高光谱技术联合归一化光谱指数估算土壤有机质含量  

Estimation of Soil Organic Matter Content Using Hyperspectral Techniques Combined with Normalized Difference Spectral Index

作　　者：洪永胜[1,2] 朱亚星[1,2] 苏学平 朱强[1,2] 周勇[1,2] 于雷[1,2] HONG Yong-sheng ZHU Ya-xing SU Xue-ping ZHU Qiang ZHOU Yong YU Lei(Hubei Provincial Key Laboratory for the Analysis and Simulation of Geographical Process, Central China Normal University, Wuhan 430079, China College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China)

机构地区：[1]华中师范大学地理过程分析与模拟湖北省重点实验室,湖北武汉430079 [2]华中师范大学城市与环境科学学院,湖北武汉430079

出　　处：《光谱学与光谱分析》2017年第11期3537-3542,共6页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(41401232;41271534);中央高校基本科研业务费专项资金项目(CCNU15A05006;CCNU15A05004)资助

摘　　要：随着近地高光谱遥感技术的发展,为快速、有效、非破坏性地获取土壤有机质(SOM)信息提供了可能。土壤高光谱波段数据众多,光谱数据变量之间存在较为严重的多重共线性,影响模型复杂结构,而构建归一化光谱指数(NDSI)可以有效去除冗余信息变量,放大光谱特征信息。以江汉平原公安县为研究区,采集56份耕层土样,在室内获取土壤光谱数据,采用"重铬酸钾-外加热法"测定SOM含量,对实测土壤光谱数据(Raw)进行倒数之对数(LR)、一阶微分(FDR)和连续统去除(CR)三种变换,计算四种变换的NDSI数值,分析SOM与NDSI的二维相关性,并对一维、二维相关系数进行全波段范围内的p=0.001水平上显著性检验,提取敏感波段和敏感光谱指数,结合偏最小二乘回归(PLSR)建立SOM的估算模型,探讨二维光谱指数用于建模的可行性。研究表明,二维相关系数相比一维相关系数有不同程度的提升,以LR最为显著,相关系数数值提升约0.26;基于二维相关性分析提取的敏感光谱指数的PLSR建模效果整体优于一维相关性分析提取的敏感波段,其中,NDSILR-PLSR模型的稳健性最优,验证集R2为0.82,模型验证RPD值为2.46,模型稳定可靠,可以满足SOM的精确监测需要,适合推广到区域范围内低分辨率的航空航天遥感(如ASTER,Landsat TM等),应用潜力较大。In recent years,proximal hyperspectral technology provides a new approach in timely,effectively and nondestructive way to detect soil organic matter （SOM）.However,the hyperspectral dataset contains too many wavelengths which could lead to the collinearity,redundancy and noise to models.The Normalized Difference Spectral Index （NDSI）derived from soil spectral reflectance could enhance the relationship between spectral features and SOM,and also could eliminate the irrelevant wave-lengths.In this paper,56 topsoil samples at 0～20 cm depth were collected as research objects from Gong＇an County in Jianghan Plain,the spectral reflectance was measured using the ASD FieldSpec3 spectrum analyzer,and the SOM was determined using potassium dichromate external heating method in the laboratory.In the next stage,the raw spectral reflectance （Raw）was pre-pared for three spectral transformations,i.e.inverse-log reflectance （LR）,first order differential reflectance （FDR）and contin-uum removal reflectance （CR）.2-D correlograms of the determination coefficients （R 2 ）were constructed using all two-band combinations of 4 spectral transformations in NDSI against SOM in the range of 400～2400 nm.Then,the determination coeffi-cients （R 2 ）of the 4 spectral transformations for 1-D determination coefficients and 2-D determination coefficients by F significant test were got （p 〈0.001）,which could be used to extract sensitive bands and spectral index.At last,partial least squares re-gression （PLSR）method were used to build quantitative inversion model of SOM based on sensitive bands and spectral index for this study area,respectively.Feasibility of 2-D spectral index for building model was this study aimed to explore.The results showed that,the 2-D determination coefficients were better than 1-D determination coefficients,especially the determination co-efficients of LR was improved by about 0.26.Compared to the sensitive bands derived from 1-D determination coefficients,on the whole,the sensit

关 键 词：土壤有机质 高光谱 归一化光谱指数 偏最小二乘回归 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]