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检索条件"任意字段=Conference on Atmospheric and Environmental Remote Sensing Data Processing and Utilization"

共 354 条记录，以下是91-100 订阅

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On the darkest pixel atmospheric correction algorithm: A revised procedure applied over satellite remotely sensed images intended for environmental applications

On the darkest pixel atmospheric correction algorithm: A rev...

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conference on remote sensing for environmental Monitoring, GIS Applications and Geology III

作者： Hadjimitsis, DG Clayton, C Retalis, A Univ Southampton Dept Civil & Environm Engn Southampton SO17 1BJ Hants England

ISBN: (纸本)0819451223

atmospheric correction is an essential part of the pre-processing of satellite remote sensing data. Several atmospheric correction approaches can be found in the literature ranging from simple to sophisticated methods. The sophisticated methods require auxiliary data, however the simple methods are based only on the image itself and are served to be suitable for operational use. One of the most widely used and well-known simple atmospheric correction methods is the darkest pixel (DP). Despite of its simplicity, the user must be aware of several key points in order to avoid any erroneous results. Indeed, this paper addresses a new strategy for selecting the suitable dark object based on the proposed analysis of digital number histograms and image examination. Several case studies, in which satellite remotely sensed image data intended for environmental applications have been atmospherically corrected using the DP method, are presented in this article.

关键词： darkest pixel histogram minimum value atmospheric correction satellite remote sensing

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Distributed real-time operational products from AIRS

Distributed real-time operational products from AIRS

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Goldberg, MD Barnet, CD Wolf, W Zhou, L Divakarla, M NOAA NESDIS Off Res & Applicat Camp Springs MD USA

ISBN: (纸本)0819454869

Since October, 2002, NESDIS has provided specially tailored radiance and retrieval products derived from Aqua AIRS and AMSU-A observations operationally (24 hours x 7 days) to a number of Numerical Weather Prediction (NWP) centers, including NCEP, ECMWF and the UK Met. Office. Two types of products are available - thinned radiance data and full resolution retrieval products consisting of atmospheric temperature, moisture and ozone as well as surface parameters of temperature and emissivity. The radiances are thinned because of current limitations in communication bandwidth and computational resources at NWP centers. There are two types of thinning: a) spatial and spectral thinning, and b) data compression using principal component analysis (PCA). PCA is used for a) reconstructing radiances with the properties of reduced noise, b) independent instrument noise estimation, c) quality control, and d) deriving the retrieval first guess used in the AIRS processing software. The radiance products also include cloud cleared radiances. The cloud clearing procedure remove the effect of cloud contamination in partial overcast conditions and have been demonstrated to increase the amount of data that can be treated as clear from 5% to 50%. The AIRS temperature and moisture retrieval are significantly more accurate than AMSU-only retrievals in clear, cloud contaminated and cloud-cleared conditions. Most NWP centers are currently assimilating clear radiances, which we believe severely limits the impact of AIRS data. Fortunately, results presented in this paper have stimulated new upcoming experiments to test the impact of cloud-cleared radiances.

关键词： Clouds Principal component analysis Contamination data modeling MODIS data centers Infrared radiation Ozone Spectral resolution Microwave radiation

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A modeling approach for aerosol optical depth analysis during forest fire events

A modeling approach for aerosol optical depth analysis durin...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Aubé, M O'Neill, NT Royer, A Lavoué, D Univ Sherbrooke CARTEL Sherbrooke PQ J1K 2R1 Canada

ISBN: (纸本)0819454869

Measurements of aerosol optical depth (AOD) are important indicators of aerosol particle behavior. Up to now the two standard techniques used for retrieving AOD are;(i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as DDV (Dense Dark Vegetation) based inversion algorithms which yield AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new assimilation methodology that links AOD measurements and the predictions of a particulate matter Transport Model. This modelling package (AODSEM V2.0 for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution may be tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important and robust parameter. We applied this methodology to a significant smoke event that occurred over the eastern part of North America in July 2002.

