Post-launch calibration of the visible and near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA-14 spacecraft

The post-launch calibration of the visible (channel l:≈0·58–0·68μm) and near-infrared (channel 2: ≈ 0·72–1·1 μm) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft is described. The southeastern part of the Libyan desert (21–23° N latitude; 28–29° E longitude) is used as a radiometrically stable calibration target to determine the ‘slope’—the inverse of the gain—of the AVHRR, expressed in units of W (m^?2 sr^?1 μm^?1 count^?1), in the two channels in the course of 1995. The variation of the ‘slope’ with time during 1995 indicates that channel 1 has degraded at the annual rate of 7·7 per cent; and channel 2 at the rate of 10·5 per cent. Comparison of the AVHRR ‘slopes’ immediately after launch of NOAA-14 with the results of pre-launch calibration performed in September/October 1993 indicates that channel 2 experienced a deterioration of ≈ 18 per cent (relative) immediately after launch while channel 1 was not appreciably affected. Formulae are given for the calculation of the post-launch calibration coefficients for the two channels.     

Revised post-launch calibration of the visible and near-infrared channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft

Records of top-of-the-atmosphere albedo over several sites around the globe indicate that the formulae given in Rao and Chen (1996) to determine the post-launch calibration of the visible (channel 1, 0.58-0.68 mu m) and near-infrared (channel 2, 0.72-1.1 mu m) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft overestimate the in-orbit degradation of the two channels, resulting in spurious upward trends in the albedo time series. Therefore, the calibration formulae have been revised to minimize the upward trends, utilizing a 3-year (1995-1997) record of albedo measurements over a calibration site (21-23 N, 28-29 E) in the southeastern Libyan desert. Formulae for the calculation of the revised calibration coefficients as a function of elapsed time in orbit are given. The revised calibration formulae presented here, and those presented in Rao and Chen (1996), yield radiance/albedo values within 5% (relative) of each other for about 900 days after launch in channel 1 and for about 500 days in channel 2.     

Atmospheric correction of Advanced Very High Resolution Radiometer imagery

The present paper proposes an automated approach to estimate the aerosol reflectance at the Advanced Very High Resolution Radiometer (AVHRR) red channel. The aerosol dominant pixels were separated through two orthogonal transforms. The aerosol reflectance ratio at these pixels was estimated through regression. The results are validated with in situ measurements. The retrieved water-leaving reflectance matched the modelled values with a relative error below 45%. The smallest error values were at the stations with the closest sampling time to image acquisition. However, a weak correlation of 16% was found between water-leaving reflectance and aerosol signals. This suggested that these errors could be attributed to the spatial and temporal variability between the two sampling methods (ship measurement and pixel reflectance).     

Improved calibration coefficients for NOAA-14 AVHRR visible and near-infrared channels

An analysis of the calibration coefficients used to describe sensor degradation in channels 1 and 2 of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft is presented. The radiometrically stable permanent ice sheet of central Antarctica is used as a calibration target to characterize sensor performance. Published calibration coefficients and the coefficients imbedded in the NOAA Level 1b data stream for the period January 1995 to November 1998 are shown to be deficient in correcting for the degradation of the sensor with time since launch. Calibration formulae constructed from NOAA-9 reflectances are used to derive improved calibration coefficients for the AVHRR visible and near-infrared channels for NOAA-14. Channel 1 reflectances for the Greenland ice sheet derived using the new coefficients are consistent with those derived previously using NOAA-9 AVHRR. In addition, improved reference AVHRR channel 2 reflectances for Greenland are derived from NOAA-14 observations. It is recommended that the coefficients derived in this study be used to calibrate reflectances for NOAA-14 AVHRR channels 1 and 2.     

