The Multispectral Thermal Imager (MTI) is a technology test and demonstration satellite whose primary mission involved a finite number of technical objectives. MTI was not designed, or supported, to become a general purpose operational satellite. The role of the MTI science team is to provide a core group of system-expert scientists who perform the scientific development and technical evaluations needed to meet programmatic objectives. Another mission for the team is to develop algorithms to provide atmospheric compensation and quantitative retrieval of surface parameters to a relatively small community of MTI users. Finally, the science team responds and adjusts to unanticipated events in the life of the satellite. Broad or general lessons learned include the value of working closely with the people who perform the calibration of the data as well as those providing archived image and retrieval products. Close interaction between the Los Alamos National Laboratory (LANL) teams was very beneficial to the overall effort as well as the science effort. Secondly, as time goes on we make increasing use of gridded global atmospheric data sets which are products of global weather model data assimilation schemes. The Global Data Assimilation System information is available globally every six hours and the Rapid Update Cycle products are available over much of the North America and its coastal regions every hour. Additionally, we did not anticipate the quantity of validation data or time needed for thorough algorithm validation. Original validation plans called for a small number of intensive validation campaigns soon after launch. One or two intense validation campaigns are needed but are not sufficient to define performance over a range of conditions or for diagnosis of deviations between ground and satellite products. It took more than a year to accumulate a good set of validation data. With regard to the specific programmatic objectives, we feel that we can do a reasonable job on retrieving surface water temperatures well within the 1°C objective under good observing conditions. Before the loss of the onboard calibration system, sea surface retrievals were usually within 0.5°C. After that, the retrievals are usually within 0.8°C during the day and 0.5°C at night. Daytime atmospheric water vapor retrievals have a scatter that was anticipated: within 20%. However, there is error in using the Aerosol Robotic Network retrievals as validation data which may be due to some combination of calibration uncertainties, errors in the ground retrievals, the method of comparison, and incomplete physics. Calibration of top-of-atmosphere radiance measurements to surface reflectance has proven daunting. We are not alone here: it is a difficult problem to solve generally and the main issue is proper compensation for aerosol effects. Getting good reflectance validation data over a number of sites has proven difficult but, when assumptions are met, the algorithm usually performs quite well. Aerosol retrievals for off-nadir views seem to perform better than near-nadir views and the reason for this is under investigation. Land surface temperature retrieval and temperature-emissivity separations are difficult to perform accurately with multispectral sensors. An interactive cloud masking system was implemented for production use. Clouds are so spectrally and spatially variable that users are encouraged to carefully evaluate the delivered mask for their own needs. The same is true for the water mask. This mask is generated from a spectral index that works well for deep, clear water, but there is much variability in water spectral reflectance inland and along coasts. The value of the second-look maneuvers has not yet been fully or systematically evaluated. Early experiences indicated that the original intentions have marginal value for MTI objectives, but potentially important new ideas have been developed. Image registration (the alignment of data from different focal planes) and band-to-band registration has been a difficult problem to solve, at least for mass production of the images in a processing pipeline. The problems, and their solutions, are described in another paper.
The zero-core-contribution model is extended to calculate absolute photodetachment cross sections taking into account the fine-structure levels and higher electronic states of the anions and neutral atoms. Comparisons are made with experimental data involving 20 different anions with $p$ outermost occupied orbitals. Very good agreement is obtained.
Deriving information about the Earth's surface requires atmospheric corrections of the measured top-of-the- atmosphere radiances. One possible path is to use atmospheric radiative transfer codes to predict how the radiance leaving the ground is affected by the scattering and attenuation. In practice the atmosphere is usually not well known and thus it is necessary to use more practical methods. We will describe how to find dark surfaces, estimate the atmospheric optical depth, estimate path radiance and identify thick clouds using thresholds on reflectance and NDVI and columnar water vapor. We describe a simple method to correct a visible channel contaminated by a thin cirrus clouds.
The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed.
The zero-core-contribution method is extended to study the photodetachment of heteronuclear diatomic molecules. Total photodetachment cross sections are calculated for the ions O${\mathrm{H}}^{\ensuremath{-}}$, S${\mathrm{H}}^{\ensuremath{-}}$, and Se${\mathrm{H}}^{\ensuremath{-}}$. The anisotropy factor $\ensuremath{\beta}$ is also calculated for O${\mathrm{H}}^{\ensuremath{-}}$. The agreement with measured values of these quantities is good.
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.
Numerous statistical approaches have been developed for small target detection in cluttered environments. Examples include orthogonal background suppression (OBS) where the initial principal components are suppressed, and the clutter matched filter (CMF) where the principal components are weighted by the inverse of the eigenvalues and the latter principal components are discarded. Our research has shown that improved target detection performance can be obtained by combining certain aspects of both OBS and CMF approaches. This is especially true in the presence of limited scene data (finite number of pixels) or an imperfect reference target spectrum. The basis of this idea is to use weighting by the inverse of the eigenvalues (from CMF) for the initial PCs and the uniform weighting for the later PCs (from OBS). Examples of this new technique and comparisons with OBS and CMF will be shown with model data with realistic clutter containing a chemical plume.
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.
