The Multispectral Thermal Imager, MTI, is a research and development project sponsored by the United States 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. The MTI builds on the efforts of a number of earlier efforts, including Landsat, NASA remote sensing missions, and others, but the MTI incorporates a unique combination of attributes. The MTI satellite was launched on 12 March 2000 into a 580 km x 610 km, sun-synchronous orbit with nominal 1 am and 1 pm equatorial crossing times. The Air Force Space Test Program provided the Orbital Sciences Taurus launch vehicle. The satellite has a design lifetime of a year, with the goal of three years. The satellite and payload can typically observe six sites per day, with either one or two observations per site from nadir and off-nadir angles. Data are stored in the satellite memory and down-linked to a ground station at Sandia National Laboratory. Data are then forwarded to the Data Processing and Analysis Center at Los Alamos National Laboratory for processing, analysis and distribution to the MTI team and collaborators. We will provide an overview of the Project, a few examples of data products, and an introduction to more detailed presentations in this special session.
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 MTI satellite 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 interpretation and analysis. 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. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.
The Multispectral Thermal Imager (MTI) is designed to demonstrate the utility of multispectral remote sensing from a satellite platform for a variety of applications of interest to the U.S. Department of Energy. These applications include characterization of industrial facilities, environmental impacts of effluents, global change, hazardous waste sites, resource exploitation, crop health, and others. The MTI was designed using a procedure which we call `End-to-end modeling and analysis (EEM).' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term `end-to-end modeling and analysis.' We based the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolved, and as real hardware was tested, we updated the EEM to facilitate trade studies, and to judge, for example, whether components that deviated from specifications were acceptable. During detailed calibration at the Los Alamos Radiometric Calibration Facility we used our models to explain certain observations, and to extend limited measurements to larger domains of applicability. Data analysis programs have been developed to generate a comprehensive set of data products through our Data Processing and Analysis Center. The satellite was due for launch on 8 February 2000: the actual launch data was 12 March, 2000. At the conference we anticipate sharing some preliminary observations from on-orbit.
The Multispectral Thermal Imager (MTI) has a number of core science retrievals which will be described. We will concentrate on describing the major Level-2 algorithms which cover land, water and atmospheric products. The land products comprise atmospherically corrected surface reflectances, vegetation health status, material identification, land temperature and emissivities. The water related products are: water mask, water quality and water temperature. The atmospheric products are: cloud mask, cirrus mask and atmospheric water vapor. We will present several of these algorithms and present results from simulated MTI data derived from AVIRIS and MODIS Airborne Simulator (MAS). An interactive analysis tool has been created to visually program and test certain Level-2 retrievals.
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.
MTI is a comprehensive research and development project that includes up-front modeling and analysis, satellite system design, fabrication, assembly and testing, on-orbit operations, and experimentation and data analysis. The satellite is designed to collect radiometrically calibrated, medium resolution imagery in 15 spectral bands ranging from 0.45 to 10.70 micrometer. The payload portion of the satellite includes the imaging system components, associated electronics boxes, and payload support structure. The imaging system includes a three-mirror anastigmatic off-axis telescope, a single cryogenically cooled focal plane assembly, a mechanical cooler, and an onboard calibration system. Payload electronic subsystems include image digitizers, real-time image compressors, a solid state recorder, calibration source drivers, and cooler temperature and vibration controllers. The payload support structure mechanically integrates all payload components and provides a simple four point interface to the spacecraft bus. All payload components have been fabricated and tested, and integrated.
The major science goal for the Multispectral Thermal Imager (MTI) project is to measure surface properties such as vegetation health, temperatures, material composition and others for characterization of industrial facilities and environmental applications. To support this goal, this program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data 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 robust operation. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper will provide an introduction to the data processing and science algorithms for the MTI project. Detailed discussions of the retrieval techniques will follow in papers from the balance of this session.
The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: `End-to-end modeling and analysis (EEM).' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term `end-to-end modeling and analysis.' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable.
Many remote sensing applications rely on imaging spectrometry. Here we use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. Our approach is supported by physics-based end- to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects.
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 ultimate goal of end-to-end system modeling is to simulate all known physical effects which determine the content of the data, before flying an instrument system. In practice we approach this ideal but do not attain it. In remote sensing, one begins with a scene, viewed either statically or dynamically, computes the radiance in each spectral band, renders the scene, transfers it through representative atmospheres to create the radiance field at an aperture, and integrates over sensor pixels. We have simulated a comprehensive sequence of realistic instrument hardware elements and the transfer of simulated data to an analysis system. This analysis package is the same as that intended for use on data collections from the real system. By comparing the analyzed image to the original scene, the net effect of nonideal system components can be understood. Iteration yields the optimum values of system parameters to achieve performance targets. We have used simulation to develop and test improved multispectral algorithms for : (1) the robust retrieval of water surface temperature, water vapor column,and other quantities; (2) the preservation of radiometric accuracy during atmospheric correction and pixel registration on the ground; and (3) exploitation of on- board multispectral measurements to assess the atmosphere between ground and aperture. We have evaluated the errors in these retrievals for a variety of target types due to: telescope OTF, calibration bias, system noise, spacecraft motion and jitter, atmospheric effects, telescope distortions, and co- registration during processing of multispectral images with offset pixels.
The hemispherical optimized net radiometer (HONER) is an instrument under development at the Los Alamos National Laboratory as part of the Atmospheric Radiation measurements/Unmanned Aerospace Vehicles (ARM/UAV) program. HONER is a radiometer which will either measure directly the difference between the total upwelling and downwelling fluxes or the individual fluxes and will provide a means of measuring the atmospheric radiative flux divergence. Unlike existing instruments which only measure the upwelling and downwelling fluxes separately, HONER will achieve an optical difference by chopping the two fluxes alternately onto a common pyroelectric detector. HONER will provide data resolved into the two relevant spectral bands; one covering the solar dominated region from less than 0.4 micrometer to approximately 4 micrometers and the other covering the region from approximately 4 micrometers to greater than 50 micrometers, dominated by thermal radiation. The means of separating the spectral regions guarantees seamless summation to calculate the total flux. The fields-of-view are near-hemispherical, upward and downward. The instrument can be converted, in flight, from the differential mode to absolute mode, measuring the upwelling and downwelling fluxes separately and simultaneously. The instrument also features continuous calibration from on-board sources. We describe the basic design and operation of the sensor head and the on-board reference sources as well as the means of the initial deployment on a UAV. This instrument can also be used in ground-based, space, or other airborne applications.
A major diagnostic in understanding the response of the Earth's climate to natural or anthropogenic changes is the radiative balance at the top of the atmosphere. Two classes of measurements may be undertaken: (1) a monitoring of the radiation balance over decade-long long-time scales; and (2) measurements designed to provide a sufficiently complete data set to validate or improve models. This paper discusses some of the important ingredients in obtaining such data and presents a description of some candidate instrumentation for use on a small satellites.