Vicarious calibration of ASTER thermal infrared bands

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on the Terra satellite has five bands in the thermal infrared (TIR) spectral region between 8-12 /spl mu/m. The TIR bands have been regularly validated in-flight using ground validation targets. Validation results are presented from 79 experiments conducted under clear sky conditions. Validation involved predicting the at-sensor radiance for each band using a radiative transfer model, driven by surface and atmospheric measurements from each experiment, and then comparing the predicted radiance with the ASTER measured radiance. The results indicate the average difference between the predicted and the ASTER measured radiances was no more than 0.5% or 0.4 K in any TIR band, demonstrating that the TIR bands have exceeded the preflight design accuracy of <1 K for an at-sensor brightness temperature range of 270-340 K. The predicted and the ASTER measured radiances were then used to assess how well the onboard calibration accounted for any changes in both the instrument gain and offset over time. The results indicate that the gain and offset were correctly determined using the onboard blackbody, and indicate a responsivity decline over the first 1400 days of the Terra mission.     

Accurate atmospheric correction of ASTER thermal infrared imagery using the WVS method

The water vapor scaling (WVS) method involves an atmospheric correction algorithm for thermal infrared (TIR) multispectral data, designed mainly for the five TIR spectral bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on the Terra satellite. First, this method is improved for better applicability to ASTER/TIR imagery. The major improvement is the determination of a water vapor scaling factor on a band-by-band basis, which can reduce most of the errors induced by various factors such as algorithm assumptions. Next, the WVS method is validated by assessing the surface temperature and emissivity retrieved for a global-based simulation model (416 448 conditions), 183 ASTER scenes selected globally, and ASTER scenes from two test sites, Hawaii Island and Tokyo Bay. In situ lake surface temperatures measured in 13 vicarious calibration experiments, Moderate Resolution Imaging Spectroradiometer sea surface temperature products, and a climatic lake temperature are also used in validation. All the results indicate that although the ASTER/TIR standard atmospheric correction algorithm performs less well in humid conditions, the WVS method will provide more accurate retrieval of surface temperature and emissivity in most conditions including notably humid conditions. The expected root mean square error is about 0.6 K in temperature. Since the WVS method will be degraded by errors in gray pixel selection and cloud detection, these processing steps should be applied accurately.     

Onboard calibration of the ASTER instrument

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution optical sensor for observing the Earth carried on the National Aeronautics and Space Administration Terra satellite. ASTER consists of three radiometers covering the following regions: visible and near-infrared (VNIR), shortwave infrared (SWIR), and thermal infrared (TIR). The preflight calibration of VNIR and SWIR utilized standard large integrating spheres whose radiance levels were traceable to primary standard fixed-point blackbodies. The onboard calibration devices for the VNIR and SWIR consist of two halogen lamps with photodiode monitors. In orbit, all three bands of the VNIR showed rapid decreases in the output signal while all SWIR bands remained stable. The TIR onboard blackbody was calibrated against a standard blackbody from 100-400 K in a vacuum chamber before launch. The TIR is unable to see the dark space. The temperature of the TIR onboard blackbody remains at 270 K for a short-term calibration to determine any offset and is varied from 270-340 K for a long-term calibration of both the offset and gain. The long-term calibration just after launch was consistent with the prelaunch calibration but then showed a steady decrease of the TIR response over the five years of operation to date.     

Validation of ASTER/TIR standard atmospheric correction using water surfaces

The standard atmospheric correction algorithm for the five thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is based on radiative transfer calculation using the MODTRAN code. Atmospheric profiles input to MODTRAN are extracted from either the Global Data Assimilation System (GDAS) product or the Naval Research Laboratory (NRL) climatology model. The present study provides validation results of this algorithm. First, in situ lake surface temperatures measured in 13 vicarious calibration (VC) experiments were compared with surface temperatures retrieved from ASTER data. As the results, the mean bias was 0.8 and 1.8 K for GDAS and NRL, respectively. The NRL model performed worse than GDAS for four experiments at Salton Sea, CA, probably because the model was not suitable for this site, which has typically higher surface temperature and humidity than other VC sites. Next, the algorithm was validated based on the max-min difference (MMD) of water surface emissivity retrieved from each of 163 scenes acquired globally. As a result, the algorithm error increased quadratically with the precipitable water vapor (PWV) content of the atmosphere, and the expected MMD error was 0.049 and 0.067 for GDAS and NRL, respectively, with a PWV of 3 cm, where 0.05 on MMD is roughly corresponding to -0.8 or +2.3 K on the retrieved surface temperature error. The algorithm performance degraded markedly when the surface temperature exceeded about 25/spl deg/C, particularly for NRL. Consequently, GDAS performs better than NRL as expected, while both will perform less well for humid conditions.     