关键词： aerosol optical depth transport modeling remote sensing forest fires

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An adjusted parameter scheme of land surface emissivity for assimilation of microwave satellite data

An adjusted parameter scheme of land surface emissivity for ...

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atmospheric and environmental remote sensing data processing and utilization: Numerical atmospheric Prediction and environmental Monitoring

作者： Dong, Peiming Xue, Jishan Chinese Academy of Meteorological Sciences 46 South Zongguancun Street Beijing 100081 China

Land surface emissivity, which varies widely with surface type, is important for the assimilation of microwave satellite data. The fast radiative transfer model RTTOV-7 developed by ECMWF had been introduced into the Global/regional assimilation and prediction system (Grapes)-3Dvar, a new three dimensional data assimilation system developed by the Research Center for Numerical Meteorological Prediction, Chinese Academy of Meteorological Sciences, to assimilate ATOVS microwave satellite radiance directly. To improve the accuracy of land surface emissivity, the NOAA/NESDIS microwave land surface emissivity model developed by F. Weng is merged into RTTOV-7 and an adjusted parameter scheme is designed to provide the surface parameters for the microwave land surface emissivity model. These surface parameters are produced from a global data assimilation system (GDAS) including a boundary layer model in NOAA/NESDIS. The result shows that the accuracy of land surface emissivity for a variety of land types is improved. It results in the improvement of the accuracy of simulated satellite radiance. Following the satellite microwave radiance operating near the window regions, which are affected strongly by land surface emissivity, could be utilized in the assimilation system to investigate their impact on numerical weather forecast.

关键词： remote sensing

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Simultaneous overpass off nadir (SOON): A method for unified CalibrationNalidation across IEOS and GEOSS system of systems

Simultaneous overpass off nadir (SOON): A method for unified...

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conference on atmospheric and environmental remote sensing data processing and utilization II

作者： Ardanuy, Philip Bergen, Bill Huang, Allen Kratz, Gene Puschell, Jeff Schueler, Carl Walker, Joe Raytheon Informat Solut 12220 Sunrise Valley Dr Reston VA 20191 USA Raytheon IIS CIVIL Syst Aurora CO 80011 USA Univ Wisconsin CIMSS Madison WI 53706 USA Raytheon Informat Solut Upper Marlboro MD 20774 USA Raytheon Space & Airbone Syst El Segundo CA 90245 USA Raytheon Santa Barbara Remote Sensing Goleta CA 93117 USA

ISBN: (纸本)0819463809

The US operates a diverse, evolving constellation of research and operational environmental satellites, principally in polar and geosynchronous orbits. Our current and enhanced future domestic remote sensing capability is complemented by the significant capabilities of our current and potential future international partners. Satellite data users, such as the JSCSDA, are following roadmaps for the relentlessly increased ingest and assimilation of these data feeds, driven by the desire to fulfill the evolving operational requirements of their respective end-user communities. In this analysis, we define "success" through the data customers' "eyes": participating in the sufficient and continuously improving satisfaction of their mission responsibilities. To successfully fuse together observations from multiple simultaneous platforms and sensors into a common, self-consistent, operational environment requires that there exist a unified calibration and validation approach. Here, we consider develop a concept for an integrating framework for absolute accuracy;long-term stability;self-consistency among sensors, platforms, techniques, and observing systems;and validation and characterization of performance. Across all systems, this is a non-trivial problem. NOAA alone sustains > 80 observing platforms, > 800 variables, and > 30K observing data collection points. Simultaneous Nadir Overpasses, or SNO's, provide a proven intercomparison technique: simultaneous, collocated, co-angular measurements. Many systems have off-nadir elements, or effects, that must be calibrated. For these systems, the nadir technique constrains the process. We define the term "SOON," for simultaneous overpass off nadir. We present a target architecture and sensitivity analysis for the affordable, sustainable implementation of a global SOON calibration/validation network that can deliver the much-needed comprehensive, common, self-consistent operational picture in near-real time, at an affordable cost.

