Geometric integration of NOAA AVHRR and SPOT data: low resolutioneffective parameters from high resolution data

Information available from ephemeris data, combined with a few ground control points, is used to carry out the geometric combination of NOAA, AVHRR, and SPOT images by means of orbital models for each satellite. The observation conditions are reconstructed and the areas observed in common determined in the SPOT image pixels and each low-resolution AVHRR pixel. The determination of effective parameters, at low spatial resolution, from high-spatial-resolution data takes into account overlapping effects between adjacent pixels, and pixel size and shape variations with viewing angle for AVHRR data. The method is applied to surface temperature mapping of a selected heterogeneous area by incorporating NOAA AVHRR thermal data in a high-spatial-resolution emissivity map derived from SPOT data     

Directional effects in a daily AVHRR land surface temperature dataset over Africa

Land surface temperature (LST) is a key indicator of the land surface state and can provide information on surface-atmosphere heat and mass fluxes, vegetation water stress, and soil moisture. Split-window algorithms have been used with National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data to estimate instantaneous LST for nearly 20 years. However, the low accuracy of LST retrievals associated with intractable variability has often hindered its wide use. In this study, we developed a six-year daily (day and night) NOAA-14 AVHRR LST dataset over continental Africa. By combining vegetation structural data available in the literature and a geometric optics model, we estimated the fractions of sunlit and shaded endmembers observed by AVHRR for each pixel of each overpass. Although our simplistic approach requires many assumptions (e.g., only four endmember types per scene), we demonstrate through correlation that some of the AVHRR LST variability can be attributed to angular effects imposed by AVHRR orbit and sensor characteristics, in combination with vegetation structure. These angular effects lead to systematic LST biases, including "hot spot" effects when no shadows are observed. For example, a woodland case showed that LST measurements within the "hot-spot" geometry were about 9 K higher than those at other geometries. We describe the general patterns of these biases as a function of tree cover fraction, season, and satellite drift (time past launch). In general, effects are most pronounced over relatively sparse canopies (tree cover <60%), at wet season sun-view angle geometries (principal plane viewing) and early in the satellite lifetime. These results suggest that noise in LST time series may be strongly reduced for some locations and years, and that long-term LST climate data records should be normalized to a single sun-view geometry, if possible. However, much work remains before these can be accomplished.     

Adjusting for Long-Term Anomalous Trends in NOAA's Global Vegetation Index Data Sets

The weekly 0.144 resolution global vegetation index from the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) has a long history, starting late 1981, and has included data derived from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard NOAA-7, -9, -11, -14, -16, -17, and -18 satellites. Even after postlaunch calibration and mathematical smoothing and filtering of the normalized difference vegetation index (NDVI) derived from AVHRR visible and near-infrared channels, the time series of global smoothed NDVI (SMN) still has apparent discontinuities and biases due to sensor degradation, orbital drift [equator crossing time (ECT)], and differences from instrument to instrument in band response functions. To meet the needs of the operational weather and climate modeling and monitoring community for a stable long-term global NDVI data set, we investigated adjustments to substantially reduce the bias of the weekly global SMN series by simple and efficient algorithms that require a minimum number of assumptions about the statistical properties of the interannual global vegetation changes. Of the algorithms tested, we found the adjusted cumulative distribution function (ACDF) method to be a well-balanced approach that effectively eliminated most of the long-term global-scale interannual trend of AVHRR NDVI. Improvements to the global and regional NDVI data stability have been demonstrated by the results of ACDF-adjusted data set evaluated at a global scale, on major land classes, with relevance to satellite ECT, at major continental regions, and at regional drought detection applications.     