ASTER preflight and inflight calibration and the validation ofLevel 2 products

Describes the preflight and inflight calibration approaches used for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The system is a multispectral, high-spatial resolution sensor on the Earth Observing System's EOS-AM1 platform. Preflight calibration of ASTER uses well-characterized sources to provide calibration and preflight round-robin exercises to understand biases between the calibration sources of ASTER and other EOS sensors. These round-robins rely on well-characterized, ultra-stable radiometers. An experiment field in Yokohama, Japan, showed that the output from the source used for the visible and near-infrared (VNIR) subsystem of ASTER may be underestimated by 1.5%, but this is still within the 4% specification for the absolute, radiometric calibration of these bands. Inflight calibration will rely on vicarious techniques and onboard blackbodies and lamps. Vicarious techniques include ground-reference methods using desert and water sites. A recent joint field campaign gives confidence that these methods currently provide absolute calibration to better than 5%, and indications are that uncertainties less than the required 4% should be achievable at launch. The EOS-AM1 platform will also provide a spacecraft maneuver that will allow ASTER to see the Moon, allowing further characterization of the sensor. A method for combining the results of these independent calibration results is presented. The paper also describes the plans for validating the Level 2 data products from ASTER. These plans rely heavily upon field campaigns using methods similar to those used for the ground-reference, vicarious calibration methods     

Radiometric performance evaluation of ASTER VNIR, SWIR, and TIR

Radiometric performance of the Advanced Spectrometer for Thermal Emission and Reflection Radiometer (ASTER) is characterized by using acquired imagery data. Noise-equivalent reflectance and temperature, sensitivity (gain), bias (offset), and modulation transfer function (MTF) are determined for the visible and near-infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR) radiometers that constitute ASTER. The responsivity evaluated from onboard calibration (OBC) and from instrumented scenes show similar trends for the VNIR: the OBC data yield 2.7% to 5.5% a year for the VNIR. The SWIR response changed less than 2% in the 3.5 years following launch. The zero-radiance offsets of most VNIR and SWIR bands have increased about 1/2 digital number per year. The in-orbit noise levels, calculated by the standard deviation of dark (VNIR and SWIR) or ocean (TIR) scenes, show that all bands are within specification. The MTF at Nyquist and 1/2 Nyquist frequencies was determined for all bands using the Moon (VNIR and SWIR) or terrestrial scenes with lines of sharp thermal contrast. In-orbit performance along-track and cross-track is better than prelaunch for the VNIR and SWIR bands in nearly all cases; the TIR effectively meets specification in-orbit.     

Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor

As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.     

Vicarious calibration of GLI by ground observation data

We conducted vicarious calibration of the Global Imager (GLI) in visible to near-infrared channels over different targets. For calibration over the ocean, we used the normalized water-leaving radiance derived from the Marine Optical Buoy (MOBY) and the aerosol optical properties (aerosol optical depth, size distribution, and refractive index) obtained through the Aerosol Robotic Network (AERONET). For calibration over land, we used the ground-based measurement data at Railroad Valley Playa. The following GLI characteristics are recognized from the calibration results. First, GLI underestimates the radiance in channels 1, 2, 4, and 5. Next, in the near-infrared channels, there is good agreement between the observed and simulated radiance over bright targets. On the other hand, it is suggested that the GLI overestimates the radiance over dark targets (e.g., on the order of 15% at 4.0 W/m/sup 2///spl mu/m/sr in channels 18 and 19). Furthermore, we evaluated these calibration results over different targets taking into account the difference in the target radiance and in the accuracy between the two results. This combined evaluation of vicarious calibration results suggests the possibility that the GLI-observed radiance has offset radiance versus the simulated radiance.     

