Calibration comparison between SCIAMACHY and MERIS onboard ENVISAT

We present a comparison of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and the Medium Resolution Imaging Spectrometer (MERIS) reflectance calibrations at wavelengths between 442 and 885 nm. Results show that SCIAMACHY underestimates the reflectance by /spl sim/13% at 442 nm reaching up to /spl sim/21% at 885 nm as compared to MERIS. We also find a small nonlinear effect for the lowest reflectance. This effect is more evident for pixels over ocean than over land.     

The Comparison of Spectral Top-of-Atmosphere Reflectances Measured by AATSR, MERIS, and SCIAMACHY Onboard ENVISAT

The top-of-atmosphere reflectance measurements by advanced along-track scanning radiometer (AATSR), medium-resolution imaging spectrometer (MERIS), and scanning imaging absorption spectrometer for atmospheric chartography (SCIAMACHY) onboard ENVISAT have been compared for collocated scenes. The AATSR and MERIS observations were averaged to the scale of a SCIAMACHY ground scene (30 km times 60 km). The SCIAMACHY reflectances were averaged to account for much coarser spectral resolution of AATSR and MERIS observations. It was found that SCIAMACHY reflectances coincide with those of MERIS within 4% MERIS calibration error. This is also the case for AATSR reflectances, except at the wavelength of 0.865 mum, where SCIAMACHY gives, on average, 6% lower reflectances as compared to those of AATSR. They are 3% too low as compared to MERIS observations at this wavelength.     

Calibration of SCIAMACHY Using AATSR Top-of-Atmosphere Reflectance Over a Hurricane

This letter investigates the synergy between the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and the Advanced Along Track Scanning Radiometer (AATSR) onboard the ENVISAT platform for reflectance calibration purposes. This calibration study was mainly performed over a portion of a hurricane corresponding to fully cloudy SCIAMACHY and AATSR pixels. Results show that SCIAMACHY underestimates the top-of-atmosphere (TOA) reflectance by up to 23% (at 870 nm) as compared to AATSR for a nadir viewing geometry. Specifically, considering AATSR calibration as accurate, which is confirmed by comparison with the Medium Resolution Imaging Spectrometer, the SCIAMACHY TOA reflectances should be multiplied by 1.21, 1.19, 1.23, and 1.10 for wavelengths at 550, 670, 870, and 1600 nm, respectively, ahead of satellite retrieval schemes based on the measurements of TOA reflectance     

MERIS and the red-edge position

The Medium Resolution Imaging Spectrometer (MERIS) is a payload component of Envisat-1. MERIS will be operated over land with a standard 15 band setting acquiring images with a 300 m spatial resolution. The red-edge position (REP) is a promising variable for deriving foliar chlorophyll concentration, which plays an important role in ecosystem processes. The objectives of this paper are: (1) to study which factors effect the REP of vegetation, (2) to study whether this REP can be derived from the MERIS standard band setting and (3) to show what REP represents at the scale of MERIS data. Two different data sets were explored for simulating the REP using MERIS bands: (1) simulated data using reflectance models and (2) airborne reflectance spectra of an agricultural area obtained by the airborne visible-infrared imaging spectrometer (AVIRIS). A “linear method”, assuming a straight slope of the reflectance spectrum around the midpoint of the slope, was a robust method for determining the REP and the MERIS bands at 665, 708.75, 753.75 and 778.75 nm could be used for applying the “linear method” for REP estimation. Results of the translation to the scale of MERIS data were very promising for applying MERIS at, for instance, the ecosystem level.     