Atmospheric corrections in the thermal infrared: global and watervapor dependent split-window algorithms-applications to ATSR and AVHRRdata

The split-window method is an appropriate way to perform atmospheric corrections of satellite brightness temperatures in order to retrieve the surface temperature. A climatological data set of 1761 different radio soundings, the TIGR database, has been used to develop two different split-window methods. A global quadratic (QUAD) method, with global coefficients to be applied on a worldwide scale, and a water vapor dependent (WVD) algorithm. The first method includes a quadratic term in the split-window equation that roughly accounts for the water vapor amount. The other method explicitly includes the water vapor amount in each split-window coefficient. When applied to the 1761 radio soundings, the latter method gives better results than the global one, especially when the surface emissivity is far from unity (0.95 or less) and when the water vapor reaches great values. Both algorithms have been tested on ATSR/ERSI and AVHRR/NOAA data over sea pixels. The QUAD algorithm gives correct results for simulations (the standard error is 0.2 K) and experimental data (the bias ranges from -0.1 to 0.4 K). The WVD algorithm appears to be more accurate for both simulations (the standard error is less than 0.1 K) and AVHRR experimental data when climatological water vapor contents are used (the bias ranges from -0.2 to 0.1 K)     

An Efficient Contextual Algorithm to Detect Subsurface Fires With NOAA/AVHRR Data

This paper deals with the potential application of National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) data to detect subsurface fire (subsurface hotspots) by proposing an efficient contextual algorithm. Most of the solutions proposed to date are mainly focused on the problem of surface fires, and very few research works have been performed to develop techniques for the subsurface fire problem. Although few algorithms based on the fixed-thresholding approach have been proposed for subsurface hotspot detection, however, for each application, thresholds have to be specifically tuned to cope with unique environmental conditions. The main objective of this paper is to develop an instrument-independent adaptive method by which direct threshold or multithreshold can be avoided. The proposed contextual algorithm is very helpful to monitor subsurface hotspots with operational satellite data, such as the Jharia region of India, without making any region-specific guess in thresholding. Novelty of the proposed work lies in the fact that once the algorithmic model is developed for the particular region of interest after optimizing the model parameters, there is no need to optimize those parameters again for further satellite images. Hence, the developed model can be used for optimized automated detection and monitoring of subsurface hotspots for future images of the particular region of interest. The algorithm is adaptive in nature and uses vegetation index and different NOAA/AVHRR channel's statistics to detect hotspots in the region of interest. The performance of the algorithm is assessed in terms of sensitivity and specificity and compared with other well-known thresholding techniques such as Otsu's thresholding, entropy-based thresholding, and existing contextual algorithm proposed by Flasse and Ceccato. The proposed algorithm is found to give better hotspot detection accuracy with lesser false alarm rate.     

Retrieval of cloud base heights from passive microwave and cloudtop temperature data

Water vapor profiling algorithms that treat liquid clouds explicitly yield a cloud base height as a byproduct. A single case of a water vapor profile retrieval using a combination of the SSM/T-2 on the DMSP satellite and cloud parameters from the AVHRR on the NOAA satellite retrieved a reasonable cloud base. While hardly definitive, this case is suggestive. The authors examine the cloud base signal in a combination of the SSM/1 and SSM/T-2 on the DMSP satellite from a theoretical point of view. It is shown that the signal is strong enough for a useful retrieval only over the ocean. For low altitudes, a cloud top temperature (CTT) constraint, as could be provided from an infrared radiometer, is required. While difficult with the DMSP-NOAA satellite combination, this has become much easier with the recent launch of NOAA-K with the AMSU-B and AVHRR. It is shown that the signal is acceptable over the relevant range of cloud liquid water content values. To achieve useful results, some local tuning of the algorithm will be necessary. This tuning could take the form of water vapor profile covariance matrices, climatological estimates of the cloud liquid water density, or purely empirical methods. Broken and multilayer clouds provide additional complications to the problem     

Improved cost effectiveness for new satellite systems

Concepts of reliability, life and earning power are applied in a new way to measure the cost effectiveness and depreciation of satellite systems in view of requirement versus capability.The operational reliability of Telesat's present satellite systems is evaluated against the early assumptions of constant failure rates. New realistic reliability wearout models are developed and result in reliability predictions that correlate well with operational data.Optimization and selection of cost effective configurations for new increased capability satellite systems are achieved by a series of tradeoffs using the new reliability wearout models. The new systems show a substantial improvement in the level of cost effectiveness optimization over a substantially longer life in comparison with the present systems. The depreciation of the new systems is also shown to be more uniformly distributed over longer life.     