Terra MODIS on-orbit spectral characterization and performance

The Moderate Resolution Imaging Spectroradiometer (MODIS) protoflight model onboard the National Aeronautics and Space Administration's Earth Observing System Terra spacecraft has been in operation for over five years since its launch in December 1999. It makes measurements using 36 spectral bands with wavelengths from 0.41 to 14.5 /spl mu/m. Bands 1-19 and 26 with wavelengths below 2.2 /spl mu/m, the reflective solar bands (RSBs), collect daytime reflected solar radiance at three nadir spatial resolutions: 0.25 km (bands 1-2), 0.5 km (bands 3-7), and 1 km (bands 8-19 and 26). Bands 20-25 and 27-36, the thermal emissive bands, collect both daytime and nighttime thermal emissions, at 1-km nadir spatial resolution. The MODIS spectral characterization was performed prelaunch at the system level. One of the MODIS onboard calibrators, the Spectroradiometric Calibration Assembly (SRCA), was designed to perform on-orbit spectral characterization of the MODIS RSB. This paper provides a brief overview of MODIS prelaunch spectral characterization, but focuses primarily on the algorithms and results of using the SRCA for on-orbit spectral characterization. Discussions are provided on the RSB center wavelength measurements and their relative spectral response retrievals, comparisons of on-orbit results with those from prelaunch measurements, and the dependence of center wavelength shifts on instrument temperature. For Terra MODIS, the center wavelength shifts over the past five years are less than 0.5 nm for most RSBs, indicating excellent stability of the instrument's spectral characteristics. Similar spectral performance has also been obtained from the Aqua MODIS (launched in May 2002) SRCA measurements.     

An atmospheric correction algorithm for thermal infraredmultispectral data over land-a water-vapor scaling method

Thermal infrared (TIR) multispectral data over land can be atmospherically corrected by radiative transfer calculations combined with global assimilated data from a weather forecast system. This approach is advantageous to operational processing but is not accurate. A new atmospheric correction algorithm with global assimilated data, a water vapor scaling (WVS) method, has improved results. In this algorithm, the accuracy of global assimilated data is markedly improved on a pixel-by-pixel basis as follows: (1) selecting gray pixels from an image; (2) estimating the scaling factors for the water-vapor profiles of gray pixels by an improved multichannel algorithm; (3) estimating the scaling factors for the water-vapor profiles of nongray pixels by horizontal interpolation; and (4) improving the water-vapor profiles of all pixels with the scaling factors. The proposed method can be applied if the image has one or more gray pixels. The simulation results for the advanced spaceborne thermal emission and reflection radiometer (ASTER) TIR subsystem show that the proposed method reduces errors on air temperature profiles as well as on water-vapor profiles and is as accurate as atmospheric correction with radiosonde measurements     

Autonomous atmospheric compensation (AAC) of high resolution hyperspectral thermal infrared remote-sensing imagery

Atmospheric emission and absorption significantly modify the thermal infrared (TIR) radiation spectra from Earth's land surface. A new algorithm, autonomous atmospheric compensation (AAC), was developed to estimate and compensate for the atmospheric effects. The algorithm estimates from hyperspectral TIR measurements two atmospheric index parameters, the transmittance ratio, and the path radiance difference between strong and weak absorption channels near the 11.73 /spl mu/m water band. These two parameters depend on the atmospheric water and temperature distribution profiles, and thus, from them, the complete atmospheric transmittance and path radiance spectra can be predicted. The AAC algorithm is self-contained and needs no supplementary data. Its accuracy depends largely on instrument characteristics, particularly spectral and spatial resolution. Atmospheric conditions, especially humidity and temperature, and other meteorological parameters, also have some secondary impacts. The AAC algorithm was successfully applied to a hyperspectral TIR data set, and the results suggest its accuracy is comparable to that based on the in situ radiosonde measurements.     

A temperature and emissivity separation algorithm for AdvancedSpaceborne Thermal Emission and Reflection Radiometer (ASTER)images

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scanner on NASA's Earth Observing System (EOS)-AM1 satellite (launch scheduled for 1998) will collect five bands of thermal infrared (TIR) data with a noise equivalent temperature difference (NEΔT) of ⩽0.3 K to estimate surface temperatures and emissivity spectra, especially over land, where emissivities are not known in advance. Temperature/emissivity separation (TES) is difficult because there are five measurements but six unknowns. Various approaches have been used to constrain the extra degree of freedom. ASTER's TES algorithm hybridizes three established algorithms, first estimating the normalized emissivities and then calculating emissivity band ratios. An empirical relationship predicts the minimum emissivity from the spectral contrast of the ratioed values, permitting recovery of the emissivity spectrum. TES uses an iterative approach to remove reflected sky irradiance. Based on numerical simulation, TES should be able to recover temperatures within about ±1.5 K and emissivities within about ±0.015. Validation using airborne simulator images taken over playas and ponds in central Nevada demonstrates that, with proper atmospheric compensation, it is possible to meet the theoretical expectations. The main sources of uncertainty in the output temperature and emissivity images are the empirical relationship between emissivity values and spectral contrast, compensation for reflected sky irradiance, and ASTER's precision, calibration, and atmospheric compensation     

