微分算法的艾比湖湿地自然保护区土壤有机质多光谱建模  

Study on Differential-Based Multispectral Modeling of Soil Organic Matter in Ebinur Lake Wetland

作　　者：李雪萍 张飞[1,2,3] 王小平 LI Xue-ping;ZHANG Fei;WANG Xiao-ping(College of Resources & Environmental Science,Xinjiang University,Urumqi 830046,China;Key Laboratory of Oasis Ecology,Xinjiang University,Urumqi 830046,China;General Institutes of Higher Learning Key Laboratory of Smart City and Environmental Modeling,Xinjiang University,Urumqi 830046,China)

机构地区：[1]新疆大学资源与环境科学学院,新疆乌鲁木齐830046 [2]新疆大学绿洲生态教育部重点实验室,新疆乌鲁木齐830046 [3]新疆智慧城市与环境建模普通高校重点实验室,新疆乌鲁木齐830046

出　　处：《光谱学与光谱分析》2019年第2期535-542,共8页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目"新疆联合基金本地优秀青年人才培养专项"(U1503302)资助

摘　　要：针对以往利用高光谱数据来来反演土壤有机质(SOM)的可行性与可靠性,结合微分处理对光谱数据信息提取的高效性,提出了直接对多光谱遥感影像进行微分处理就可得出SOM建模研究,旨在为今后SOM速测提供参考。采用Landsat 8_OLI多光谱遥感影像数据,对多光谱遥感影像进行辐射定标、几何校正、大气校正、镶嵌和裁剪,运用IDL软件对影像进行一阶微分处理和二阶微分处理,发现一阶微分图像能够更好地表达地物的真实情况,更好地区别水体与土壤。原始遥感影像包含大量的信息其中还包括噪声,通过微分处理后的遥感影像剔出了原始影像中反射率值突兀变化的部分。在研究区采用五点法采集土壤样品。室内实验用重铬酸钾氧化-容量法测得SOM数据。多光谱数据结合地面实测SOM数据,分析SOM与多光谱数据反射率的关系,发现一阶微分处理后的遥感数据与SOM含量的相关性存在敏感波段,说明一阶微分处理可以将原始遥感图像数据在多光谱范围内的一些隐含的土壤有机质信息释放出来。选取相关性高的数据建立基于原始遥感数据、一阶微分数据、二阶微分数据的单波段多光谱线性模型和多波段多光谱线性模型,选取最优模型来估算和反演土壤有机质含量。结论如下:(1)通过对原始影像进行微分处理发现,微分处理后的影像变化明显,一阶微分处理的影像噪声降低,更加突出了影像中土壤有机质隐藏的信息。二阶微分处理的影像抑制了土壤有机质信息。(2)原始遥感影像各波段数据对土壤有机质含量的相关性较低,一阶微分处理后的遥感影像数据反映出土壤有机质敏感波段即部分波段数据相关性明显高于原始数据,二阶微分处理后的遥感影像各波段数据对土壤有机质含量的相关性较弱。(3)多波段建模效果要优于单波段建模;一阶微分多波段模型预测精度最优,其模型�In this paper,according to the feasibility and reliability of using the hyperspectral data to retrieve SOM from hyperspectral data,combined with the high efficiency of differential processing in extracting spectral information,a new method based on differential algorithm for soil organic matter modeling In this study,the content of soil organic matter can be obtained by differentiating the multi-spectral remote sensing images directly,which aims to provide the direction for the future study of soil organic matter rapid measurement is proposed.In this paper,Landsat 8_OLI multi-spectral remote sensing image data is used to perform the radiation calibration,geometric correction,atmospheric correction,mosaic and cropping of multi-spectral remote sensing images.The first order differential and second order differential are processed by IDL software.The image can better express the real situation of the object.The first-order differential image can distinguish the water body from the soil better.The original remote sensing image contains a lot of information,including the noise.The differential image processed by the remote sensing image excludes the original image In the study area,five-point method was used to collect soil samples,indoor potassium dichromate oxidation-volume method to measure soil organic matter data,and multispectral data was used to analyze soil organic matter data from the ground to analyze soil organic matter It is found that there is a sensitive band in the correlation between the first-order differential data and soil organic matter content,indicating that the first-order differential processing can transform the original remote sensing image data in some obscure soil in the multi-spectral range.Organic information is released;select a high correlation number established based on the raw remote sensing data,first-order differential data,single-band multi-spectral data of the second order differential linear and multi-band multi-spectral linear model,and select the best model to estimate soil or

关 键 词：土壤有机质 微分算法 多光谱建模 

分 类 号：TP7[自动化与计算机技术—检测技术与自动化装置]