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1.
This letter is aimed at better understanding of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) reflectance radiometric calibration errors using the Medium Resolution Imaging Spectrometer (MERIS) onboard ENVISAT. Earlier investigations showed that the SCIAMACHY calibration error can reach 20% in the visible bands, which prevents aerosol retrievals using the SCIAMACHY data. Recent improvements of the SCIAMACHY calibration are discussed. It is found that the differences in reflectances for the wavelengths 443, 560, 665, 754, and 865 nm between MERIS and improved Processor 6 SCIAMACHY data are close to the MERIS radiometric calibration error, which is below 4%  相似文献   

2.
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  相似文献   

3.
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.  相似文献   

4.
MERIS and the red-edge position   总被引：1，自引：0，他引：1  
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.  相似文献   

5.
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.  相似文献   

6.
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.  相似文献   

7.
The Airborne Reflective/Emissive Spectrometer is specified as a whisk-broom imaging spectrometer for remote sensing of land surfaces covering the wavelength regions 0.47-2.45 /spl mu/m and 8-12 /spl mu/m with 160 spectral bands. The instrument is being built by Integrated Spectronics, financed by the German Aerospace Agency (DLR) and the GeoResearch Centre Potsdam (GFZ) and will be available to the scientific community from end 2005 on. The spectroradiometric design is based on scientific requirements derived from three main application scenarios comprising vegetation, soil, and mineral sciences. Two of these are described in this letter. Measured or modeled reflectance spectra are input to a simulation model that calculates at-sensor radiance spectra, resamples them with the channel-specific response functions, adds different amounts of noise in the radiance domain, and performs a retrieval to get the corresponding noisy surface reflectance spectra. The retrieval results as a function of the sensor noise level are compared with the accuracy requirements imposed by the different application fields taking into account the technical boundary conditions. The final specifications account for the most demanding requirements of the three application fields: a spectral sampling distance of 13-14 nm in the 470-1800 nm region, and 12 nm in the 2000-2450-nm region. The required noise-equivalent radiances are 5, 3, and 2 nW/spl middot/cm/sup -2//spl middot/sr/sup -1//spl middot/nm/sup -1/ for the spectral regions 470-1000, 1000-1800, and 2000-2450 nm, respectively.  相似文献   

8.
利用MERIS数据植被指数分析福建省植被长势季节变化   总被引：1，自引：0，他引：1  
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。  相似文献   

9.
Soft-classification-based methods for estimating chlorophyll-a concentration (Cchla) 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 Cchla 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 Cchla data from 91 sample stations. Secondly, we used MERIS reflectance and in situ measured Cchla data in each OWT to calibrate the optimal Cchla estimation model for each OWT. We then developed a soft-classification-based Cchla estimation method, which blends the Cchla 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 Cchla 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 Cchla 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.  相似文献   

10.
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 Rrs(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 (APDm) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr−1, whereas the Rrs(λ) uncertainty at 412 nm is the highest (APDm 47–62%, RMS 0.0027–0.0041 sr−1). The uncertainties of the aerosol optical thickness (AOT) τa, diffuse attenuation coefficient for downward irradiance at 490 nm Kd(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 Kd(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.  相似文献   

11.
针对实现卫星对地观测的自适应多模态,需要根据先验判定卫星成像区域内地表覆盖类型及其反射率状况建立与太阳光照条件、地表覆盖类型、反射率相关的成像载荷积分时间、不同压缩比的成像参数设置模型,以选择最优的观测模式的问题,该文以中分辨率成像光谱仪(MERIS)地表反射率影像和GlobCover全球陆地覆盖分类图为数据源,建立了地表覆盖分类图及其反射率影像矢量化处理的技术流程,构建了以冰雪、沙漠、裸土、岩石、农作物、森林、草地、水体等不同地表覆盖类型及其在不同季节蓝、绿、红、近红外波段的地物反射率数据库。以此作为遥感卫星成像任务规划的技术支撑,构建自适应选择最优的观测模式,提升遥感图像的质量。  相似文献   

12.
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.  相似文献   

13.
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。  相似文献   

14.
Particulate organic carbon (POC) plays an important role in the carbon cycle in water due to its biological pump process. In the open ocean, algorithms can accurately estimate the surface POC concentration. However, no suitable POC-estimation algorithm based on MERIS bands is available for inland turbid eutrophic water. A total of 228 field samples were collected from Lake Taihu in different seasons between 2013 and 2015. At each site, the optical parameters and water quality were analyzed. Using in situ data, it was found that POC-estimation algorithms developed for the open ocean and coastal waters using remote sensing reflectance were not suitable for inland turbid eutrophic water. The organic suspended matter (OSM) concentration was found to be the best indicator of the POC concentration, and POC has an exponential relationship with the OSM concentration. Through an analysis of the POC concentration and optical parameters, it was found that the absorption peak of total suspended matter (TSM) at 665 nm was the optimum parameter to estimate POC. As a result, MERIS band 7, MERIS band 10 and MERIS band 12 were used to derive the absorption coefficient of TSM at 665 nm, and then, a semi-analytical algorithm was used to estimate the POC concentration for inland turbid eutrophic water. An accuracy assessment showed that the developed semi-analytical algorithm could be successfully applied with a MAPE of 31.82% and RMSE of 2.68 mg/L. The developed algorithm was successfully applied to a MERIS image, and two full-resolution MERIS images, acquired on August 13, 2010, and December 7, 2010, were used to map the POC spatial distribution in Lake Taihu in summer and winter.  相似文献   