利用氧气和水汽吸收波段暗像元假设的MERIS影像二类水体大气校正方法

摘 要:MERIS数据以其更为合理的水色波段设置和300m较高的空间分辨率,在内陆湖泊水环境遥感监测中有较大的应用潜力, 对其进行有效的大气校正则是水环境参数定量化反演的前提。以太湖为研究区, 研究基于氧气和水汽吸收波段的暗象元假设, 改进传统的近红外波段暗像元假设的大气校正方法。采用MERIS L2p数据辅助获取湖区气溶胶参数, 并利用2007年11月11日、2008年11月20日以及2009年4月25日三景MERIS影像进行方法验证。结果表明, 该方法能够快速、有效地完成MERIS影像的大气校正, 与地面准同步实测数据相比, 三次校正的RMSP都在25%以下; 与BEAM自带的二类水体大气校正算法、气溶胶厚度辅助的6S大气校正以及改进的暗象元算法进行精度比较, 表明该算法校正精度较高。由于该算法不需要同步实测气溶胶数据, 因此具有一定的适用性。     

The cloud phase discrimination from a satellite

A new technique to identify mixed-phase clouds but also clouds with supercooled water droplets using satellite measurements is proposed. The technique is based on measurements of the backscattered solar light at wavelengths 1.55 and 1.67 /spl mu/m in combination with cloud brightness temperature measurements at 12 /spl mu/m. For the first time, the concept of the phase index-temperature correlation plot (the P-T diagram) is introduced in the cloud remote sensing. Retrievals of cloud temperature and cloud phase index are performed using data from the Advanced Along Track Scanning Radiometer (AATSR) and Scaning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) both onboard the Envisat platform.     

利用MERIS数据植被指数分析福建省植被长势季节变化

监测植被长势动态变化可以提供生态系统状况有价值的信息,可以检测到人类或气候作用引起的变化。本研究利用2004—2005年间10期MERIS影像数据,以福建省为例,探讨MERIS数据在区域植被长势季节变化监测中的应用效果;分析了MERIS数据用于区域植被季节变化监测时的数据处理方法;比较了MERIS数据几种植被指数,提出了利用10和8波段组合改进MERISNDVI的建议;利用多时相合成的NDVI简单分析了2004年夏季—2005年夏季三个季节的植被长势状况。结果表明,MERIS植被指数的时空变化有效反映了气候变化对植被长势的影响。     

A soft-classification-based chlorophyll-a estimation method using MERIS data in the highly turbid and eutrophic Taihu Lake

Soft-classification-based methods for estimating chlorophyll-a concentration (C_chla) by satellite remote sensing have shown great potential in turbid coastal and inland waters. However, one of the most important water color sensors, the MEdium Resolution Imaging Spectrometer (MERIS), has not been applied to the study of turbid or eutrophic lakes. In this study, we developed a new soft-classification-based C_chla estimation method using MERIS data for the highly turbid and eutrophic Taihu Lake. We first developed a decision tree to classify Taihu Lake into three optical water types (OWTs) using MERIS reflectance data, which were quasi-synchronous (±3 h) with in situ measured C_chla data from 91 sample stations. Secondly, we used MERIS reflectance and in situ measured C_chla data in each OWT to calibrate the optimal C_chla estimation model for each OWT. We then developed a soft-classification-based C_chla estimation method, which blends the C_chla estimation results in each OWT by a weighted average, where the weight for each MERIS spectra in each OWT is the reciprocal value of the spectral angle distance between the MERIS spectra and the centroid spectra of the OWT. Finally, the soft-classification based C_chla estimation algorithm was validated and compared with no-classification and hard-classification-based methods by the leave-one-out cross-validation (LOOCV) method. The soft-classification-based method exhibited the best performance, with a correlation coefficient (R²), average relative error (ARE), and root-mean-square error (RMSE) of 0.81, 33.8%, and 7.0 μg/L, respectively. Furthermore, the soft-classification-based method displayed smooth values at the edges of OWT boundaries, which resolved the main problem with the hard-classification-based method. The seasonal and annual variations of C_chla were computed in Taihu Lake from 2003 to 2011, and agreed with the results of previous studies, further indicating the stability of the algorithm. We therefore propose that the soft-classification-based method can be effectively used in Taihu Lake, and that it has the potential for use in other optically-similar turbid and eutrophic lakes, and using spectrally-similar satellite sensors.     