Global data sets for land applications from the Advanced Very High Resolution Radiometer: an introduction

The Advanced Very High Resolution Radiometer (AVHRR) has become one of the most important sensors for monitoring the terrestrial environment at resolutions of 1 km to very coarse resolutions of 15 km and greater. To make these data suitable for scientific and other applications considerable effort has been devoted to the creation of global data sets. Experience has demonstrated that even for a relatively simple sensor such as the AVHRR, the task of creating global data set is fraught with difficulties and that a number of iterations have been necessary despite considerable efforts in the specification of users' requirements

Four types of data processing streams, overlapping in time, have occurred in the creation of global data sets from the AVHRR. The first three data processing streams were all based on the reduced resolution, Global Area Coverage (GAC) data set, which is collected globally every day. In the first data processing stream a much reduced data set was created in the form of the Global Vegetation Index (GVI) product: revised improved versions of the product have been produced. In the second data processing stream an improved product was created by workers at NASA's Goddard Space Flight Center with higher spatial resolution but which until recently has only been available by continent. This has resulted in the creation of a number of regional data sets. In the third data processing stream operational creation of global data sets at moderately coarse resolution (c. 8 km) is being initiated. The most notable example of this data processing stream is part of NASA's Pathfinder project and stems in large part directly from the second data processing stream: it will involved production of a reprocessed improved global data set for the period from 1982 to the present. In the fourth data processing stream the full potential of the AVHRR in terms of its spatial resolution is being realized, through the generation of a global data set at 1 1 km resolution data.     

Improvements in the global biospheric record from the Advanced Very High Resolution Radiometer (AVHRR)

Results are provided of a project to derive improved products from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data record for land investigations. As part of this project, a prototype AVHRR processing system has been developed. This paper describes the different components of this system, which include radiometric in-flight vicarious calibration for the visible and near infrared channels, geometric correction and atmospheric correction as pre-processing steps. The processed data are then stored in a new intermediate data format, which enables flexible compositing approaches. The system generates surface reflectance and vegetation index products as well as new higher order products of reflectance at 3.75 mum and active fires. A comparison of a significant sample of data with widely used precursor AVHRR products is presented to evaluate the processing chain and the improvements it provides.     

A simple,accurate method to compute brightness temperature and/or radiance for the thermal infrared channels of the Advanced Very High Resolution Radiometer (AVHRR)

Users of thermal infrared data from the AVHRR on a NOAA polar-orbiting operational satellite convert the count value output to radiance units, and then assign an equivalent blackbody temperature to the radiance value. Assigning a blackbody temperature to the radiance value is an indirect process, which requires knowledge of the AVHRR spectral response function and a fairly complex calculation. Both difficulties can be avoided by the simple two-step process shown in this Letter. First, blackbody temperature is estimated from a square-root of the measured radiance, then the estimate is refined by values from a ‘universal’ correction curve. The RMS difference between this approximation and the complex calculation is a few hundredths deg K for temperatures in the 200-320 deg K range. The inverse computation, radiance from temperature, is accurate to within 0·01-0·02mWm^?2sr^?1 (cm^?1)^?1. Results are shown for the NOAA-7, -9, -11, and -12 spacecraft.     

Rainfall and vegetation monitoring in the Savanna Zone of the Democratic Republic of Sudan using the NOAA Advanced Very High Resolution Radiometer

NOAA-6 and NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) global-area coverage (4?km ground resolution) data were obtained at three-day intervals throughout each of the four-month periods covering the 1980, 1983 and 1984 growing seasons, between latitudes 10° and 22° North in the Democratic Republic of Sudan. Daily rainfall data for twelve meteorological stations spanning the Savanna Zone were analysed. Rainfall in Sudan during 1980 was below normal, but in 1983 and 1984 there were moderate and severe droughts. The satellite data were used to calculate normalized difference vegetation index (NDVI) values from the visible and near-infrared bands of the satellite data. These were processed into ten-day composite data sets using the AVHRR thermal-infrared channel as a cloud screen and a temporal compositing procedure that reduces cloud contamination and selects viewing angles closest to nadir.

