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A.p. Rodger - One of the best experts on this subject based on the ideXlab platform.
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The performance of the multispectral Thermal Imager (MTI) surface temperature retrieval algorithm at three sites
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: A.p. Rodger, L. Balick, W.b. ClodiusAbstract:This work describes the surface temperature retrieval algorithm for the U.S. Department of Energy Multispectral Thermal Imager (MTI) satellite and its performance at three test sites. The MTI is a 15-band multispectral research and technology development satellite that provides high spatial resolution Imagery of the earth's surface from a polar orbit. It has a capability for pixel-by-pixel retrieval of total atmospheric water vapor during the day. The surface temperature retrieval process uses atmospheric profiles of temperature and water vapor from numerical weather prediction data assimilation products available for the globe. The profiles of water vapor are scaled using the retrieved pixel-by-pixel water vapor during the day to improve atmospheric compensation within the image. The algorithm requires specification of a maximum emissivity or the acceptance of a default: here the maximum band emissivity is known and specified. The results of the algorithm are evaluated at three sites with a high degree of surface uniformity and known spectral emissivity: Lake Tahoe, NV/CA, Ivanpah Playa, NV/CA, and the Mauna Loa caldera, HI. At the first two sites, coincident measurements of surface temperature and emissivity are available. At Mauna Loa, surface emissivity measurements are available, but surface temperature measurements are not. Therefore, at Mauna Loa, the surface emissivity estimates derived from the surface temperature retrieval are compared with emissivity measurements. The results show that the surface temperature retrievals had a root mean square (RMS) difference with surface measurements of 0.6 K during the day and 1.0 K at night. This indicates, albeit weakly, that the use of pixel-by-pixel water vapor retrieved by the satellite improves the overall surface temperature retrievals. At Ivanpah Playa, all the data are daytime, and the surface temperature retrievals have an RMS difference with the in situ measurements of 0.8 K. The Mauna Loa emissivities derived from the surface temperature retrieval agreed excellently with in situ emissivity measurements. The approach taken to perform surface temperature retrieval, used operationally within the MTI research and development program, is seen to be simple and effective.
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Satellite-based columnar water vapor retrieval with the multi-spectral Thermal Imager (MTI)
IEEE Transactions on Geoscience and Remote Sensing, 2003Co-Authors: P. Chylek, C.c. Borel, W. Clodius, P.a. Pope, A.p. RodgerAbstract:The Multi-spectral Thermal Imager (MTI) has three near-infrared bands (E, F, and G) within the 850-1050-nm spectral range that are used for the columnar water vapor (CWV) retrieval using the continuum interpolated band ratio (CIBR) and the atmospheric precorrected differential absorption (APDA) methods. The retrieved CWV amounts are compared with the aerosol robotic network (AERONET) measurements at the Oklahoma Atmospheric Radiation Measurement (ARM) program and the Stennis Space Center sites. We find no significant difference in the accuracy of the two tested methods. However, there is a considerable difference in the root mean square error (RMSE) for the CWV retrieval over the Oklahoma ARM and the Stennis Space Center sites. The overall RMSE of the MTI CWV retrieval is found to be 13% to 14%. The error is reduced to 11% to 12% for CWV amounts larger then 1 g/cm/sup 2/.
Alan R Gillespie - One of the best experts on this subject based on the ideXlab platform.
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extending surface temperature and emissivity retrieval to the mid infrared 3 5 μm using the multispectral Thermal Imager mti
Remote Sensing of Environment, 2005Co-Authors: Amit Mushkin, Lee K. Balick, Alan R GillespieAbstract:Abstract Surface-temperature (T) and emissivity (e) estimation from remotely sensed mid-infrared (MIR: 3–5 μm) data requires modifications to existing long-wave infrared (LWIR: 8–12 μm) T/e separation algorithms because of the significantly different characteristics of Planck's function between the MIR and LWIR wavelength regions and the strong effects of reflected solar irradiance in the MIR. A modified version of the normalized emissivity method (NEM), utilizing independently scaled maximum emissivities in each channel, was applied to Thermal data acquired by the Multispectral Thermal Imager (MTI) with two MIR channels, J (3.81 μm) and K (4.97 μm), and three LWIR channels, L (8.26 μm), M (8.65 μm), and N (10.51 μm). Atmosphere-free simulations of T and e retrieval over a wide variety of terrestrial surfaces yielded T values within ± 0.75 K of ‘true T’ in the range of 270–330 K and e values within ± 0.011 of true e in channels L, M and N, and ± 0.019 and ± 0.023 in channels K and J, respectively. The algorithm was tested successfully using MTI data over the Mauna Loa caldera in Hawaii. Unconstrained effects of shading and unresolved shadows in channel J day time data, and the strong atmospheric effects in channel K limit the application of the algorithm, in its present form, to night-time data.