High-Resolution Forecast Models of Water Vapor Over Mountains: Comparison With MERIS and Meteosat Data

Propagation delay due to variable tropospheric water vapor (WV) is one of the most intractable problems for radar interferometry, particularly over mountains. The WV field can be simulated by an atmospheric model, and the difference between the two fields is used to correct the radar interferogram. Here, we report our use of the U.K. Met Office Unified Model in a nested mode to produce high-resolution forecast fields for the 3-km-high Mount Etna volcano. The simulated precipitable-water field is validated against that retrieved from the Medium-Resolution Imaging Spectrometer (MERIS) radiometer on the Envisat satellite, which has a resolution of 300 m. Two case studies, one from winter (November 24, 2004) and one from summer (June 25, 2005), show that the mismatch between the model and the MERIS fields ( rms = 1.1 and 1.6 mm, respectively) is small. One of the main potential sources of error in the models is the timing of the WV field simulation. We show that long-wavelength upper tropospheric troughs of low WV could be identified in both the model output and Meteosat WV imagery for the November 24, 2004 case and used to choose the best time of model output.     

Spatial resolution improvement by merging MERIS-ETM images for coastal water monitoring

The Medium Resolution Imaging Spectrometer (MERIS) launched in March 2002 and has been providing images since June 2002. Before its launch, we had implemented a method to improve its resolution by merging its images with Landsat Enhanced Thematic Mapper images in order to preserve the best characteristics of the two images (spatial, spectral, temporal). We now present the results of this method for real MERIS images (level 1b and 2) in a coastal area. The robustness of the method is studied as well as the influence of the delay between the acquisitions of the two images.     

A satellite cross-calibration experiment

Recently, the Advanced Earth Observing Satellite 2 (ADEOS-2) was launched (December 14, 2002) successfully, and the Global Imager (GLI) onboard the ADEOS-2 satellite became operational in April 2003. In a first calibration checkup, the radiometric performance of GLI was compared relatively to that of other sensors on different satellites with different calibration backgrounds. As a calibration site, a large snowfield near Barrow, Alaska, was used, where space sensors in polar orbits view the same ground target on the same day with small differences in the local crossing times. This is why GLI, the Moderate Resolution Imaging Spectroradiometer (Terra, Aqua), the Sea-viewing Wide Field-of-view Sensor, the Advanced Very High Resolution Radiometer (N16, N17), the Medium Resolution Imaging Spectrometer, and the Advanced Along Track Scanning Radiometer datasets were selected for the following clear-sky condition days: April 14 and 26, 2003. At the same time, ground-truth experiments (e.g., measurements of ground reflectance, bidirectional reflectance distribution function, aerosol optical thickness) were carried out. Thereinafter, top-of-atmosphere (TOA) radiance/reflectance was forward calculated by means of radiative transfer code for each sensor, each band, and each day. Finally, the vicariously retrieved TOA signal was compared to TOA sensor Level 1B data. As a result, GLI's performance is encouraging at that time of the mission. GLI and the other seven sensors deliver similar sensor output in the range of about 5% to 7% around the expected vicariously calculated TOA signal.     

地面成像光谱辐射测量系统及其应用

系统介绍了自主研制的基于制冷面阵CCD地面成像光谱辐射测量系统(field Imaging spectrometer system,FISS)的成像原理,结构设计,主要指标参数和数据处理流程等。利用室内布设的精确标志点和野外测量数据纠正了FISS系统几何畸变;利用自行开发的光谱定标软件对FISS系统进行波长定标,确定了各通道中心波长和全波半高宽;在室内,以积分球为光源,对FISS系统逐波段进行了绝对辐射定标,定标精度优于5%,并建立了各种测量条件下绝对辐射定标系数查找表;最后,利用FISS系统样机进行了大量室内和野外测量实验,并基于获取的部分数据做了作物-杂草识别、近海岸海洋环境试验、牛奶品种识别和植物生化参量反演等研究。研究结果表明,FISS系统能够成功地用于上述领域的研究,并在地质、食品、农业、林业和城市等领域也具有强大的应用潜力。     

