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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281-290 订阅

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Virtual laboratory for satellite training and data utilization

Virtual laboratory for satellite training and data utilizati...

引用

conference on atmospheric and environmental remote sensing data processing and utilization

作者： Purdom, JFW Hinsman, D Wilson, J Colorado State Univ Cooperat Inst Res Atmosphere Ft Collins CO USA

ISBN: (纸本)0819454869

The Virtual Laboratory for Education and Training in Satellite Matters (VL) was established to maximize the exploitation of meteorological satellite data across the globe. It is a collaborative effort joining four major operational meteorological satellite operators with six WMO "centers of excellence" for education and training in satellite meteorology. Those "centers of excellence" serve as the satellite-focused training resource for WMO Members. The VL continues to evolve and has been used successfully in a number of WMO sponsored training events since 2000.

关键词： satellite meteorology training satellite data utilization

来源：评论

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remote sensing opportunities for coastal management

Remote sensing opportunities for coastal management

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Howard, EG Pereira, JJ Dittberner, GJ Griffin, M Burke, HH NOAA NESDIS Silver Spring MD 20910 USA

ISBN: (纸本)0819454869

In earlier work (2), NOAA's Coastal Service Center in Charleston, S.C. reviewed current remote sensing and took a broader look at that technology applied to coastal resource management. They found 25 application areas and grouped them into 5 broader categories. In this paper we will explain some background and complexity of remote sensing when imaging in shallow water. This region is more complex than the deep ocean but there is synergy or opportunity to combine remote sensing measurements. Then we will summarize the 25 coastal areas of application with regard to spatial, spectral and temporal remote sensing needs including use of potential hyper-spectral sensors. Finally, we use the example of coral reef observations to explain the difficulty in trying to set remote sensing operational rules.

关键词： remote sensing coastal applications hyper-spectral sensors underwater imaging

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Long-term operation of ground-based atmospheric sensing systems in the tropical western pacific

Long-term operation of ground-based atmospheric sensing syst...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Ivey, M Jones, L Porch, B Apple, M Widener, K Montana State Univ Bozeman MT 59717 USA

ISBN: (纸本)0819454869

Three semi-autonomous atmospheric sensing systems were installed in the tropical western Pacific region. The first of these atmospheric Radiation and Cloud Stations (ARCS) began operation in 1996. Each ARCS is configured as a system-of-systems since it comprises an ensemble of independent instrument systems. The ARCS collect, process, and transmit large volumes of cloud, solar and thermal radiation, and meteorological data to support climate studies and climate-modeling improvements as part of the U.S. Department of Energy's atmospheric and Radiation Measurement (ARM) Program. data from these tropical ARCS stations have been used for satellite ground-truth data comparisons and validations, including comparisons for MTI and AQUA satellite data. Our experiences with these systems in the tropics led to modifications in their design. An ongoing international logistics effort is required to keep gigabytes per day of quality-assured data flowing to the ARM program's archives. Design criteria, performance, communications methods, and the day-to-day logistics required to support long-term operations of ground-based remote atmospheric sensing systems are discussed. End-to-end data flow from the ARCS systems to the ARM Program archives is discussed.

关键词： atmospheric and meteorological sensing semi-autonomous remote systems DOE ARM program tropical western pacific remote system diagnostics

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Analysis of regional high spatial resolution sounding products - Demonstration of MODIS and AIRS "stand-alone and synergistic" processing approaches

Analysis of regional high spatial resolution sounding produc...

引用

conference on atmospheric and environmental remote sensing data processing and utilization

作者： Guan, L Huang, HL Gao, W Weisz, E Li, J Univ Wisconsin Cooperat Inst Meteorol Satellite Studies Madison WI 53706 USA

ISBN: (纸本)0819454869

In this paper we present regional high spatial resolution sounding products from MODIS and AIRS data processed by both stand-alone and synergistic retrieval approaches. These unique regional high spatial resolution (at sensor's single field of view) atmospheric sounding products such as temperature, total precipitable water and surface temperature can provide valuable information for regional near-real time weather monitoring and meso-scale synoptic analysis, and other local environmental applications. Performance comparison between stand-alone and fusion products will assist validation effort and lead to the refinement of processing algorithms. Synergistic utilization of MODIS and AIRS data will also demonstrate the complementary information content provided by two different sensors and will pave the way for future optimal amalgamation of imaging and sounding data.