应用无人机实现地面无线传感器网络通信中继的探讨

提出了应用无人机实现地面无线传感器网络远程通信中继的方案,对方案的可行性进行了分析,通过与卫星中继、有人机中继的比较具体论述了无人机通信中继的必要性和优越性。分析了系统的总体结构和作战信息链路,对整个系统的关键技术即数据融合技术和数据链技术进行了探讨,并针对战场应用提出了相关的设想,为应用无人机进行战场通信中继的预先研究奠定了基础。     

Combining Airborne Photographs and Spaceborne SAR Data to Monitor Temperate Glaciers: Potentials and Limits

Monitoring temperate glacier activity has become more and more necessary for economical and security reasons and as an indicator of the local effects of global climate change. Remote sensing data provide useful information on such complex geophysical objects, but they require specific processing techniques to cope with the difficult context of moving and changing features in high-relief areas. This paper presents the first results of a project involving four laboratories developing and combining specific methods to extract information from optical and synthetic aperture radar (SAR) data. Two different information sources are processed, namely: 1) airborne photography and 2) spaceborne C-band SAR interferometry. The difficulties and limitations of their processing in the context of Alpine glaciers are discussed and illustrated on two glaciers located in the Mont-Blanc area. The results obtained by aerial triangulation techniques provide digital terrain models with an accuracy that is better than 30 cm, which is compatible with the computation of volume balance and useful for precise georeferencing and slope measurement updating. The results obtained by SAR differential interferometry using European Remote Sensing Satellite images show that it is possible to measure temperate glacier surface velocity fields from October to April in one-day interferograms with approximately 20-m ground sampling. This allows to derive ice surface strain rate fields required to model the glacier flow. These different measurements are complementary to results obtained during the summer from satellite optical data and ground measurements that are available only in few accessible points     

A recurrent neural network classifier for improved retrievals ofareal extent of snow cover

Accurate detection of areal extent of snow in mountainous regions is important. Areal extent of snow is a useful climatic indicator. Moreover, snow melt is a major source of water supply for many arid regions (e.g., western United States, Morocco) and affects regional ecosystems. Unfortunately, accurate satellite retrievals of areal extent of snow have been difficult to achieve. Two approaches to effectively and accurately detect clear land, cloud, and areal extent of snow in satellite data are developed. A feed-forward neural network (FFNN) is used to classify individual images, and a recurrent NN is used to classify sequences of images. The continuous outputs of the NN, combined with a linear mixing model, provide support for mixed-pixel classification. Validation with independent in situ data confirms the classification accuracy (94% for feed-forward NN, 97% for recurrent NN). The combination of rapid temporal sampling (e.g., GOES) and a recurrent NN classifier is recommended (relative to an isolated scene (e.g., AVHRR) and a feed-forward NN classifier)     

The Systems Reliability Service and Its Generic Techniques

The formation of the Systems Reliability Service (SRS) is discussed against a background of historical reliability development. This background extends to nearly twenty years ago when various methods of carrying out safety assessments of nuclear plant and systems were being formulated. The early deterministic methods relying to a great extent on subjective judgement have been developed into more generalised techniques involving probabilistic concepts. Subsequently, reliability assessments were extended to cover not just safety but also availability aspects. Earlier developed theoretical foundation gave rise to reliability technology. In order to apply this technology successfully, it has been found necessary to organise under one management multi-disciplinary groups covering computation and analysis, project assessment, research and development, and a wide ranging reliability data bank. The basic operation of the data bank is discussed as well as general applications of SRS techniques. These techniques, although developed primarily for nuclear plants, have also been found useful in their applications to non-nuclear plants and to systems in general.     