Evaluating the capabilities of Sentinel-2 for quantitative estimation of biophysical variables in vegetation

The red edge position (REP) in the vegetation spectral reflectance is a surrogate measure of vegetation chlorophyll content, and hence can be used to monitor the health and function of vegetation. The Multi-Spectral Instrument (MSI) aboard the future ESA Sentinel-2 (S-2) satellite will provide the opportunity for estimation of the REP at much higher spatial resolution (20 m) than has been previously possible with spaceborne sensors such as Medium Resolution Imaging Spectrometer (MERIS) aboard ENVISAT. This study aims to evaluate the potential of S-2 MSI sensor for estimation of canopy chlorophyll content, leaf area index (LAI) and leaf chlorophyll concentration (LCC) using data from multiple field campaigns. Included in the assessed field campaigns are results from SEN3Exp in Barrax, Spain composed of 35 elementary sampling units (ESUs) of LCC and LAI which have been assessed for correlation with simulated MSI data using a CASI airborne imaging spectrometer. Analysis also presents results from SicilyS2EVAL, a campaign consisting of 25 ESUs in Sicily, Italy supported by a simultaneous Specim Aisa-Eagle data acquisition. In addition, these results were compared to outputs from the PROSAIL model for similar values of biophysical variables in the ESUs. The paper in turn assessed the scope of S-2 for retrieval of biophysical variables using these combined datasets through investigating the performance of the relevant Vegetation Indices (VIs) as well as presenting the novel Inverted Red-Edge Chlorophyll Index (IRECI) and Sentinel-2 Red-Edge Position (S2REP). Results indicated significant relationships between both canopy chlorophyll content and LAI for simulated MSI data using IRECI or the Normalised Difference Vegetation Index (NDVI) while S2REP and the MERIS Terrestrial Chlorophyll Index (MTCI) were found to have the strongest correlation for retrieval of LCC.     

MODIS辐照度法定标试验研究

利用内蒙古二连浩特实验场对Terra卫星MODIS传感器开展辐照度基定标方法研究。定标结果表明,辐照度法定标系数和MODIS的星上定标、反射率基法定标系数非常接近,相对差异3.3%,证明辐照度基定标方法正确。定标系数之间的差异说明,漫射辐射与总辐射辐照度比测量的精度对辐照度法结果影响很关键。不同气溶胶模式下得到的结果说明辐照度法可以减小因气溶胶模式的假设产生的误差。     

Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3

Sentinel-2 is planned for launch in 2014 by the European Space Agency and it is equipped with the Multi Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region, which can be used to derive vegetation indices using red-edge bands in their formulation. These are particularly suitable for estimating canopy chlorophyll and nitrogen (N) content. This band setting is important for vegetation studies and is very similar to the ones of the Ocean and Land Colour Instrument (OLCI) on the planned Sentinel-3 satellite and the Medium Resolution Imaging Spectrometer (MERIS) on Envisat, which operated from 2002 to early 2012. This paper focuses on the potential of Sentinel-2 and Sentinel-3 in estimating total crop and grass chlorophyll and N content by studying in situ crop variables and spectroradiometer measurements obtained for four different test sites. In particular, the red-edge chlorophyll index (CI_red-edge), the green chlorophyll index (CI_green) and the MERIS terrestrial chlorophyll index (MTCI) were found to be accurate and linear estimators of canopy chlorophyll and N content and the Sentinel-2 and -3 bands are well positioned for deriving these indices. Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20 m.     