关键词： AIRS MODIS atmospheric profile retrieval synergistic

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Application of a testbed for validating remote sensor data and retrieval algorithms

Application of a testbed for validating remote sensor data a...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Lipton, A Moncet, JL Galantowicz, J Hu, HJ Lynch, R Boukabara, SA Hogan, DB d'Entremont, R He, YG Atmospher & Environm Res Inc 131 Hartwell Ave Lexington MA 02421 USA

ISBN: (纸本)0819454869

The AER algorithm testbed has been applied to instruments measuring in spectra from the ultraviolet to the microwave. The sensor simulation component starts with environmental data from numerical weather prediction models, surface property and terrain databases, and imagers, and simulates the detailed sensor spatial and spectral sampling processes, radiative transfer, polarization, and detector characteristics. This simulation is integrated with algorithm execution, to provide end-to-end capability. The tools allow for simulation of specific sensor errors, and tracing of their impact through the algorithm process to the quality of the retrieved environmental products. A critical component of the testbed is its radiative transfer models, which employ state-of-the-science programs for line-by-line optical properties, for radiative transfer in scattering atmospheres, and for a variety of surfaces. Fast and accurate computational methods are incorporated, such as Optimal Spectral Sampling (OSS). Application examples are shown, including characterization of AMSU sensor data errors and retrieval performance evaluation, in which retrievals from the microwave sounder data and infrared image data contribute to the interpretation of remote sensing phenomena in cloudy environments.

关键词： sensor simulation remote sensing radiative transfer satellite

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Compression of AIRS data using empirical mode decomposition

Compression of AIRS data using empirical mode decomposition

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Gladkova, I Roytman, L Goldberg, M Weber, J CUNY City Coll NOAA CREST New York NY 10031 USA

ISBN: (纸本)0819454869

In this paper, we consider an application of the Empirical Mode Decomposition (EMD) introduced by Norden E. Huang in 1996 to the compression of 3D hyperspectral sounding data. The EMD is a new data analysis method which is based on expansion of the data in terms of Intrinsic Mode Functions (IMF). These IMFs are based on and derived from the data set. Since EMD adaptively represent the signal as a sum of "well behaved" amplitude/frequency modulated components, we found it very well suited for the whitening part of the compression scheme.

关键词： compression empirical mode decomposition intrinsic mode functions Karhunen-Loeve

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Satellite ocean remote sensing at NOAA/NESDIS

Satellite ocean remote sensing at NOAA/NESDIS

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Bayler, EJ NOAA NESDIS Ctr Satellite Applicat & Res Camp Springs MD 20746 USA

ISBN: (纸本)0819454869

Satellite oceanography within the Center for Satellite Applications and Research (STAR) in National Oceanic and atmospheric Administrationis (NOAA) National environmental Satellite, data, and Information Service (NESDIS) focuses on observation retrievals and applications to address the NOAA missions of environmental assessment, prediction, and stewardship. Satellite oceanography within NOAA/NESDIS is an end-to-end process, addressing user requirements, sensor design support, observation retrieval research and development, calibration, applications and product research and development, the transition of research to operations, continuing product validation, and operational user support. The breadth of scientific investigation encompasses three functional areas: satellite ocean sensors, ocean dynamics/data assimilation, and marine ecosystems/climate. A cross-cutting science team from these functional areas has been established for each core subject: sea-surface temperature, sea-surface height, sea-surface roughness, ocean color, ocean surface winds, and sea ice. These science teams pursue the science and issues end to end within the core subject, with the primary objective being the transition of research to operations. data fusion opportunities between science teams are also pursued. Each science team area addresses the common themes of calibration/validation, data assimilation, climate, and operational oceanography. Experimental and operational products, as well as user support, are provided to the user community via the NOAA OceanWatch/CoastWatch program.