On-Orbit Calibration Assessment of AVHRR Longwave Channels on MetOp-A Using IASI

Accurate and precise satellite radiance measurements are important for data assimilations in numerical weather prediction models and for climate-change detection. After the successful launch of the Infrared Atmospheric Sounding Interferometer (IASI), several studies have indicated that the IASI radiance measurements are well calibrated and maintain superb spectral and radiometric calibration accuracy. Owing to its hyperspectral nature and high-quality measurements, the IASI radiance can serve as a relative reference to independently assess the radiance measurements of broad- or narrow-band instruments that share the same spectral region. In this paper, we demonstrate the utility of the IASI radiances to evaluate the Advanced Very High Resolution Radiometer (AVHRR) infrared (IR) channel measurements. The coregistered AVHRR pixels inside each IASI pixel are averaged spatially. We then compared the spatially averaged radiance from AVHRR IR channels with IASI by convolving the IASI-measured spectra with the AVHRR spectral response functions. It was found that, statistically, the temperature observed from AVHRR channels 4 and 5 is slightly warmer than that in IASI for the brightness temperature (BT) range of 200 K–300 K. The mean BT difference (IASI minus AVHRR) is less than 0.4 K with a standard deviation of $ sim$0.3 K for AVHRR channels 4 and 5. The BT difference between IASI and AVHRR IR channels is scene-temperature dependent for both channels 4 and 5, which is probably caused by the nonlinearity of the AVHRR detectors. Both AVHRR channels 4 and 5 show slight scan-dependent bias with maximum differences of approximately $sim$0.2 K (with AVHRR being warmer than IASI) at both ends of the scan.      

IPv6 networks over DVB‐RCS satellite systems

Satellite plays an important role in global information infrastructure (GII) and next generation networks (NGNs). Similarly, satellite communication systems have great advantages to support IPv6 (Internet Protocol version 6) networks as a technology that allows universal access to broadband e‐services (audio, video, VPN, etc.). In the context of DVB‐S2 (digital video broadcast‐satellite) and DVB‐RCS (digital video broadcast‐return channel via satellite) standards, this paper presents the current SatSix project (satellite‐based communications systems within IPv6 networks) within the European 6th Framework Programme, which is implementing innovative concepts and effective solutions (in relation with the economical cost) for broadband satellite systems and services using the technology presented above. This project is promoting the introduction of the IPv6 protocol into satellite‐based communication systems. Moreover, through SatSix, the industry is addressing the next generation Internet, IPv6. It also enhances its competitive position in satellite broadband multimedia systems by exploiting the common components defined by the European DVB‐S2 and DVB‐RCS satellite broadband standards. Copyright © 2007 John Wiley & Sons, Ltd.     

Higher resolution Earth surface features from repeat moderateresolution satellite imagery

This paper demonstrates that a high-resolution reflectivity model used in conjunction with an instrument pointspread function (PSF) can both determine georegistration parameters of coarse resolution sensors and improve the spatial resolution by compositing noncoincident repeat satellite data. To demonstrate this ability, an ideal location is selected and several first principle assumptions are made to simplify the reflectivity model. Twenty-three 1-km advanced very high-resolution radiometer (AVHRR) images are composited by using a Bayesian statistical sampling technique to yield estimates of a simple terrain-based reflectivity model with 180-m resolution. The terrain values are determined from a 90-m resolution digital elevation model (DEM). The Bayesian technique uses the AVHRR data to iteratively determine the most likely values for the model spectral albedos contained within an AVHRR field of view. Model predicted radiances for the repeat AVHRR footprints are computed by integrating model albedo values over the AVHRR PSF. As a first-order verification, simulated AVHRR reflectivities are shown to reconstruct well a smoothly varying prescribed albedo field. Comparisons of the composited real AVHRR image result with Landsat Multi Spectral Scanner (MSS) data show that the model reconstruction resolves surface features, which are not resolved in a single AVHRR image     

遥感卫星"夸父A"星地通信接收站布局建模与分析

面向实时接收遥感卫星"夸父A"连续对日观测数据的应用需求,提出"夸父A"卫星与地面单个固定接收站相对位置模型,在此基础上定量评估现有国内及海外站的接收效率,并进一步提出地面接收站全球布局的基本原则及其可行的优化方案.研究成果将为"夸父"计划星地数据通信系统的实施提供重要的技术参考.     