“天绘一号”卫星在轨辐射定标方法

在轨辐射定标包括相对辐射定标和绝对辐射定标, 它是提高遥感数据定量化精度的关键步骤和重要方法。本文阐述了基于均匀场地分区综合的相对辐射定标方法、基于反照率的绝对辐射定标方法及其基本原理, 并首次将其应用于“天绘一号”卫星上的高分辨、多光谱和三线阵相机的辐射定标中。研究结果表明, 相对辐射定标过程去除了卫星图像的条带噪声, 且保存了图像细节;然后, 使用反照率基法, 通过在敦煌场地铺设灰阶靶标, 测量卫星过顶时的地物目标反射率光谱和大气信息, 对“天绘一号”卫星传感器进行了绝对辐射定标;最后, 使用辐射定标结果来反演地物反射率, 与实测的地物反射率相比误差小于5%, 验证了在轨辐射定标系数的有效性。     

卫星光学传感器全过程辐射定标

光学传感器全过程定标,就是对传感器从研发到使命终结整个过程的检测与定标,它包括在传感器研制过程中在实验室利用人工源和室外自然源对其辐射特性进行检测和定标,也包括建立与传感器一起工作的星上定标系统装置,以便当卫星发射升空传感器开始正常工作后,定期地应用星上定标系统对传感器响应的变化进行相对或绝对的定标,全过程定标同时包括在轨运行期间采用基于陆地(或海面)特性的“替代定标”,或借助其他卫星进行的“交叉定标”,最终依据定标结果来确定传感器使命的终结。全过程定标是一个系统实验过程,提高传感器应用效益是其目的,提高定标精度是目标,标准及标准传递是贯穿全过程定标的主线,为此而发展的定标系统和方法是全过程定标的技术支撑,本文作者及其研究室的工作涉及上述全过程的内容,本文首次将全过程定标所涉及的内容系统地予以阐述。提高定标的精度不仅要从系统硬件构成上考虑,如高精度低温绝对辐射计、传递标准探测器、积分球、标准板等,更需要从方法和实验上解决问题,如标准传递过程误差源的分析与控制,大气空间中辐射传输衰减校正模型以及相关的实验等。     

HJ-1B B08 在轨星上定标有效波段宽度计算的查找表法

通过构建适用于HJ-1B 热红外通道(IRSB08)特性的有效波段宽度计算方法, 提高HJ-1B B08 在轨星上绝 对辐射定标的精度。根据HJ-1B 星上定标原理、利用卫星发射前地面实验数据和Planck 方程, 建立基于定标黑体 温度的有效波段宽度计算的查找表法, 结果表明查找表法得到的有效波段宽度为2.01 ?m 左右, 介于半高宽法 1.940 ?m 和矩方法2.394 ?m 之间, 且与定标黑体温度的关联性很小, 在低温点和高温点之间的相对差异在0.3%以 内。半高宽法和矩方法分别低估和高估有效     

光谱角—欧氏距离的高光谱图像辐射归一化

辐射归一化旨在减小不同时相遥感影像间因获取条件不一致而导致的非地表辐射变化的差异,是土地覆盖变化监测的重要前提条件。本文根据高光谱图像上同类地物的谱形及数值的相似性,利用光谱角距离(SAD)和欧氏距离(ED)双重判定选取不变特征点,提出了一种基于光谱角—欧氏距离的辐射归一化方法。在评价指标中除了常用的均方根误差和相对偏差,更增加了高光谱特色的衡量光谱保真性指标:皮尔森系数、光谱扭曲程度。利用高光谱遥感CHRIS图像对本文提出方法进行验证,并与基于多元变化检测(MAD)的辐射归一化方法比较。结果表明,本文方法不仅在辐射特性上优于基于多元变化检测(MAD)的方法,而且具有保持光谱特性的优势,具有较好的应用前景。     

Assessment of satellite ocean color products of MERIS,MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea)

The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance R_rs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APD_m) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr⁻¹, whereas the R_rs(λ) uncertainty at 412 nm is the highest (APD_m 47–62%, RMS 0.0027–0.0041 sr⁻¹). The uncertainties of the aerosol optical thickness (AOT) τ_a, diffuse attenuation coefficient for downward irradiance at 490 nm K_d(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of K_d(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task.