关键词： Satellites Oceanography remote sensing Climatology data modeling Algorithm development environmental sensing Sensors Calibration Ocean optics

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Testbed architecture for rapid prototyping and assessment of environmental remote sensing algorithms

Testbed architecture for rapid prototyping and assessment of...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Zaccheo, TS Galantowicz, J Hogan, DB Kennelly, EJ Snell, HE Atmospher & Environm Res Inst Lexington MA 02421 USA

ISBN: (纸本)0819454869

The Interactive Algorithm Tool Box (IATB) is a multi-layered architecture designed to aid in the rapid implementation and end-to-end assessment of algorithms for estimating environmental parameters from remote sensing data. This architectural scheme employs a layered approach. The primary layer provides common methods for accessing sensor, ancillary and auxiliary data as well as user configurable parameters. The second layer provides a standard set of tools that can be used in the development of the target remote sensing algorithm and its supporting simulation tools. One of the primary tools provides a self-consistent mechanism for performing radiative transfer calculations over a broad spectral range from the Microwave to the Infrared/Visible. This toolbox also provides standard mechanisms for building first-order sensor models. The final layer provides a platform independent "wrapper" for integrating the target algorithm and its simulation tools with a set of standard and custom analysis tools. This layer provides an end-to-end product that can be used for extended analysis and calibration/validation with either simulated or "real" data. The testbed architecture has been applied to instruments measuring in spectra from the visible to the microwave. It has been employed during the development of algorithms for existing remote sensing systems (e.g. AMSU and AIRS) as well as sensor suites that will be flown on next generation satellites (e.g. NPOESS and GOES). This paper describes the IATB architecture and presents the implementation for several applications.

关键词： remote sensing retrieval algorithm sensor simulation satellite

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Development of the IASI operational processing and distribution system

Development of the IASI operational processing and distribut...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： King, T Wolf, W Goldberg, M Barnet, C Sun, H Zhou, L QSS Grp Inc Lanham MD 20706 USA

ISBN: (纸本)0819454869

Development and testing of the IASI processing and distribution system is currently ongoing at NOAA/NESDIS/ORA. Level I C data for 8461 channels will be available to NESDIS/NOAA from EUMETSAT shortly after MetOp 1 launch (currently scheduled for October 2005). Prior to launch, a simulation system will provide pseudo near-real time data for system testing and refinement. This will allow for a smooth and immediate system transition to the actual data processing when it becomes available. The ingested EUMETSAT level1C data will be subset both spectrally and spatially and then placed into BUFR format for a number of products including: (1) Level 1C (calibrated, apodized, and navigated) brightness temperatures, (2) cloud-cleared radiances, and (3) PCA reconstructed radiances. The subset level1C data will be delivered within three hours of observation. System validation will consist of comparing the products to collocated radiosonde observations and model forecasts.

关键词： Binary data Clouds data acquisition data processing Infrared radiation data centers Algorithm development data modeling atmospheric modeling Satellites

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Cluster versus grid for large-volume hyperspectral image preprocessing

Cluster versus grid for large-volume hyperspectral image pre...

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conference on atmospheric and environmental remote sensing data processing and utilization

作者： Brazile, J Schaepman, ME Schläpfer, D Kaiser, JW Nieke, J Itten, KI Univ Zurich Dept Geog Remote Sensing Labs CH-8057 Zurich Switzerland

ISBN: (纸本)0819454869

The handling of satellite or airborne earth observation data for scientific applications minimally requires pre-processing to convert raw digital numbers into scientific units. However depending on sensor characteristics and architecture, additional work may be needed to achieve spatial and/or spectral uniformity. Standard higher level processing also typically involves providing orthorectification and atmospheric correction. Fortunately some of the computational tasks required to perform radiometric and geometric calibration can be decomposed into highly independent subtasks making this processing highly parallelizable. Such "embarrassingly parallel" problems provide the luxury of being able to choose between cluster or grid based solutions to perform these functions. Perhaps the most convenient solutions are grid-based, since most research groups making these kinds of measurements are likely to have access to a LAN whose spare computing resources could be non-obtrusively employed in a grid. However, since many higher level scientific applications of earth observation data might be composed of more highly interdependent subtasks, the parallel computing resources allocated for these tasks might also be made available for low level pre-processing as well. We look at two modules developed for our prototype data calibration processor for APEX, an airborne imaging spectrometer, which have been implemented on both a cluster and a grid leading us to be able to make observations and comparisons of the two approaches.

关键词： hyperspectral cluster grid MODTRAN APEX

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