Retrieval of Atmospheric Integrated Water Vapor and Cloud Liquid Water Content Over the Ocean From Satellite Data Using the 1-D-Var Ice Cloud Microphysics Data Assimilation System (IMDAS)

Reliable prediction of precipitation by numerical weather prediction (NWP) models depends on the appropriate representation of cloud microphysical processes and accurate initial conditions of observations of atmospheric variables. Therefore, to retrieve reasonable cloud distributions, a 1-D variational Ice Cloud Microphysics Data Assimilation System (IMDAS) is developed to improve the predictability of NWP models. The general framework of IMDAS includes the Lin ice cloud microphysics scheme as a model operator, a four-stream fast microwave radiative transfer model in the atmosphere as an observation operator, and a global minimization method that is known as the shuffled complex evolution. IMDAS assimilates the satellite microwave radiometer data set of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and retrieves integrated water vapor and integrated cloud liquid water content. This new method successfully introduces heterogeneity into the initial state of the atmosphere, and the modeled microwave brightness temperatures agree well with the observations of the Wakasa Bay Experiment 2003 in Japan. It has significantly improved the performance of the cloud microphysics scheme by the intrusion of heterogeneity into the external global reanalysis data, which resultantly improved atmospheric initial conditions.     

Algorithm for NO/sub 2/ vertical column retrieval from the ozone monitoring instrument

We describe the operational algorithm for the retrieval of stratospheric, tropospheric, and total column densities of nitrogen dioxide (NO/sub 2/) from earthshine radiances measured by the Ozone Monitoring Instrument (OMI), aboard the EOS-Aura satellite. The algorithm uses the DOAS method for the retrieval of slant column NO/sub 2/ densities. Air mass factors (AMFs) calculated from a stratospheric NO/sub 2/ profile are used to make initial estimates of the vertical column density. Using data collected over a 24-h period, a smooth estimate of the global stratospheric field is constructed. Where the initial vertical column densities exceed the estimated stratospheric field, we infer the presence of tropospheric NO/sub 2/, and recalculate the vertical column density (VCD) using an AMF calculated from an assumed tropospheric NO/sub 2/ profile. The parameters that control the operational algorithm were selected with the aid of a set of data assembled from stratospheric and tropospheric chemical transport models. We apply the optimized algorithm to OMI data and present global maps of NO/sub 2/ VCDs for the first time.     

Impact of variable atmospheric water vapor content on AVHRR datacorrections over land

This paper explores the impact of the integrated water vapor content (IWV) in the atmospheric column on the corrections of optical satellite data over land. First, simulation runs were used to quantify the trends in red and near infrared parts of the electromagnetic spectrum. Second, advanced very high resolution radiometer (AVHRR) measurements obtained over Canada during the 1996 growing season, together with reanalyzed IWV content data, were employed to determine the actual impact of constant IWV values. Third, various options in characterizing IWV for atmospheric corrections of AVHRR composites were examined. It was found that (1) as expected, IWV affects near-infrared radiation substantially more than red, although the latter is also altered; (2) that additional, subtle interactions take place between IWV, radiance levels, and viewing geometry that influence the retrieved surface reflectance; (3) that spatial and temporal variation in IWV caused changes in the normalized difference vegetation index up to 7.5% in relative terms during the peak green period; and (4) that IWV varies so substantially that pixel and date-specific values need to be used for the atmospheric correction of AVHRR data. At present, subdaily gridded IWV data sets from atmospheric data reanalysis projects are the only candidate source for such purpose     

A Web-based TelePACS using an asymmetric satellite system

We have developed a WWW-based TelePACS that can access every permitted PACS server via the Internet. Java programming techniques were used to implement the system, which can access and retrieve medical information and images through Web browsers such as netscape without specific tools. We also have developed a consolidator that performs as a manager to connect a conventional PACS server to a Web-based TelePACS server. We have developed the asymmetric satellite data communication system (ASDCS) as a fast communication system. The ASDCS uses a receive-only satellite link for data delivery and a terrestrial network for control communication. In conclusion, we were able to develop a cost-effective and fast PACS using Web technology. Web technology expanded the scope of use for a dedicated PACS from intrahospital to public use