Stereo Cloud Heights From Multispectral IR Imagery via Region-of-Interest Segmentation

Multispectral thermal imagery acquired from low Earth orbit was used to develop a method of cloud-height determination that applies image brightness temperature histograms and region-of-interest (ROI) image segmentation as a processing step prior to stereo-height retrieval. The National Aeronautics and Space Administration's Infrared Spectral Imaging Radiometer (ISIR) acquired all imagery during the August 1997 STS-85 mission of the Space Shuttle Discovery. ISIR, the first Earth-observing spectroradiometer to employ an uncooled large-format microbolometer-array focal plane, provided continuous coverage in four spectral bands along track in an 80-km-wide swath. ROI segmentation created binary cloud masks ranging over brightness temperatures in the imagery for which the parallax was determined by a two-dimensional correlation method, allowing stereo heights to be determined using the standard parallax equations. A subpixel parallax algorithm allowed stereo heights to be determined with a precision of roughly$pm$0.39 km for clouds in the observed altitude range of 0.5–10 km.     

Infrared radiation measurement of the aerial target based on temperature calibration and target images

Inthe last several decades ,a lot of theoretical studiesoninfrared radiation measurement of aerial targets hadbeen carried out .Undoubtedly,the measurement meansby theory modeling according to the thermal radiationlawplay ani mportant rolein many cases .H…     

Spectral linear mixing model in low spatial resolution image data

Different ways to estimate the spectral reflectance for the component classes in a mixture problem have been proposed in the literature (pure pixels, spectral library, field measurements). One of the most common approaches consists in the use of pure pixels, i.e., pixels that are covered by a single component class. This approach presents the advantage of allowing the extraction of the components' reflectance directly from the image data. This approach, however, is generally not feasible in the case of low spatial resolution image data, due to the large ground area covered by a single pixel. In this paper, a methodology aiming to overcome this limitation is proposed. The proposed approach makes use of the spectral linear mixing model. In the proposed methodology, the components' proportions in image data are estimated using a medium spatial resolution image as auxiliary data. The linear mixing model is then solved for the unknown spectral reflectances. Experiments are presented, using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus, as low and medium spatial resolution image data, respectively, acquired on the same date over the Tapajos study site, Brazilian Amazon. Three component classes or endmembers are present in the scene covered by the experiment, namely vegetation, exposed soil, and shade. The components' spectral reflectance for the Terra MODIS spectral bands were then estimated by applying the proposed methodology. The reliability of these estimates is appraised by analyzing scatter diagrams produced by the Terra MODIS spectral bands and also by comparing the fraction images produced using both image datasets. This methodology appears appropriate for up-scaling information for regional and global studies.     

An off-nadir-pointing imaging spectroradiometer for terrestrialecosystem studies

The Advanced Solid-state Array Spectroradiometer (ASAS), an airborne, off-nadir-pointing imaging spectroradiometer used to acquire bidirectional radiance data for terrestrial targets, is described. As its platform aircraft flies over a target, the sensor can image the target through a sequence of at least seven fore-to-aft view directions ranging up to 45° on either side of nadir. ASAS acquires data for 29 spectral bands in the visible and near-infrared portions of the spectrum (465 to 871 nm) with a resolution of 15 nm. The basic ASAS data product is a sequence of digital images acquired from multiple view directions and consisting of calibrated spectral radiance values. Examples of ASAS data from field experiments are presented. The data demonstrate the combined effects of reflectance anisotropy and increased atmospheric path length on off-nadir observations. One result of these effects is a variation in vegetation indices as a function of view direction     

Stochastic model-based processing for detection of small targets innon-Gaussian natural imagery

Stochastic background models incorporating spatial correlations can be used to enhance the detection of targets in natural terrain imagery, but are generally difficult to apply when the statistics are non-Gaussian. Chapple and Bertilone (see Opt. Commun., vol.150, p.71-76, 1998) proposed a simple stochastic model for images of natural backgrounds based on the pointwise nonlinear transformation of Gaussian random fields, and demonstrated its effectiveness and computational efficiency in modeling the textures found in natural terrain imagery acquired from airborne IR sensors. In this paper, we show how this model can be used to design algorithms that detect small targets (up to several pixels in size) in natural imagery by identifying anomalous regions of the image where the statistics differ significantly from the rest of the background. All of the model-based algorithms described here involve nonlinear spatial processing prior to the final decision threshold. Monte Carlo testing reveals that the model-based algorithms generally perform better than both the adaptive threshold filter and the generalized matched filter for detecting low-contrast targets, despite the fact that they do not require the target statistics needed for constructing the matched filter.     