关键词： calibration validation SNO companson intercomparison satellite instrument sensor Earth environmental weather

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remote sensing for bridge health monitoring

Remote sensing for bridge health monitoring

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atmospheric and environmental remote sensing data processing and utilization V: Readiness for GEOSS III

作者： Liu, Wanqiu Chen, She-Een Hauser, Edd Department of Civil and Environmental Eng. UNCC 9201 University City Boulevard Charlotte NC 28223-0001 United States Center for Trans. Policy Studies UNCC 9201 University City Boulevard Charlotte NC 28223-0001 United States

ISBN: (纸本)9780819477460

This paper addresses the potential applications of commercial remote sensing (CRS) technologies for bridge monitoring. High resolution optical-photonic images can provide bridge damage information including through-deck collision damages, large permanent deformations, overload cracking and surface erosions, as well as surrounding environmental information. This paper summaries bridge issues that can be detected from high resolution remote sensing imageries based on visual interpretation as guidance for remote sensing imagery based bridge inspection, and the development of future automatic detection methods. A LiDAR based automatic bridge evaluation system LiBE (LiDAR Bridge Evaluation) is introduced in this paper with an application example of a test bridge maintained by the Los Angeles County (CA) Department of Public Works. Laser scanning techniques have also been used for bridge load testing in a new bridge near Charlotte, NC and maintained by the North Carolina DOT. The primary results of these preliminary tests are also presented. remote sensing techniques are introduced as a supplement to the existing, required visual bridge inspections. © 2009 SPIE.

关键词： remote sensing

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USU global ionospheric data assimilation models

USU global ionospheric data assimilation models

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Schunk, RW Scherliess, L Sojka, JJ Thompson, DC Utah State Univ Ctr Atmospher & Space Sci Logan UT 84322 USA

ISBN: (纸本)0819454869

The USU global ionospheric data assimilation model is part of the Global Assimilation of Ionospheric Measurements (GAIM). This model uses a physics-based ionosphere-plasmasphere-polar wind model and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. Some of the data that are assimilated include in situ electron density measurements from the DMSP satellites, bottomside electron density profiles from the Air Force network of digisondes, GPS-TEC data from a network of more than 900 stations, and occultation data. GAIM provides specifications and forecasts on a spatial grid that can be global, regional, or local. The primary GAIM output is in the form of 3-dimensional electron density distributions from 90 kin to the geosynchronous altitude. GAIM also provides auxiliary parameters (NmF2, h(m)F(2), NmE, h(m)E, slant and vertical TEC) and global distributions of the self-consistent ionospheric drivers (neutral winds and densities, electric fields, and particle precipitation). In its specification mode, GAIM provides quantitative estimates for the accuracy of the reconstructed ionospheric densities. In addition to the physics-based, Kalman filter model, we have also developed a Gauss-Markov Kalman filter model. The status of the models and the relevant applications are discussed.

关键词： ionosphere thermosphere data assimilation Kalman filter total electron content UV radiances ionosondes. densities winds GPS/TEC

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A study on the accuracies of ozone data observed with ground-based and satellite-borne instruments

A study on the accuracies of ozone data observed with ground...

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conference on atmospheric and Enviromental remote sensing data processing and utilization III: Readiness for GEOSS

作者： Wang Zhenhui Zhang Jinqiang Chen Hongbin Zhang Zhongbo He Zhixin Nanjing Univ Informat Sci & Technol Jiangsu Prov Key Lab Meteorol Disaster Nanjing 210044 Peoples R China NUIST Sch Remote Sensing Nanjing 210044 Jiangsu Peoples R China Chinese Acad Sci Inst Atmospher Phys Beijing 100029 Peoples R China

ISBN: (纸本)9780819468321

Three-fold restriction technique is used to determine the standard deviation of the error in the total-ozone content obtained from the three independent data resources such as ground-based station data, TOMS (Total Ozone Mapping Spectrophotometer) and GOME (The Global Ozone Monitoring Experiment) in 1995-2004. The results show that, in general, the accuracy of TOMS V8 data is the best and that of ground-based observations is the worst. Since the ground-based observations can be classified into 3 types according to the equipment principles such as Filter, Brewer and Dobson, the standard deviation of the errors for the 3 types of ground data are also calculated with the 3-fold restriction technique and it has been found that the Filter has the largest error, the Brewer is the second, and the Dobson is the least. The data quality at Shiangher Dobson Station of China is better than either TOMS or GOME. The data quality at Waliguan Brewer Station of China is better than TOMS, but worse than GOME. The error in TOMS V8 is evidently less than in TOMS V7 because of the algorithm amelioration of TOMS V8 over TOMS V7.