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Extending surface temperature and emissivity retrieval to the mid-infrared (3-5 μm) using the Multispectral Thermal Imager (MTI)
Remote Sensing of Environment, 2005Co-Authors: Amit Mushkin, Lee K. Balick, Alan R GillespieAbstract:Surface-temperature (T) and emissivity (ε) estimation from remotely sensed mid-infrared (MIR: 3-5 μm) data requires modifications to existing long-wave infrared (LWIR: 8-12 μm) T/ε separation algorithms because of the significantly different characteristics of Planck's function between the MIR and LWIR wavelength regions and the strong effects of reflected solar irradiance in the MIR. A modified version of the normalized emissivity method (NEM), utilizing independently scaled maximum emissivities in each channel, was applied to Thermal data acquired by the Multispectral Thermal Imager (MTI) with two MIR channels, J (3.81 μm) and K (4.97 μm), and three LWIR channels, L (8.26 μm), M (8.65 μm), and N (10.51 μm). Atmosphere-free simulations of T and ε retrieval over a wide variety of terrestrial surfaces yielded T values within ± 0.75 K of 'true T' in the range of 270-330 K and ε values within ± 0.011 of true ε in channels L, M and N, and ± 0.019 and ± 0.023 in channels K and J, respectively. The algorithm was tested successfully using MTI data over the Mauna Loa caldera in Hawaii. Unconstrained effects of shading and unresolved shadows in channel J day time data, and the strong atmospheric effects in channel K limit the application of the algorithm, in its present form, to night-time data.
Amit Mushkin - One of the best experts on this subject based on the ideXlab platform.
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extending surface temperature and emissivity retrieval to the mid infrared 3 5 μm using the multispectral Thermal Imager mti
Remote Sensing of Environment, 2005Co-Authors: Amit Mushkin, Lee K. Balick, Alan R GillespieAbstract:Abstract Surface-temperature (T) and emissivity (e) estimation from remotely sensed mid-infrared (MIR: 3–5 μm) data requires modifications to existing long-wave infrared (LWIR: 8–12 μm) T/e separation algorithms because of the significantly different characteristics of Planck's function between the MIR and LWIR wavelength regions and the strong effects of reflected solar irradiance in the MIR. A modified version of the normalized emissivity method (NEM), utilizing independently scaled maximum emissivities in each channel, was applied to Thermal data acquired by the Multispectral Thermal Imager (MTI) with two MIR channels, J (3.81 μm) and K (4.97 μm), and three LWIR channels, L (8.26 μm), M (8.65 μm), and N (10.51 μm). Atmosphere-free simulations of T and e retrieval over a wide variety of terrestrial surfaces yielded T values within ± 0.75 K of ‘true T’ in the range of 270–330 K and e values within ± 0.011 of true e in channels L, M and N, and ± 0.019 and ± 0.023 in channels K and J, respectively. The algorithm was tested successfully using MTI data over the Mauna Loa caldera in Hawaii. Unconstrained effects of shading and unresolved shadows in channel J day time data, and the strong atmospheric effects in channel K limit the application of the algorithm, in its present form, to night-time data.