The ten-day composite NDVI values and the integrals of NDVI for each growing season were found to be closely correlated with rainfall. The constants of regressions between NDVI and rainfall were lower in 1983 and 1984 than in 1980, which suggests there was reduced water-use efficiency by the rangeland vegetation in drought years. It was found that July and August NDVI values were closely related to the integrated NDVI values; hence early- and mid-season NDVI data could be used to predict annual primary production. Images showing the geographical distribution of values of NDVI prepared for the three years clearly illustrate the effects of the 1983 and 1984 droughts, compared with the higher rainfall of 1980. The precision of the relationship between rainfall and the vegetation indices for the meteorological stations encourages the view that NOAA AVHRR GAC composite NDVI values can be used to monitor effective rainfall in the Savanna Zone of the Democratic Republic of Sudan     

Calibration of the visible and near-infrared channels of NOAA-11 and -14 AVHRRs by using reflections from molecular atmosphere and stratus cloud

A new method to determine the calibration coefficients for visible and near-infrared channels of Advanced Very High Resolution Radiometer (AVHRR) aboard NOAA satellite is presented and applied to NOAA-11 and -14 spacecrafts. The method uses the reflections from clear-sky ocean and stratus clouds. The clear-sky data analysis gives a minimum estimate of the slope coefficient (albedo per count) for a target month by using radiative transfer theory for molecular atmosphere. Cloudy-sky pixels were precisely excluded from that analysis by using multi-spectral data of AVHRR. Neighbouring pixels of cloud were also excluded to avoid three-dimensional radiative effects such as cloud shadow. On the other hand, the optical thickness (at a visible wavelength) of summer stratus clouds was retrieved from nominally calibrated reflectance of respective visible and near-infrared channels. This analysis was performed to adjust the balance between the two-channels' calibration coefficients because if the two channels were correctly calibrated, the cloud optical thickness retrieved from the two channels must be the same. Finally, the calibration coefficients were determined using iteration.     

Comparison of data from the Scanning Multifrequency Microwave Radiometer (SMMR) with data from the Advanced Very High Resolution Radiometer (AVHRR) for terrestrial environmental monitoring: an overview

Abstract

Comparison between the microwave polarized difference temperature (MPDT) derived from 37 GHz band data and the normalized difference vegetation index (NDVI) derived from near-infrared and red bands, from several empirical investigations are summarized. These indicate the complementary character of the two measures in environmental monitoring. Overall the NDVI is more sensitive to green leaf activity, whereas the MPDT appears also to be related to other elements of the above-ground biomass. Monitoring of hydrological phenomena is carried out much more effectively by the MPDT. Further work is needed to explain spectral and temporal variation in MPDT both through modelling and field experiments.     

Removal of atmospheric effects on a pixel by pixel basis from the thermal infrared data from instruments on satellites. The Advanced Very High Resolution Radiometer (AVHRR)

This paper is concerned with those values of sea-surface temperatures which lie between 270 and 300 K. The thermal infrared (THIR) data under consideration are from the 3-7, II and 12μm channels of the Advanced Very High Resolution Radiometer (AVHRR) instruments on TIROS-N, NOAA-6 and 7 satellites.

Simple relations for calculating the brightness temperatures from the THIR channels of the AVHRR are derived. Algorithms are presented for correcting these brightness temperatures for the non-linear response of the detectors used in the 11 and 12μm channels and for the emissivity of sea-water. Assuming the emissivity of sea-water is equal to 0.98, it is shown that, say, at 290 K. the emissivity corrections are about 0.45, 1.27 and 1.37K, respectively, in the 3.7, 11 and 12 μm channels.

For comparison purpose, we have included a brief account of the atmospheric correction procedure' which is intended to be employed for correcting the thermal infrared data from the European Remote Sensing satellite, ERS-1, in the late 1980s.

Using the standard atmospheric transmittances which were calculated by Phulpin and Deschamps (1980) we have developed a simple procedure for applying atmospheric corrections to the Advanced Very High Resolution Radiometer data using two spectral channels. This atmospheric correction procedure (i) does not require a knowledge of the distribution and abundance of the absorbers, emitters and scatterers in the atmosphere, and (ii) still enables one to evaluate the effective transmittance of the atmosphere which lies within the instantaneous field of view of the remote sensor. This means that one can apply the atmospheric correction on a pixel by pixel basis. An algorithm for the determination of the sea-surface temperature (SST) from the satellite data is presented. This algorithm utilizes the 11 and 12μm channel data from the NOAA-7 satellite. The reliability of this algorithm has been tested.

