徐涵秋, 孙凤琴, 徐光志. 高分五号高光谱AHSI和多光谱VIMI传感器数据的交互对比[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20200586
引用本文: 徐涵秋, 孙凤琴, 徐光志. 高分五号高光谱AHSI和多光谱VIMI传感器数据的交互对比[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20200586
XU Hanqiu, SUN Fengqin, XU Guangzhi. Cross comparison of the Gaofen-5 AHSI and VIMI sensors[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20200586
Citation: XU Hanqiu, SUN Fengqin, XU Guangzhi. Cross comparison of the Gaofen-5 AHSI and VIMI sensors[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20200586

高分五号高光谱AHSI和多光谱VIMI传感器数据的交互对比

Cross comparison of the Gaofen-5 AHSI and VIMI sensors

  • 摘要: 高分五号卫星搭载的对地观测传感器有高光谱传感器(AHSI)和全谱段光谱传感器(VIMI),但这两种传感器之间的光谱信号是否一致迄今仍鲜有报道。因此,本次研究通过敦煌定标场和滕州地区的3对AHSI和VIMI同步影像对,对2种传感器辐亮度数据之间的一致性进行了交互对比,并与同步的Landsat-8 OLI辐亮度数据进行验证。结果发现,2种传感器的辐亮度数据之间存在着一定的偏差,VIMI的辐亮度数据明显小于AHSI,其偏差率接近32%,二者的R2也只有0.817;在各个对应波段之间,红波段的差距最大,其偏差率超过了40%。与Landsat-8 OLI的验证表明,AHSI的辐亮度数据与OLI很接近,偏差率小于5%,但VIMI数据的偏差率则大于20%。鉴于VIMI和AHSI的辐亮度数据存在着差距,在现阶段如需要同时应用二者的数据,建议要对VIMI数据进行转换校正。本次利用敦煌试验区的模型进行的转换结果表明,VIMI辐亮度数据经转换后可大幅缩小与AHSI数据之间的差距,有利于二者的协同使用。

     

    Abstract: The Advanced HyperSpectral Imager (AHSI) and the Visual and Infrared Multispectral Imager (VIMI) are the two sensors onboard China's Gaofen-5 remote sensing satellite. These two sensors provide images of different spectral and spatial resolutions. To date, the quantitative relationship between the two sensors' data has not been investigated in detail. To understand the quantitative relationship and the calibration agreement between AHSI and VIMI, date-coincided image pairs of the two sensors from the Dunhuang calibration site as well as the Tengzhou area were used to conduct a cross comparison. The approach was achieved by evaluating the consistency of the at-sensor radiance data between the two sensors. The results were then validated to those of near-simultaneous Landsat-8 OLI sensor. This study finds that the at-sensor radiance data of VIMI is overall lower than that of AHSI, with a mean absolute percentage error (MAPE) of 32% and an R2 of 0.817. Among the corresponding bands, the red band has the greatest difference between the two sensors, with a MAPE of more than 40%. The validation to Landsat-8 OLI shows that AHSI's radiance data is close to that of OLI with a MAPE of less than 5%, while the MAPE of VIMI is more than 20%. Given the differences between VIMI and AHSI radiance data revealed in this study, it is suggested to correct VIMI data if both data need to be used together. The conversion using the model developed in this study based on the Dunhuang site shows that the difference between the VIMI and the AHSI radiance data can be greatly reduced after conversion. A synergistic use of AHSI and calibrated VIMI data can greatly benefit the science community by proving a high-quality observation of the Earth.

     

/

返回文章
返回