关键词： total ozone content three-fold restriction method satellite sensed data ground-based observations

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Evaluation of Satellite Land Surface Temperatures Using Ground Measurements from Surface Radiation Budget Network

Evaluation of Satellite Land Surface Temperatures Using Grou...

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conference on atmospheric and environmental remote sensing data processing and utilization IV - Readiness for GEOSS II

作者： Yu, Yunyue Tarpley, Dan Raja, M. K. Rama Varma Vinnikov, Konstantin Goldberg, Mitch D. NOAA NESDIS Ctr Satellite Applicat & Res 5200 Auth Rd 5200 Camp Springs MD 20746 USA Short & Assoc Inc Chevy Chase MD 20815 USA IM Syatems Grp Inc Kensington MD 20895 USA Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9780819473059

Evaluation of satellite land surface temperature (LST) is one of the most difficult tasks in LST retrieval algorithm development, because of spatial and temporal variability of land surface temperature and surface emissivity variations. A large number of high quality "match-up" satellite and ground LST data is needed for the evaluation process. In developing a LST algorithm for the GOES-R Advanced Baseline Imager, we produced a set of "match-up" dataset from SURFace RADiation (SURFRAD) budget network ground measurements and GOES-8 and -10 satellite measurements. The dataset covers one-year GOES Imager data over six SURFRAD sites in the United States. A stringent cloud filtering procedure was applied to minimize cloud contamination in the match-up dataset. Each of the SURFRAD sites contains enough match-up data pairs for ensuring significance of statistical analyses of the LST algorithm. The evaluation was performed by directly and indirectly comparing the SURFRAD and satellite LSTs of each site. The direct comparison was illustrated using scatter plots and histogram plots of the ground and the satellite LSTs, while the indirect comparison was performed using a matrix analysis model developed by Flynn (2006)[1]. We demonstrated that LST measurements from the SURFRAD instrument can be used in our evaluation of the GOES-R LST algorithm development and the precision of the GOES-R LST algorithm can be fairly well estimated.

关键词： Land surface temperature remote sensing GOES-R

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Evaluation of data thinning for climate applications using the first four years of AIRS hyperspectral data - art. no. 66840P

Evaluation of data thinning for climate applications using t...

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conference on atmospheric and Enviromental remote sensing data processing and utilization III: Readiness for GEOSS

作者： Aumann, Hartmut H. Fishbein, Evan Gohlke, Jan CALTECH Jet Prop Lab Pasadena CA 91109 USA

ISBN: (纸本)9780819468321

The application of infrared hyper-spectral sounder data to climate research requires the global analysis of multi-decadal time series of various atmosphere, surface or cloud related parameters. The data used in this analysis has to meet stringent global and scene independent absolute accuracy and stability requirements, it also has to be spatially and radiometrically unbiased, manageable in size and self-contained. Self-contained means that the data set contains not only a globally unbiased sample of the state of the Earth Climate system as seen in the infrared, it has to contain enough data to contrast clear with average (cloudy) data and to allow an independent assessment of the radiometric and spectral accuracy and stability of the data. We illustrate this with data from the atmospheric Infrared Sounder (AIRS) and Infrared atmospheric Sounder Interferometer (IASI) data. AIRS and IASI were designed with fairly similar functional requirements. AIRS was launched on the EOS Aqua spacecraft in May 2002 into a 705 km polar sun-synchronous orbit with accurately maintained 1:30 PM ascending node. Essentially un-interrupted data are available since September 2002. Since October 2006 IASI is in a 9:30 AM polar orbit at 8 15 km altitude on the MetOp2 satellite, with data available since May 2007.

关键词： infrared temperature sounder global change IASI CRIS

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