Comparison of atmospherically corrected SSTs with the simultaneous in situ bulk and point temperature data set (17 points) for relatively cloud-free atmosphere resulted in a bias of 0.63 K and a root mean square difference (r.m.s.d.) of ±0.69 K. When the algorithm for SST determination was corrected for this bias then the r.m.s.d. reduced to ±022 K.     

Calibration of NOAA-7 AVHRR,GOES-5, and GOES-6 VISSR/VAS solar channels

The NOAA-7, GOES-5, and GOES-6 VISSR/VAS solar channels have been calibrated for the periods from October 1983 through January 1985 (NOAA-7, GOES-6) and from October 1983 through July 1984 (GOES-5). Space and the White Sands National Monument area in Mexico, whose reflectance properties are well known, are used as calibration targets. The shortwave reflected terrestrial radiance that is measured at satellite altitude is computed using a fairly accurate radiative transfer model which accounts for multiple scattering and bidirectional effects (Tanré et al., 1979). The relevant atmospheric characteristics are estimated from climatological data (ozone amount, aerosol size-frequency distribution, and refractive index) and observations at the nearest meteorological sites (water vapor amount, visibility). The approach produces accuracies of 8–13% depending on the channel considered. For both types of instruments, no drift in the solar channels in detected during the 15-month period. The gain changes, about 15% of the mean values, are largely attributed to inhomogeneities of the ground target (shading effects due to the presence of dunes). No systematic effect of the normalization procedure applied by NOAA to the raw VISSR/VAS data is detected. There is some evidence that the GOES-5 solar channels gradually deteriorated from March 1984 until the satellite failure in July 1984. Comparisons between gains determined in orbit and those before launch show that the NOAA-7 solar channels read higher by about 15%. The disparities, however, cannot be explained by model errors and must have occurred before the time period analyzed here.     

Assessment of MetOp-A Advanced Very High Resolution Radiometer (AVHRR) short-wave infrared channel measurements using Infrared Atmospheric Sounding Interferometer (IASI) observations and line-by-line radiative transfer model simulations

MetOp-A satellite-based hyper-spectral Infrared Atmospheric Sounding Interferometer (IASI) observations are used to evaluate the accuracy of the broadband short-wave infrared (SWIR) atmospheric window channel (channel 3B) centred at 3.74 μm of the Advanced Very High Resolution Radiometer (AVHRR) carried on the same platform. To complement the partial spectral coverage of IASI, line-by-line radiative transfer model (LBLRTM)-simulated IASI spectra are used. The comparisons result in significant negative AVHRR minus IASI bias in radiance (～–0.04 mW m^–2 sr^–1 cm^–1) with scene temperature dependency in which the absolute value of the bias linearly increases with increasing temperature. It is demonstrated that the negative bias and the scene temperature dependency of the bias are the results of significant absorption in the portion of AVHRR spectral band not seen by IASI, leading to the conclusion that MetOp-A AVHRR channel 3B is not purely an ‘atmospheric window’ channel.     

基于精密星敏感器的航天器高精度姿态测量标定方法

为了解决传统航天器姿态测量方法中存在的误差率高的问题,提出基于精密星敏感器的航天器高精度姿态测量标定方法。首先对使用的精密星敏感器进行设计,并将在不影响航天器运行的前提下安装在合适的位置上。通过建立运动坐标系、坐标参数转换和设置姿态参数三个步骤得出航天器运动模型,在该模型下分析出航天器姿态的基本运动规律、利用精密星敏感器识别并选取航天器空间下的任意三个星点,最后综合定位的星点和航天器姿态的运动规律,从不同的角度上确定航天器姿态测量结果,为了提高航天器姿态测量结果的精度进行标定处理。通过模拟实验分析得出结论：与传统测量方法相比,基于精密星敏感器的航天器高精度姿态测量标定方法的平均误差率降低了6.0%。     

