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.     

Inflight straylight analysis for ASTER thermal infrared bands

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument was launched into Earth orbit on the Terra platform in late 1999. ASTER produces images of the Earth in 14 spectral bands including five bands in the thermal infrared (TIR) part of the electromagnetic spectrum (8-12 /spl mu/m). On one occasion ASTER was used to image the Moon as part of the long-term calibration strategy for instruments on the Terra platform. Analysis of the imagery revealed that the TIR band had noticeable straylight effects (ghosting), and an algorithm was developed to correct for these effects. The algorithm was applied to ASTER/TIR images acquired over a vicarious calibration (VC) site at Cold Springs Reservoir (CSR), NV. Data from CSR had been evaluated in three previous VC experiments and showed large unexplained differences between the ASTER image radiance and vicarious predicted radiance not observed in other larger, more laterally homogenous sites. After straylight correction the vicarious and image radiances were in good agreement. A further comparison with nearly simultaneous airborne TIR data acquired with the MODIS/ASTER (MASTER) sensor indicated that the ASTER straylight corrected data also agreed with the airborne data. Finally, the algorithm was applied to artificially created models. The results indicated that a radiance change caused by straylight reached 6% to 8% of a radiance contrast for a smaller square target than 10/spl times/10 pixels or a narrower line target than five pixels. Straylight in ASTER/TIR imagery may not be very large for most targets, but may become an error factor for high-radiance-contrast targets.     

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.     

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.     

Atmospheric correction of ASTER

An atmospheric correction algorithm for operational use for the high-spatial resolution, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is presented. The correction is a straightforward approach relying on inputs from other satellite sensors to determine the atmospheric characteristics of the scene to be corrected. Methods for the solar reflective and thermal infrared (TIR) are presented separately. The solar-reflective approach uses a lookup table (LUT) based on output from a Gauss-Seidel iteration radiative transfer code. A method to handle adjacency effects is included that relies on model output, assuming a checkerboard surface. An example of a numerical simulation shows that the effect of a land surface on the radiance over the ocean is stronger just off the coastal zone and decreases exponentially with increasing distance from the land. A typical numerical simulation is performed over the Tsukuba lake area in Japan. The TIR approach relies on the radiative transfer code Moderate Resolution Atmospheric Radiance and Transmittance Model (MODTRAN). The code is run for a given set of atmospheric conditions for multiple locations in the scene for several representative elevations. Pixel-by-pixel radiances are then found using spatial interpolation. Sensitivity analysis of the methods indicate that the results of the atmospheric correction will be limited by the accuracies of the input parameters     

Terra MODIS on-orbit spatial characterization and performance

The Moderate Resolution Imaging Spectroradiometer (MODIS) Proto-Flight Model, onboard the National Aeronautics and Space Administration's Earth Observing System Terra spacecraft, has been in operation for over four years. It has 36 spectral bands and a total of 490 detectors located on four focal plane assemblies (FPAs). MODIS makes observations at three spatial resolutions (nadir): 0.25 km (bands 1-2), 0.5 km (bands 3-7), and 1 km (bands 8-36). The instrument's spatial characterization was measured prelaunch using an integration and alignment collimator. Parameters measured included the detectors' instantaneous field-of-view (IFOV), band-to-band registration (BBR), and line spread function in both the along-scan and along-track directions. On-orbit, the spatial characterization is periodically measured using the onboard spectro-radiometric calibration assembly (SRCA). This paper describes the SRCA BBR algorithms, characterization methodologies, and on-orbit results. A Fourier approach used to calculate the along-track BBR is also described. This approach enhances the algorithm's robustness in comparison with the conventional centroid approach. On-orbit results show that the Terra MODIS focal planes shifted slightly during launch and initial on-orbit operation. Since then they have been very stable. The BBR is within 0.16 km (nadir IFOV) in the along-scan direction and 0.23 km (nadir IFOV) in the along-track direction among all bands. The small but noticeable periodic variation of the on-orbit BBR can be attributed to the annual cycling of instrument temperature due to Sun-Earth distance variation. The visible FPA position has the largest temperature dependence among all FPAs, 17 m/K along-scan and 0.6 m/K along-track.     

