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).     

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.     

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.     

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.     

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.     

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     

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.     

Cloud-clearing techniques over land for land-surface temperature retrieval from the Advanced Along-Track Scanning Radiometer

We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along-Track Scanning Radiometer (AATSR) instrument and compare these to the standard threshold-based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land-surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8–9% over SADIST (maximum score of 77.93% compared with 69.27%). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3 × 3 pixel domain. We find an increase of 5–7% in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02% compared with 85.69%). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to be provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).     

Inter-satellite calibration linkages for the visible and near-infared channels of the Advanced Very High Resolution Radiometer on the NOAA-7, -9, and -11 spacecraft

The post-launch degradation of the visible (channel 1:≈0· 58–0·68μm) and near-infrared (channel 2: ≈ O·72–1·1 μm) channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA–7, –9, and –11 Polar-orbiting Operational Environmental Satellites (POES) was estimated using the south-eastern part of the Libyan desert as a radiometrically stable calibration target. The relative annual degradation rates, in per cent, for the two channels are, respectively: 3·6 and 4·3 (NOAA–7) 5·9 and 3·5 (NOAA–9); and 1·2 and 2·0 (NOAA–11). Using the relative degradation rates thus determined, in conjunction with absolute calibrations based on congruent path aircraft/satellite radiance measurements over White Sands, New Mexico (U.S.A.), the variation in time of the absolute gain or ‘slope’ of the AVHRR on NOAA–9 was evaluated. Inter-satellite calibration linkages were established, using the AYHRR on NOAA–9 as a normalization standard. Formulae for the calculation of calibrated radiances and albedos (AYHRR usage), based on these interlinkages, are given for the three AYHRRs.     

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.     

The Design of an Inexpensive Very High Resolution Scan Camera System

We describe a system for transforming an off‐the‐shelf flatbed scanner into a $200 scan backend for large format cameras. While we describe both software and hardware aspects, the focus of the paper is on software issues such as color calibration and removal of scanner artifacts. With current scanner technology, the resulting camera system is capable of taking black&white, color, or near‐infrared photographs with up to 490 million pixels. Our analysis shows that we achieve actual optical resolutions close to the theoretical maximum, and that color reproduction is comparable to commercial camera systems. We believe that the camera system described here has many potential applications in image‐based modeling and rendering, cultural heritage projects, and professional digital photography.     

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.     

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.     

高分辨率遥感图像配准并行加速方法

基于SIFT算法的遥感图像配准精度高、稳定性强,但图像幅宽大、提取特征点数量多使得配准过程耗时长。提出了一种高分辨率遥感图像配准的并行加速方法。该方法在特征点提取时利用GPU实现了高斯金字塔建立过程中的并行加速,并对提取出的大量特征点使用共享内存来进行局部极值高速缓存,降低了特征点提取所需的运算时间;同时通过分块处理以及OpenMP多线程技术实现了特征点匹配及仿射模型计算过程的CPU并行处理。实验表明:本方法相对于传统的SIFT算法平均加速3倍,并且对于固定大小的图像,本方法的特征点提取时间和特征点个数具有线性关系,加速比随着提取出特征点数量的增加而增大。     

A generic interface for parallel access to large data sets from HPF applications

A critical performance issue for a number of scientific and engineering applications is the efficient transfer of data to secondary storage. Languages such as High Performance Fortran (HPF) have been introduced to allow programming distributed-memory systems at a relatively high level of abstraction. However, the present version of HPF does not provide appropriate constructs for controlling the parallel I/O capabilities of these systems. In this paper, constructs to specify parallel I/O operations on multidimensional arrays in the context of HPF are proposed. The paper also presents implementation concepts that are based on the HPF compiler VFC and the parallel I/O run-time system Panda. Experimental performance results are discussed in the context of financial management and traffic simulation applications.     

