Near-nadir observations by the Multispectral Instrument (MSI) onboard the Sentinel-2 and the Operational Land Imager (OLI) onboard Landsat 8 were collected during two Simultaneous Nadir Overpasses (SNO). Multispectral...Near-nadir observations by the Multispectral Instrument (MSI) onboard the Sentinel-2 and the Operational Land Imager (OLI) onboard Landsat 8 were collected during two Simultaneous Nadir Overpasses (SNO). Multispectral images with 10, 20, and 30 m resolution from a spatially uniform area in the Saharan desert were acquired for direct comparison of MSI and OLI Top- Of-Atmosphere (TOA) reflectances. This paper presents an initial radiometric cross-calibration of the 8 corresponding spectral bands of the Sentinel-2 MSI and Landsat 8 OLI sensors. With the well-calibrated Landsat 8 OLI as a reference, the comparison indicates that 6 MSI bands are consistent with OLI within 3% in terms of spectral band adjustment factors Bi . The Near-Infra-Red (NIR) and cirrus bands are exceptions. They yield radiometric differences on the order of 8% and 15% respectively. Cross-calibration results show that the radiometric difference of the 7 corresponding bands are consistent to OLI within 1% or better, except on cirrus band. A pixel-by-pixel match between the MSI and OLI observations for different land covers showed that. This initial study suggests that the red-edge band B8A of MSI can be used to replace the NIR band B08 when conducting vegetation monitoring.展开更多
本文利用6S(Second Simulation of a Satellite Signal in the Solar Spectrum)、Acolite DSF(Dark spectrum fitting)、C2RCC(Case 2 Regional Coast Color)、SeaDas(SeaWiFS Data Analysis System)、Sen2Cor(Sentinel 2 Correction)、...本文利用6S(Second Simulation of a Satellite Signal in the Solar Spectrum)、Acolite DSF(Dark spectrum fitting)、C2RCC(Case 2 Regional Coast Color)、SeaDas(SeaWiFS Data Analysis System)、Sen2Cor(Sentinel 2 Correction)、Polymer(Polynomial based algorithm applied to MERIS)和iCOR(Image correction for atmospheric effects)7种大气校正算法,结合松花湖、月亮泡、小兴凯湖实测遥感反射率数据对“哨兵-2号”(Sentinel-2)数据进行大气校正研究,验证算法性能。整体校正结果显示,相较于实测遥感反射率,上述7种大气校正算法均在可见光波段(400~800 nm)呈现不同程度的低估。除C2RCC算法外,其余6种算法校正后的遥感反射率与实测光谱曲线变化趋势基本吻合,其中Sen2Cor算法与iCOR算法性能最佳,Polymer算法性能最差;在单波段校正精度对比中,Sen2Cor和iCOR算法几乎所有波段的均方根误差和平均绝对百分比误差都低于其余5种算法。Sen2Cor算法在560 nm、665 nm和705 nm处校正精度优于其余6种算法,iCOR算法在443 nm和740 nm处有良好的表现,在490 nm处6S算法校正精度最高,拥有最低的均方根误差(0.0059 sr^(−1))和平均绝对百分比误差(21.40%)。结果表明,这7种大气校正算法均可以在一定程度上去除大气影响,增加影像的可用性,Sen2Cor算法和iCOR算法更适用于本文所研究水体或相似水体。展开更多
文摘Near-nadir observations by the Multispectral Instrument (MSI) onboard the Sentinel-2 and the Operational Land Imager (OLI) onboard Landsat 8 were collected during two Simultaneous Nadir Overpasses (SNO). Multispectral images with 10, 20, and 30 m resolution from a spatially uniform area in the Saharan desert were acquired for direct comparison of MSI and OLI Top- Of-Atmosphere (TOA) reflectances. This paper presents an initial radiometric cross-calibration of the 8 corresponding spectral bands of the Sentinel-2 MSI and Landsat 8 OLI sensors. With the well-calibrated Landsat 8 OLI as a reference, the comparison indicates that 6 MSI bands are consistent with OLI within 3% in terms of spectral band adjustment factors Bi . The Near-Infra-Red (NIR) and cirrus bands are exceptions. They yield radiometric differences on the order of 8% and 15% respectively. Cross-calibration results show that the radiometric difference of the 7 corresponding bands are consistent to OLI within 1% or better, except on cirrus band. A pixel-by-pixel match between the MSI and OLI observations for different land covers showed that. This initial study suggests that the red-edge band B8A of MSI can be used to replace the NIR band B08 when conducting vegetation monitoring.
文摘本文利用6S(Second Simulation of a Satellite Signal in the Solar Spectrum)、Acolite DSF(Dark spectrum fitting)、C2RCC(Case 2 Regional Coast Color)、SeaDas(SeaWiFS Data Analysis System)、Sen2Cor(Sentinel 2 Correction)、Polymer(Polynomial based algorithm applied to MERIS)和iCOR(Image correction for atmospheric effects)7种大气校正算法,结合松花湖、月亮泡、小兴凯湖实测遥感反射率数据对“哨兵-2号”(Sentinel-2)数据进行大气校正研究,验证算法性能。整体校正结果显示,相较于实测遥感反射率,上述7种大气校正算法均在可见光波段(400~800 nm)呈现不同程度的低估。除C2RCC算法外,其余6种算法校正后的遥感反射率与实测光谱曲线变化趋势基本吻合,其中Sen2Cor算法与iCOR算法性能最佳,Polymer算法性能最差;在单波段校正精度对比中,Sen2Cor和iCOR算法几乎所有波段的均方根误差和平均绝对百分比误差都低于其余5种算法。Sen2Cor算法在560 nm、665 nm和705 nm处校正精度优于其余6种算法,iCOR算法在443 nm和740 nm处有良好的表现,在490 nm处6S算法校正精度最高,拥有最低的均方根误差(0.0059 sr^(−1))和平均绝对百分比误差(21.40%)。结果表明,这7种大气校正算法均可以在一定程度上去除大气影响,增加影像的可用性,Sen2Cor算法和iCOR算法更适用于本文所研究水体或相似水体。
