摘要
资源一号02D(ZY1-02D)卫星搭载了我国自主研制的可见近红外相机(VNIC)和高光谱相机(AHSI),是我国首颗民用高光谱业务卫星,具有广泛的应用前景。通过整体辐射精度、信噪比、清晰度以及信息熵4个评价指标,对ZY1-02D VNIC和AHSI数据进行辐射质量评价,并分别采用Sentinel-2 MSI和GF-5 AHSI数据进行对比。结果表明:ZY1-02D VNIC数据在可见光波段具有亮度高、信噪比高等优势;在红边近红外等波段,影像具有灰度范围大、信息量大的特点。ZY-1-02D VNIC数据在影像亮度、灰度范围、清晰度和信息量方面均优于Sentinel-2,二者信噪比近似。ZY-1-02D AHSI数据在395—1341 nm范围内辐射质量良好;在1929—2501 nm范围,存在噪声严重的波段,影像质量较差。与GF-5 AHSI数据对比,ZY-1-02D AHSI数据的影像亮度和信噪比相当,但ZY-1-02D AHSI数据在灰度范围方面优势明显,且短波红外谱段的清晰度和信息量优于GF-5 AHSI数据。
ZY-1-02D is the first civil hyperspectral satellite in China,equipped with Visible Near-Infrared Camera(VNIC)and Advanced Hyperspectral Imager(AHSI).This study evaluates and analyzes the radiance quality of ZY-1-02D VNIC/AHSI data and compares them with Sentinel-2 MSI/GF-5 AHSI data.Four indicators are used to assess image quality:radiance precision,Signal-to-Noise Ratio(SNR),definition,and Shannon entropy.The results indicate that ZY-1-02D VNIC data has the advantages of high radiance and high SNR in visible bands.In red-edge and near-infrared bands,ZY-1-02D VNIC data has the advantages of a large gray range and a large amount of information.The comparison between ZY-1-02D and Sentinel-2 MSI data shows that ZY-1-02D VNIC data has better performance in radiance,gray range,definition,and information content.The performance of the two sensors is similar in terms of SNR.ZY-1-02D AHSI data has great quality in 395~1314 nm wavelength.However,in 1929—2501 nm,some bands have severe noise and poor quality caused by water vapor.The comparison between ZY-1-02D AHSI and GF-5 AHSI data shows that the performance in radiance and SNR of the two sensors are similar.The gray range of ZY-1-02D AHSI data is greater than GF-5AHSI data in both VNIR and SWIR.The definition and information content of ZY-1-02D AHSI data are better than GF-5 AHSI data in SWIR bands.
作者
孙培宇
柯樱海
钟若飞
赵世湖
刘瑶
Sun Peiyu;Ke Yinghai;Zhong Ruofei;Zhao Shihu;Liu Yao(State Key Laboratory Cultivation Base of Urban Environment Process and Simulation,Beijing 100048,China;Beijing Laboratory of Water Resources Security,Beijing 100048,China;College of Resource Environment and Tourism,Capital Normal University,Beijing 100048,China;Land Satellite Remote Sensing Application Center,MNR,Beijing 100048,China)
出处
《遥感技术与应用》
CSCD
北大核心
2022年第4期938-952,共15页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(42071396)
国家重点研发计划项目(2017YFC0505903)资助