Impacts of spectral band difference effects on radiometric cross-calibration between satellite sensors in the solar-reflective spectral domain

In order for quantitative applications to make full use of the ever-increasing number of Earth observation satellite systems, data from the various imaging sensors involved must be on a consistent radiometric scale. This paper reports on an investigation of radiometric calibration errors due to differences in spectral response functions between satellite sensors when attempting cross-calibration based on near-simultaneous imaging of common ground targets in analogous spectral bands, a commonly used post-launch calibration methodology. Twenty Earth observation imaging sensors (including coarser and higher spatial resolution sensors) were considered, using the Landsat solar reflective spectral domain as a framework. Scene content was simulated using spectra for four ground target types (Railroad Valley Playa, snow, sand and rangeland), together with various combinations of atmospheric states and illumination geometries. Results were obtained as a function of ground target type, satellite sensor comparison, spectral region, and scene content. Overall, if spectral band difference effects (SBDEs) are not taken into account, the Railroad Valley Playa site is a “good” ground target for cross calibration between most but not all satellite sensors in most but not all spectral regions investigated. “Good” is defined as SBDEs within ± 3%. The other three ground target types considered (snow, sand and rangeland) proved to be more sensitive to uncorrected SBDEs than the RVPN site overall. The spectral characteristics of the scene content (solar irradiance, surface reflectance and atmosphere) are examined in detail to clarify why spectral difference effects arise and why they can be significant when comparing different imaging sensor systems. Atmospheric gas absorption features are identified as being the main source of spectral variability in most spectral regions. The paper concludes with recommendations on spectral data and tools that would facilitate cross-calibration between multiple satellite sensors.     

Water target based cross-calibration of CBERS-02 CCD camera with MODIS data

The CBERS-02, the second satellite of China Brazil Earth Resources Satellite series, was launched on Oct. 21, 2002. Onboard the satellite, there are three major sensors, a CCD camera, a wide field imager and an infrared multispectral scanner (http://www. cresda.com). The purpose of this paper is to calibrate the CCD camera with a methodol- ogy of cross-calibration. The spatial resolution of the multispectal bands of CCD camera is 19.5 m, the swath is about 115 km. It is capable of side…     

高光谱成像仪交叉定标技术研究及应用

针对高光谱成像仪的在轨定标,提出三种交叉定标技术方案,分析了时相匹配、视场匹配、光谱匹配和几何匹配等交叉定标过程中的关键单元技术,结合HJ-1A/HSI、EO-1/Hyperion等开展了交叉定标算法模型验证。通过这三种技术方案的应用,与场地定标相结合,将有利于提高在轨定标的频次、快速校验场地定标系数,有效提升高光谱数据的定量化应用水平。     

利用MODIS对FY-2E/VISSR红外窗区和水汽通道的交叉绝对辐射定标

介绍了利用高精度的TERRA/MODIS观测资料对FY-2E红外窗区和水汽吸收通道进行绝对交叉定标的方法,并选用2010年5、7和12三个月的卫星数据进行了交叉定标计算.结果表明,交叉定标系数计算亮温与MODIS匹配点处实测结果非常接近,约90％的亮温偏差小于1K,其中高温区结果更稳定,偏差小于低温区,这主要是由于低温区杂散光影响显著造成的.总的说来,借助TERRA/MODIS可以实现对FY-2E/VISSR的高频次高精度的绝对定标,为FY-2E在轨替代定标提供重要的方法基础.     

一种膝关节角度测量及其校准方法

针对膝关节角度测量问题，给出了一种基于微型加速度传感器测量角度原理的膝关节角度测量方法，该方法结合固定于膝关节同一位置但不同轴向角度的两个微型加速度传感器的测量数据，联合推算出膝关节角度。根据两个传感器输出加速度向量模相等的原理，进一步提出了测量角度的交叉校准方法。实验结果表明，采用该方法建立的膝关节角度测量系统，测量成本较低，测量精度达到±1．5°。     

Radiometric cross-calibration of the CBERS-02 CCD camera with the TERRA MODIS

With the requirement of quantitative application of remote sensing, it is more pressing to improve the accuracy of remote sensing. Slater proposed a calibration method using a large homogeneous surface target [1], which has been proved promising and has been applied to many sensors[2―10], such as TM, ETM+, HRVIR. However, this method re-quired so much labor and fund that it could not produce enough calibration coefficients. In addition, it could not be applied to history data. Later, many…     