Overview of Advanced Spaceborne Thermal Emission and ReflectionRadiometer (ASTER)

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a research facility instrument provided by the Ministry of International Trade and Industry (MITI), Tokyo, Japan to be launched on NASA's Earth Observing System morning (EOS-AM1) platform in 1998. ASTER has three spectral hands in the visible near-infrared (VNIR), six bands in the shortwave infrared (SWIR), and five bands in the thermal infrared (TIR) regions, with 15-, 30-, and 90-m ground resolution, respectively. The VNIR subsystem has one backward-viewing band for stereoscopic observation in the along-track direction. Because the data will have wide spectral coverage and relatively high spatial resolution, it will be possible to discriminate a variety of surface materials and reduce problems in some lower resolution data resulting from mixed pixels. ASTER will, for the first time, provide high-spatial resolution multispectral thermal infrared data from orbit and the highest spatial resolution surface spectral reflectance temperature and emissivity data of all of the EOS-AM1 instruments. The primary science objective of the ASTER mission is to improve understanding of the local- and regional-scale processes occurring on or near the Earth's surface and lower atmosphere, including surface-atmosphere interactions. Specific areas of the science investigation include the following: (1) land surface climatology; (2) vegetation and ecosystem dynamics; (3) volcano monitoring; (4) hazard monitoring; (5) aerosols and clouds; (6) carbon cycling in the marine ecosystem; (7) hydrology; (8) geology and soil; and (9) land surface and land cover change. There are three categories of ASTER data: a global map, regional monitoring data sets, and local data sets to be obtained for requests from individual investigators     

Vicarious calibration experiment in support of the Multi-angle Imaging SpectroRadiometer

On June 11, 2000, the first vicarious calibration experiment in support of the Multi-angle Imaging SpectroRadiometer (MISR) was conducted. The purpose of this experiment was to acquire in situ measurements of surface and atmospheric conditions over a bright, uniform area. These data were then used to compute top-of-atmosphere (TOA) radiances, which were correlated with the camera digital number output, to determine the in-flight radiometric response of the on-orbit sensor. The Lunar Lake Playa, Nevada, was the primary target instrumented by the Jet Propulsion Laboratory for this experiment. The airborne MISR simulator (AirMISR) on board a NASA ER-2 acquired simultaneous observations over Lunar Lake. The in situ estimations of top-of-atmosphere radiances and AirMISR measurements at a 20-km altitude were in good agreement with each other and differed by 9% from MISR measurements. The difference has been corrected by adjusting the gain coefficients used in MISR standard product generation. Data acquired simultaneously by other sensors, such as Landsat, the Terra Moderate-Resolution Imaging SpectroRadiometer (MODIS), and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS), were used to validate this correction. Because of this experiment, MISR radiances are 9% higher than the values based on the on-board calibration. Semiannual field campaigns are planned for the future in order to detect any systematic trends in sensor calibration.     

ASTER geometric performance

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) system acquires multispectral images ranging from the visible to thermal infrared region. The ASTER system consists of three subsystems: visible and near-infrared (VNIR), short-wave infrared (SWIR) and thermal infrared (TIR) radiometers. The VNIR subsystem has a backward-viewing telescope as well as a nadir one. To deliver data products of high quality from the viewpoint of geolocation and band-to-band registration performance, a fundamental program, called Level-1 data processing, has been developed for images obtained using four telescopes with a cross-track pointing function. In this work, the methodology of the geometric validation is first described. Next, the image quality of ASTER data products is evaluated in view of the geometric performance over a period of four years. The band-to-band registration accuracy in the subsystem is better than 0.1 pixels and that between subsystems is better than 0.2 pixels. This means that the geometric database is determined accurately and the image matching method based on a cross-correlation function is effective in the operational usage.