15.
Three artificial neural network (ANN) processors available as plug-in modules for the Basic ERS & ENVISAT (A)ATSR and MERIS Toolbox (BEAM) were validated in Lake Taihu, China. Mean deviations of reflectance derived from Lakes\Boreal and Lakes\Eutrophic were 10-90%, while reflectance from the FUB-WeW processor showed larger errors. All processors showed underestimates of chlorophyll a (Chl-a), total suspended matter (TSM), and phytoplankton pigment absorption, while particulate scattering values were severely overestimated. None of the readily available MERIS processors is currently able to separate atmospheric and water-leaving radiance over Lake Taihu, while the retrieval of phytoplankton biomass through ANN processors shows promise.  相似文献   

16.
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.  相似文献   

17.
航天高光谱遥感器CHRIS的水体图像大气校正   总被引：2，自引：0，他引：2  
CHRIS(Compact High Resolution Imaging Spectrometer)是欧空局于2001年10月发射的PROBA-1卫星上搭载的探索性高光谱遥感器,它具备高空间分辨率、多角度观测、高光谱成像等特点,为水质遥感监测提供不可多得的数据源。基于卫星遥感图像定量监测水质,一个关键步骤就是进行精确的大气校正,提取水面反射率。相比陆地遥感图像,水面反射率是弱信号,对大气校正的要求更高。6S(Second Simulation of SatelliteSignal in the Solar Spectrum)和MODTRAN(MOderate resolution TRANsmittance code)是两种常用的大气辐射传输模型。本文选取基于6S的REMS(Remote Sensing Environmental Monitoring System)和基于MODT-RAN的ACORN(Atmospheric CORrection Now)两种大气校正软件,对太湖梅梁湾的三景不同成像角度CHRIS图像进行大气校正,将大气校正后的图像水体反射率与地面同步实测水体反射率进行比较分析。结果表明,经过大气校正的CHRIS图像得到的水面反射率与实测反射率波形十分地接近,在全部波长范围内的相关系数达到90%。分析实测的水体反射率角度特征,发现图像的角度特征更明显。三个观测角度下反射率之间的各差值都呈现出在绿光波段较大,在红光和近红外波段偏小的特点,这和实测结果相符。ACORN校正后的图像的角度特征更好地与实测结果吻合。  相似文献   

18.
There is an increased trend toward quantitative estimation of land surface variables from hyperspectral remote sensing. One challenging issue is retrieving surface reflectance spectra from observed radiance through atmospheric correction, most methods for which are intended to correct water vapor and other absorbing gases. In this letter, methods for correcting both aerosols and water vapor are explored. We first apply the cluster matching technique developed earlier for Landsat-7 ETM+ imagery to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, then improve its aerosol estimation and incorporate a new method for estimating column water vapor content using the neural network technique. The improved algorithm is then used to correct Hyperion imagery. Case studies using AVIRIS and Hyperion images demonstrate that both the original and improved methods are very effective to remove heterogeneous atmospheric effects and recover surface reflectance spectra.  相似文献   

19.
The effect of natural variation of raindrop size distribution (DSD)on the retrieval of rainfall rate from the dual-frequency (13.6/35.5 GHz,as will be in the Global Precipitation Measurement Mission) Precipitation Radar (DPR) measurements is studied by utilizing a large set of disdrometer-measured DSD data through a simple simulation framework. A DPR inversion technique(DPR-IT) that focuses on the retrieval of DSD information from the non-Rayleigh backscattering characteristic of the hydrometeors and a conventional DPR technique(DPR-CT) that focuses on the independent retrieval of rainfall rate from the attenuation measurement are considered in this analysis. The preliminary results show that at different rainfall rate regions these methods have different responses to the DSD variability. For instance, it appears that DPR-IT suffers relatively less from the DSD variability in the regions of weak to moderate rainfall rate (/spl bsol/ mm /spl middot/ h/sup -1/),while in the strong rainfall rate (>/spl sim/10 mm /spl middot/ h/sup -1/) region the DPR-CT generally has less sensitivity to DSD variations than the DPR-IT.  相似文献   

20.
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.  相似文献   

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