面向地质应用的ZY-102D高光谱数据大气校正方法对比  

Comparative study on atmospheric correction methods for ZY-102D hyperspectral data for geological applications

作　　者：李娜 董新丰 王靖岚[3] 陈理 甘甫平 李彤彤 张世凡 LI Na;DONG Xinfeng;WANG Jinglan;CHEN Li;GAN Fuping;LI Tongtong;ZHANG Shifan(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources,Beijing 100083,China;School of Earth Sciences and Resource,China University of Geosciences(Beijing),Beijing 100083,China;Sichuan Water Conservancy Vocational College,Chengdu 610000,China)

机构地区：[1]中国自然资源航空物探遥感中心,北京100083 [2]中国地质大学(北京)地球科学与资源学院,北京100083 [3]四川水利职业技术学院,成都610000

出　　处：《自然资源遥感》2023年第4期17-24,共8页Remote Sensing for Natural Resources

基　　金：国家重点研发计划项目“中空间分辨率光谱地球研发与应用技术研究”(编号:2019YFE0127300);民用航天项目(编号:D040102);中国地质调查局项目“全国遥感地质调查与监测”(编号:DD20221642)共同资助。

摘　　要：高光谱数据凭借其在光谱维的技术优势,在地物精细识别尤其是矿物信息精准识别方面应用广泛。高光谱反射率产品是开展矿物识别的基础数据依据,使用合适的大气校正方法获取能够满足应用需求的高精度的地表反射率产品至关重要。为此,采用ATCOR,FLAASH和QUAC这3种应用相对较广的大气校正模型,对资源一号02D(ZY-102D)卫星高光谱数据进行大气校正处理,并从目视效果、典型地物波谱分析和矿物信息提取3个方面开展了对比分析。分析结果表明:在目视效果上,3种大气校正模型均能有效提升影像清晰度,ATCOR模型略优于FLAASH和QUAC模型;3种模型典型地物光谱与ASD实测光谱相关系数平均值R 2达0.7以上,吻合度较好,精度较高,ATCOR模型反演结果的影像光谱更接近ASD实测光谱;对绿泥石识别结果三者一致性较好,绢云母一致性则稍差,对比发现FLAASH和QUAC模型在地表绢云母含量较低区域漏识率较高。综上所知,3种模型大气校正效果均比较理想,但在矿物识别应用中ATCOR模型较FLAASH和QUAC模型总体上有优势。Hyperspectral data,exhibiting technical advantages in the spectral dimension,have been extensively used for accurately identifying surface features,particularly mineral information.Mineral identification relies on hyperspectral reflectance products,necessitating the application of proper atmospheric correction methods to obtain high-precision surface reflectance products that meet application requirements.Hence,three commonly used atmospheric correction models,ATCOR,FLAASH,and QUAC,were utilized to correct the hyperspectral data acquired by the ZY-102D satellite.Moreover,a comparative analysis was conducted on their visual effects,spectral analysis of typical surface features,and extraction of mineral information.The results are as follows:①All three atmospheric correction models can effectively enhance image clarity in terms of visual effects.Specifically,the ATCOR model slightly outperformed the FLAASH and QUAC models;②The correlation coefficients(R 2)between the typical surface feature spectra of the three models and the ASD-measured spectra showed average values exceeding 0.7,suggesting high consistency and accuracy.Especially,the imaging spectra derived from the inversion results of the ATCOR model were more similar to the ASD-measured spectra;③The three models yielded relatively consistent results in chlorite identification but divergent results in sericite identification.Comparatively,the FLAASH and QUAC models exhibited high omission rates in surface regions with low sericite content.Overall,all three models can achieve satisfactory atmospheric correction effects,but the ATCOR model is superior to the other two models in mineral identification.

关 键 词：资源一号02D 大气校正 ATCOR FLAASH QUAC 矿物识别 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] P627[自动化与计算机技术—控制科学与工程]