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Extending surface temperature and emissivity retrieval to the mid-infrared (3-5 μm) using the Multispectral Thermal Imager (MTI)
Remote Sensing of Environment, 2005Co-Authors: Amit Mushkin, Lee K. Balick, Alan R GillespieAbstract:Surface-temperature (T) and emissivity (ε) estimation from remotely sensed mid-infrared (MIR: 3-5 μm) data requires modifications to existing long-wave infrared (LWIR: 8-12 μm) T/ε separation algorithms because of the significantly different characteristics of Planck's function between the MIR and LWIR wavelength regions and the strong effects of reflected solar irradiance in the MIR. A modified version of the normalized emissivity method (NEM), utilizing independently scaled maximum emissivities in each channel, was applied to Thermal data acquired by the Multispectral Thermal Imager (MTI) with two MIR channels, J (3.81 μm) and K (4.97 μm), and three LWIR channels, L (8.26 μm), M (8.65 μm), and N (10.51 μm). Atmosphere-free simulations of T and ε retrieval over a wide variety of terrestrial surfaces yielded T values within ± 0.75 K of 'true T' in the range of 270-330 K and ε values within ± 0.011 of true ε in channels L, M and N, and ± 0.019 and ± 0.023 in channels K and J, respectively. The algorithm was tested successfully using MTI data over the Mauna Loa caldera in Hawaii. Unconstrained effects of shading and unresolved shadows in channel J day time data, and the strong atmospheric effects in channel K limit the application of the algorithm, in its present form, to night-time data.
Paul G Weber - One of the best experts on this subject based on the ideXlab platform.
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Multispectral Thermal Imager: mission and applications overview
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: J.j. Szymanski, Paul G WeberAbstract:The Multispectral Thermal Imager (MTI) satellite is a research and development project sponsored by the U.S. Department of Energy. The primary mission is to demonstrate advanced multispectral and Thermal imaging from a satellite, including new technologies, data processing, and analysis techniques and validation by reference to ground truth. The MTI builds on the efforts of a number of earlier efforts, including Landsat, National Aeronautics and Space Administration remote sensing missions, and others, but the MTI incorporates a unique combination of attributes designed to advance the state of the art. The MTI satellite was launched on March 12, 2000 into a 580 km/spl times/610 km, sun-synchronous orbit with nominal 1 a.m. and 1 p.m. equatorial crossing times. The Air Force Space Test Program provided the Orbital Sciences Taurus launch. The satellite-based sensors obtain radiance data that are subsequently processed into measurements of atmospheric and surface properties such as column water vapor, atmospheric aerosol loading, surface temperatures, material composition, and others. This paper provides an overview of the MTI research objectives, design, operations, data products, and data processing and analysis. Several other papers provide greater detail on selected topics.
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multispectral Thermal Imager mission overview
SPIE's International Symposium on Optical Science Engineering and Instrumentation, 1999Co-Authors: Paul G Weber, B W Smith, W.b. Clodius, Christoph C Borel, Brian C Brock, Alfred J Garrett, S C Bender, Max L DeckerAbstract:The Multispectral Thermal Imager (MTI) is a research and development project sponsored by the Department of Energy and executed by Sandia and Los Alamos National Laboratories and the Savannah River Technology Center. Other participants include the U.S. Air Force, universities, and many industrial partners. The MTI mission is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of industrial facilities and related environmental impacts from space. MTI provides simultaneous data for atmospheric characterization at high spatial resolution. Additionally, MTI has applications to environmental monitoring and other civilian applications. The mission is based in end-to-end modeling of targets, signatures, atmospheric effects, the space sensor, and analysis techniques to form a balanced, self-consistent mission. The MTI satellite nears completion, and is scheduled for launch in late 1999. This paper describes the MTI mission, development of desired system attributes, some trade studies, schedule, and overall plans for data acquisition and analysis. This effort drives the sophisticated payload and advanced calibration systems, which are the overall subject of the first session at this conference, as well as the data processing and some of the analysis tools that will be described in the second segment.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