基于光谱与几何匹配的GOCI与MODIS交叉辐射定标

海洋卫星COMs-1（Communication, Ocean &Meteorological Satellite-1）上携带的GOCI（Geostationary Ocean Color Imager）传感器以海洋监测为主,也具备较好的陆地监测潜力,但传感器陆地辐射特性存在偏差。为改善GOCI陆地辐射特性,基于MODIS数据,对GOCI可见光和近红外波段开展交叉辐射定标,弥补场地定标成本较高、定标参数更新周期长的不足,拓展其陆地定量遥感监测能力。交叉辐射定标中,考虑GOCI和MODIS传感器相应波段光谱响应函数之间的匹配; 通过辐射传输模拟,订正两传感器观测角度对辐射定标的影响;通过选取两传感器同一过境时刻的数据,降低太阳角度对辐射定标的影响,提高交叉定标精度。通过MODIS数据模拟的GOCI相应波段的表观辐亮度与GOCI实测结果比对,R2大于0.88。对定标结果进行初步验证,表明交叉辐射定标后,GOCI陆地上的辐射特性满足基本的定量遥感需求。     

珠海一号欧比特高光谱数据交叉辐射定标初探

搭载于“珠海一号”卫星星座的欧比特高光谱OHS（Orbit Hyper Spectral）传感器,以较高的光谱分辨率和空间分辨率,在近岸及内陆湖泊水色遥感应用方面具有很大潜力。然而OHS缺乏星上定标系统,目前在轨定标采用陆地定标场的资料,其定标结果在水体等低反射率地物误差较大。因此提出一种基于传感器入瞳总辐亮度的交叉辐射定标法,该方法结合QAA（Quasi-Analytical Algorithm）准分析算法和6SV2.1辐射传输模型,利用GOCI（Geostationary Ocean Color Imager）多光谱数据对OHS高光谱数据进行交叉辐射定标。研究结果表明：①GOCI和OHS传感器获取的地物辐射相关性好,在可见光波段范围内,R²均高于0.84;②重新定标后的数据能明显改善不同传感器之间的辐射差异,在可见光波段范围内,定标误差小于9%。实验为高光谱传感器的辐射定标提供了一种新的方法,对建立高光谱定量化、业务化水色遥感处理系统,特别对OHS数据在水域的各种应用具有重要意义。     

环境一号卫星CCD相机水体信息采集特性分析

利用覆盖我国4大海区共88景图像数据,针对4波段CCD相机(HJ-1A/CCD1、HJ-1A/CCD2、HJ-1B/CCD1、HJ-1B/CCD2)在水体中的信息采集特性进行分析。结果表明:(1)HJ-1A和B星虽不是水色卫星,但其CCD相机在水体中依然有一定的信息,可作为水色遥感器服务于水环境;(2)HJ-1B/CCD1在南海海域水体信息采集过程存在明显的太阳耀斑现象,因而在水色信息提取时太阳耀斑是一个不可忽略的因子;(3)无论是在一类水体还是在二类水体,各遥感器的近红外波段皆存在水体信息采集为零的现象,其中HJ1B-CCD2尤为明显。利用近10景涵盖了HJ-1A/CCD1、HJ-1A/CCD2、HJ-1B/CCD1、HJ-1B/CCD2数据,以及同时过境的EOS/MODIS,采用基于遥感器入瞳处总辐亮度的交叉定标方法进行交叉辐射定标,获取适用于水体目标的交叉辐射定标参数。最后根据瑞利散射和气溶胶散射的计算值,以及获取的交叉定标系数,反推出HJ1B-CCD2可能接受到的灰度值。     

基于Terra/MODIS数据的HJ-1B/CCD1交叉定标方法研究

交叉辐射定标是国际上新近发展起来的一种无场地定标方法,它的应用弥补了场地定标成本较高、定标参数更新周期较长的不足。对于我国2008年发射的环境与灾害监测预报小卫星CCD数据而言,探索交叉辐射定标方法的适用性,对及时发现传感器辐射性能的变化,促进CCD遥感数据的定量化应用具有重要意义。本研究以辐射定标精度较高的Terra/MODIS数据为参考,分别使用光线匹配法（RM）和辐射传输模型方法（RTM）对HJ-1B/CCD1数据进行交叉辐射定标,并与相同条件下进行的场地定标结果比较。实验结果表明,使用这两种方法获取的CCD1的第2、3、4波段的定标结果与场地定标结果差异较小,只有第1波段定标结果与场地定标结果差异相对较大,这证明了交叉辐射定标方法的有效性。另外,虽然RTM方法考虑了参考传感器和待定标传感器光谱响应和观测几何的差异,但是由于RTM方法会受到所使用的6S模型本身的误差以及输入的大气参数、地表参数测量误差的影响,该方法并不总是优于RM方法。