Retrieval of high-resolution sea surface temperature data for Sendai Bay, Japan, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

We studied sea surface temperature (SST) retrieval algorithms for Sendai Bay, using output from the thermal-infrared channels of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on board Terra. While the highest resolutions of other satellite SST products are about 1 km, the ASTER thermal-infrared channels provide 90-m spatial resolution. To develop the ASTER algorithm, we employed statistical methods in which SSTs retrieved from the thermal-infrared measurements were tuned against the Moderate Resolution Imaging Spectroradiometer (MODIS) SST product with a 1-km spatial resolution. Terra also carries a MODIS sensor, which observed the same area as the ASTER sensor at the same time. The MODIS SST was validated around Sendai Bay, revealing a bias of −0.15 °C and root mean-square difference (RMSD) of 0.67 °C against in situ SSTs. Taking into account the spatial-resolution difference between ASTER and MODIS, match-up was generated only if the variability of ASTER brightness temperatures (T₁₃) was small in a pixel of MODIS SST (MP). The T₁₃ within one MP was about 121 pixels. The standard deviation (σ₁₃) of T₁₃ was calculated for each cloud-free MP, and the threshold of σ₁₃ for choosing match-up MPs was decided by analyzing the σ₁₃ histogram of one ASTER image. The 15 synchronous pairs of ASTER/MODIS images are separated into two groups of 8 pairs called set (A) and 7 pairs called set (B). Using the common procedure, the match-ups are generated for set (A) and set (B). The former is used for developing the ASTER Multi-Channel SST (MCSST) algorithm, and the latter for validation of the developed ASTER SST. Analysis of the whole 15 pairs indicated that ASTER SST does not depend on the satellite zenith angle. We concluded that, using Akaike's information criterion with set (A) match-ups, the multiple regression formula with all five thermal-infrared channels was adequate for the ASTER SST retrieval. Validation of ASTER SST using match-up set (B) indicated a bias of 0.101 °C and RMSD of 0.455 °C.     

高解析喷码机嵌入式系统的设计与实现

早期喷码机中,装有Windows操作系统的上位机将处理后的数据传递给下位机,造成喷码机系统庞大复杂,效率低下.对此,采用基于WinCE和ARM9的喷码机系统,选用XJ128按需喷印喷头进行硬件设计.系统将ARM9强大的数据处理能力和WinCE良好的实时性和可剪裁性的优点相结合,集数字图像处理与SPI总线数据传输于一体,通过编写应用程序和分层流式驱动提供喷码机所需信号,大大提高了喷码效率,减小了喷码机的体积,具有较好的实用价值.     

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA's Terra platform

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution, multispectral imager with along-track stereo capabilities scheduled for launch on the first NASA spacecraft of the Earth Observing System (Terra) in 1999. Data will be obtained in 14 spectral bands covering the visible through the thermal infrared wavelength region. A number of standard data products will be available to requesters through an on-line archival and processing system. Particular, user-specified data acquisitions will be possible through a Data Acquisition Request system.     

基于单轴气浮台的航天器运动部件干扰力矩地面标定方法研究

遥感卫星为实现宽视场和高分辨率,一般搭载含可往复转动大惯量成像部件的载荷,然而其转动产生的干扰给卫星姿态控制带来的影响,往往超出载荷成像所必须的姿态稳定度和指向精度要求,卫星平台需要采取措施对干扰力矩进行抑制。但由于加工、装配等原因,载荷干扰力矩与设计值一般均存在差异,给补偿方案设计、参数装订及地面验证置信度等带来不确定性。本文介绍了一种利用单轴气浮台实现航天器运动部件干扰力矩标定的方法,设计试验对该技术在实验室非真空条件下的实现、天地差情况进行说明,并对影响标定结果的误差进行了分析。