L. Balick - One of the best experts on this subject based on the ideXlab platform.
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The performance of the multispectral Thermal Imager (MTI) surface temperature retrieval algorithm at three sites
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: A.p. Rodger, L. Balick, W.b. ClodiusAbstract:This work describes the surface temperature retrieval algorithm for the U.S. Department of Energy Multispectral Thermal Imager (MTI) satellite and its performance at three test sites. The MTI is a 15-band multispectral research and technology development satellite that provides high spatial resolution Imagery of the earth's surface from a polar orbit. It has a capability for pixel-by-pixel retrieval of total atmospheric water vapor during the day. The surface temperature retrieval process uses atmospheric profiles of temperature and water vapor from numerical weather prediction data assimilation products available for the globe. The profiles of water vapor are scaled using the retrieved pixel-by-pixel water vapor during the day to improve atmospheric compensation within the image. The algorithm requires specification of a maximum emissivity or the acceptance of a default: here the maximum band emissivity is known and specified. The results of the algorithm are evaluated at three sites with a high degree of surface uniformity and known spectral emissivity: Lake Tahoe, NV/CA, Ivanpah Playa, NV/CA, and the Mauna Loa caldera, HI. At the first two sites, coincident measurements of surface temperature and emissivity are available. At Mauna Loa, surface emissivity measurements are available, but surface temperature measurements are not. Therefore, at Mauna Loa, the surface emissivity estimates derived from the surface temperature retrieval are compared with emissivity measurements. The results show that the surface temperature retrievals had a root mean square (RMS) difference with surface measurements of 0.6 K during the day and 1.0 K at night. This indicates, albeit weakly, that the use of pixel-by-pixel water vapor retrieved by the satellite improves the overall surface temperature retrievals. At Ivanpah Playa, all the data are daytime, and the surface temperature retrievals have an RMS difference with the in situ measurements of 0.8 K. The Mauna Loa emissivities derived from the surface temperature retrieval agreed excellently with in situ emissivity measurements. The approach taken to perform surface temperature retrieval, used operationally within the MTI research and development program, is seen to be simple and effective.
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In-flight validation of mid- and Thermal infrared data from the Multispectral Thermal Imager (MTI) using an automated high-altitude validation site at Lake Tahoe CA/NV, USA
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: S.j. Hook, W.b. Clodius, L. Balick, R.e. Alley, R.c. Richards, A. Abtahi, S.g. SchladowAbstract:The Multispectral Thermal Imager (MTI) is a 15-band satellite-based imaging system. Two of the bands (J, K) are located in the mid-infrared (3-5 /spl mu/m) wavelength region: J, 3.5-4.1 /spl mu/m and K, 4.9-5.1 /spl mu/m, and three of the bands (L, M, N) are located in the Thermal infrared (8-12 /spl mu/m) wavelength region: L, 8.0-8.4 /spl mu/m; M, 8.4-8.8 /spl mu/m; and N, 10.2-10.7 /spl mu/m. The absolute radiometric accuracy of the MTI data acquired in bands J-N was assessed over a period of approximately three years using data from the Lake Tahoe, CA/NV, automated validation site. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the MTI overpass to predict the vicarious at-sensor radiance. The vicarious at-sensor radiance was convolved with the MTI system response functions to obtain the vicarious at-sensor MTI radiance in bands J-N. The vicarious radiances were then compared with the instrument measured radiances. In order to avoid any reflected solar contribution in the mid-infrared bands, only nighttime scenes were used in the analysis of bands J and K. Twelve cloud-free scenes were used in the analysis of the data from the mid-infrared bands (J, K), and 23 cloud-free scenes were used in the analysis of the Thermal infrared bands (L, M, N). The scenes had skin temperatures ranging between 4.4 and 18.6/spl deg/C. The skin temperature was found to be, on average, 0.18/spl plusmn/0.36 degC cooler than the bulk temperature during the day and 0.65/spl plusmn/0.31 degC cooler than the bulk temperature at night. The smaller skin effect during the day was attributed to solar heating. The mean and standard deviation of the percent differences between the vicarious (predicted) at-sensor radiance convolved to the MTI bandpasses and the MTI measured radiances were -1.38/spl plusmn/2.32, -2.46/spl plusmn/1.96, -0.04/spl plusmn/0.78, -1.97/spl plusmn/0.62, -1.59/spl plusmn/0.55 for bands J-N, respectively. The results indicate that, with the exception of band L, the instrument measured radiances are warmer than expected.
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Multispectral Thermal Imager science, data product and ground data processing overview
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International, 2001Co-Authors: J.j. Szymanski, W. Atkins, W. Christensen, Christoph C Borel, James Theiler, A Morrison, L. Balick, W.b. Clodius, Christian Rohde, P. Pope, B W Smith, K. Hirsch, A B Davis, Kesley Ramsey, C. Little, Kristin Pollock, K. Starkovich, D. Roussel-Dupre, E. Riddle, C. Novak, P. McLachlan, J.B. Krone, A. Galbraith, J.C. Echohawk, K Smith, Philippe WeberAbstract:The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The system also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data analysis and interpretation. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. This paper describes the MTI data products and ground processing, as well as the "how to" aspects of starting a data center from scratch
