二乘的土壤参数光谱反演[J].武汉大学学报(信息科学版),2014,39(7): 862-866.
[17]雷宇斌,刘宁,郭云开,等. 高光谱组合变换下土壤Cd含量GWR模型反演研究[J].测绘工程,2018, 27(11): 71-76.
[18]张东辉,赵英俊,秦凯. 一种新的光谱参量预测黑土养分含量模型[J].光谱学与光谱分析,2018,38(9): 2932-2936.
[19]徐夕博,吕建树,吴泉源,等. 基于PCA-MLR和PCA-BPN的莱州湾南岸滨海平原土壤有机质高光谱预测研究[J].光谱学与光谱分析, 2018, 38(8): 2556-2562.
[20]金慧凝,张新乐,刘焕军,等. 基于光谱吸收特征的土壤含水量预测模型方法研究[J].土壤学报, 2016, 53(3): 627-635.
[21]CANDOLFI A,MAESSCHALCK R D,JOUANRIMBAUD D. The influence of data pre-processing in the pattern recognition of excipients near-infrared spectra1[J]. Journal of Pharmaceutical and Biomedical Analysis,1999,21:115-132.
[22]GALLMIER E,ZHANG S,MCFARLANE T.Using PCA and PLS on publicly available data to predict the extractability of hydrocarbons from shales [J]. Journal of Natural Gas Science and Engineering, 2017,44:109-121.
[23]邹慧敏,李西灿,尚璇,等. 粒子群优化神经网络的土壤有机质高光谱估测[J].测绘科学, 2019, 44(5): 146-150,170.
[24]贾方方,宋瑞芳,王芳,等. 基于变异系数法的灰色关联决策模型在烤烟品质评价中的应用[J].中国农学通报,2016,32(4): 124-128.
[25]刘焕军,王翔,李厚萱,等. 土壤矿物对松嫩平原主要土壤类型反射光谱特征的影响机理[J].光谱学与光谱分析,2018,38(10): 3238-3244.

相似文献/References:

[1]董海霞,赵明柳,唐守寅,等.石灰对土壤中Cd 和Zn 形态及对水稻有效性的影响[J].江苏农业学报,2016,(06):1320.[doi:doi:10.3969/j.issn.1000-4440.2016.06.020]
 DONG Hai-xia,ZHAO Ming-liu,TANG Shou-yin,et al.The effects of liming on the fraction and bioavailability to rice of Cd and Zn in a contaminated soil[J].,2016,(01):1320.[doi:doi:10.3969/j.issn.1000-4440.2016.06.020]
[2]何立超,马素敏,李成梁,等.温度、盐分以及 pH 值对鸭肉脂肪氧合酶活性的交互影响[J].江苏农业学报,2016,(06):1404.[doi:doi:10.3969/j.issn.1000-4440.2016.06.032]
 HE Li-chao,MA Su-min,LI Cheng-liang,et al.The interactive influence of temperature, salt concentration and pH on LOX activity of duck breast meat[J].,2016,(01):1404.[doi:doi:10.3969/j.issn.1000-4440.2016.06.032]
[3]牛贞福,国淑梅,徐金强,等.大蒜提取液对平菇竞争性杂菌的抑制及对平菇生长的促进作用[J].江苏农业学报,2016,(01):73.[doi:10.3969/j.issn.1000-4440.2016.01.011 ]
 NIU Zhen-fu,GUO Shu-mei,XU Jin-qiang,et al.Inhibition against competitive microbes of Pleurotus ostreatus by garlic extract and its growth-promoting effects[J].,2016,(01):73.[doi:10.3969/j.issn.1000-4440.2016.01.011 ]
[4]黄远芬,王欣,刘宝林.不同处理条件对明胶体系凝胶特性的影响[J].江苏农业学报,2015,(03):673.[doi:10.3969/j.issn.1000-4440.2015.03.033]
 HUANG Yuan-fen,WANG Xin,LIU Bao-lin.Gel properties of gelatin system affected by treatment conditions[J].,2015,(01):673.[doi:10.3969/j.issn.1000-4440.2015.03.033]
[5]郭松,常庆瑞,赵泽英,等.基于高光谱的不同生育期玉米花青素含量估测[J].江苏农业学报,2024,(02):303.[doi:doi:10.3969/j.issn.1000-4440.2024.02.012]
 GUO Song,CHANG Qing-rui,ZHAO Ze-ying,et al.Estimation of anthocyanin content in maize at different growth stages based on hyperspectral technology[J].,2024,(01):303.[doi:doi:10.3969/j.issn.1000-4440.2024.02.012]

备注/Memo

备注/Memo:
收稿日期:2019-05-27基金项目:中央高校基本科研业务费专项(XDJK2016C083);重庆市基础科学与前沿技术研究一般项目(cstc2016jcyjA0184);国家自然科学基金项目(41671291)作者简介:沈从旺(1994-),男,硕士研究生,安徽省马鞍山人,研究方向为土地资源与信息化技术。(E-mail)1439237791@ qq.om通讯作者:徐丽华, (E-mail)sweitlianna@126.om
更新日期/Last Update: 2020-03-13