Initial assessment of ATSR-2 data structure for land surface applications

Principal component analysis was used to assess the structure of 1 km spatial resolution data from the second Along Track Scanning Radiometer (ATSR-2). Results indicate that the nadir spectral data have a structure similar to Landsat Thematic Mapper data and could be reduced to two eigenvectors with a loss of under 10 per cent of the total variance. The dual-view spectral data could be reduced to three eigenvectors with a loss of under 12 per cent of the total variance. The thermal data may provide additional information to that contained in the spectral data at some sites. The physical basis of the data structure is interpreted. Thus, ATSR-2 data are of considerable interest for estimating land surface characteristics at a regional scale.     

Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling

This paper presents a spatial Global Sensitivity Analysis (GSA) approach in a 2D shallow water equations based High Resolution (HR) flood model. The aim of a spatial GSA is to produce sensitivity maps which are based on Sobol index estimations. Such an approach allows to rank the effects of uncertain HR topographic data input parameters on flood model output. The influence of the three following parameters has been studied: the measurement error, the level of details of above-ground elements representation and the spatial discretization resolution. To introduce uncertainty, a Probability Density Function and discrete spatial approach have been applied to generate 2,000 DEMs. Based on a 2D urban flood river event modelling, the produced sensitivity maps highlight the major influence of modeller choices compared to HR measurement errors when HR topographic data are used. The spatial variability of the ranking is enhnaced.     

一种用于ADSL的高精度调制器的建模与仿真

要模数转换问题的研究中,介绍了∑-△调制器的过采样和噪声整形技术,为提高转换精度和速率,提出了一个采用四阶级联结构和∑-△调制技术实现高精度的调制器的行为级模型,根据影响建模的各种非理想因素,对各种实际非理想因素(例如开关热噪声、时钟抖动、运放的有限直流增益等)通过优化系统参数之后,可以得到一个用于ADSL设计中的高精度∑-△调制器行为级模型。并在MATLAB下对其仿真验证,结果表明为实际设计提供了依据。调制器在基带带宽1.5MHz、24倍过采样率条件下,系统的信噪比达到87dB,精确度可达14比特。     

Global land monitoring from AVHRR: potential and limitations

Global Vegetation Index ( GVI) time series of visible, near-IR and thermal IR Advanced Very High Resolution Radiometer (AVHRR)weekly composite data with a 015^° spatial resolution collected from NOAA-9 and -11 satellites have been used to develop a prototype global land monitoring system. The system is based on standardized anomalies of the Normalized Difference Vegetation Index (NDVI) and channel 4 brightness temperature ( T₄ )for the period April 1985-September 1994. Processing included: post-launch updated calibration; cloud screening; filling in the cloud induced data gaps by monthly averaging and spatial interpolation; suppressing residual noise by smoothing; calculating 5-year monthly means and standard deviations of NDVI and T₄and their standardized anomalies. The derived anomalies show potential for detecting and interpreting the seasonal cycle and statistically significant interannual variability. Yet, discontinuities and residua! trends can be traced in time series of NDVI and T4. Discontinuities result from the switch from NOAA-9 to NOAA-11 in 1988, and the Mount Pinatubo eruption in 1991. Trends are a combined effect of satellite orbit drift and a possible persistent error in post-launch calibration of solar channels. The orbit drift affects the solar and thermal IR channels through systematic variation of illumination geometry and diurnal heating/cooling of the surface and atmosphere, respectively. Examples are given to illustrate the magnitude of these effects, which reduce the ability to monitor small year-to-year surface changes. The present system yields more accurate results in geographic regions, where atmospheric, angular and diurnal variability effects have a lesser impact on the derived anomalies, i.e. over vegetated areas outside the tropics during local summers. For global-scale monitoring, angular, atmospheric and diurnal variability corrections must be incorporated in the present system.     

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration’s (NASA) Terra and Aqua remote-sensing satellites. The VIIRS will eventually replace Aqua MODIS for both land science and applications and add to the coarse-resolution, long-term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provides critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from the M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties associated with transitioning from using MODIS to VIIRS-based NDVIs. In particular, we compare NDVIs derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily climate modelling grid images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red – NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, and NDVI uncertainties were 0.014, 0.029, and 0.056, respectively, for the 500 m product and 0.013, 0.016, and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02–0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual data sets.