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     

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.     

MODIS On-Orbit Spatial Characterization Using Ground Targets

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is currently being operated on both Terra and Aqua spacecrafts. MODIS uses 36 bands arranged in four focal plane assemblies (FPAs)—visible, near infrared, short- and middle-wavelength infrared, and long-wavelength infrared. Misregistrations between spectral bands and FPAs and changes of spatial characterization on-orbit could impact the quality of science data products generated with multiple bands located on different FPAs. In this paper, an approach is presented to compute the MODIS band-to-band registration (BBR) using ground measurements. A special ground scene with unique features is selected to calculate the spatial registration along-scan and along-track. The monthly and yearly spatial deviations are calculated for the bands of both Terra and Aqua MODIS except for some ocean bands, cloud bands, and the Aqua MODIS band 6. The comparison with results derived from the spectroradiometric calibration assembly, a device operated on-orbit to track the BBR shift between any two of the spectral bands, generally shows good agreement. The measured differences between these two approaches are typically less than 100 m in the scan direction and 200 m in the track direction. This approach can provide more frequent characterization of the MODIS BBR and is extremely useful for other sensors that do not have an onboard spatial characterization device.      

Estimating Broadband Emissivity of Arid Regions and Its Seasonal Variations Using Thermal Infrared Remote Sensing

Surface emissivity in the thermal infrared region is an important parameter for determining the surface radiation budget in climate, weather, and hydrological models. This paper focuses on estimating the spatial and temporal variations of the surface emissivities using thermal infrared remotely sensed data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite. We developed a regression approach to use the ASTER and MODIS data for estimating the broadband emissivity (BBE; 8-13.5 mum). The regressions were calibrated using a library of spectral emissivity data for terrestrial materials. We applied these regressions to ASTER and MODIS data to obtain emissivity maps for several arid regions of the Earth. In the 8-9-mum band for sparsely or nonvegetated desert areas, emissivity values between 0.66 and 0.96 have been observed, which are due to the low emissivity of quartz-rich sands at these wavelengths. As a result, the range of BBE is between 0.86 and 0.96. The seasonal variation over a two-year period and the dependence on land cover/soil type were also investigated.     

MODIS Polarization-Sensitivity Analysis

The moderate resolution imaging spectroradiometer (MODIS) is one of the primary instruments in the Earth Observing System (EOS). Currently, MODIS instruments are onboard the NASA EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. The MODIS reflective solar bands (RSBs) are sensitive to the polarization of incident light, particularly for the visible bands. To derive accurate top-of-the-atmosphere radiances, it is essential to know the polarization sensitivity, characterized by a polarization factor and phase angle, of the instruments. From prelaunch polarization sensitivity measurements, the polarization factors and phase angles for all visible and near-infrared bands of both instruments are derived, analyzed, and compared. The polarization factors are wavelength, angle of incidence on the MODIS scan mirror, and detector-dependent. For Terra MODIS, they are also mirrorside-dependent. The 412-nm band has the largest polarization factor, which is about 0.04 for both instruments. The polarization factors of all other bands are either smaller than or close to 0.02, which is the polarization requirement for the MODIS RSB whose wavelengths are longer than 412 nm. The unexpected one-, three-, and four-cycle anomalies observed in the measurements are analyzed. These anomalies are shown to be likely due to the nonuniformity of the light source and the retro-reflected light from the MODIS optical system. Their impacts on the derived polarization parameters are estimated and discussed.     

A Neural Network Technique for Separating Land Surface Emissivity and Temperature From ASTER Imagery

Four radiative transfer equations for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands 11, 12, 13, and 14 are built involving six unknowns (average atmospheric temperature, land surface temperature, and four band emissivities), which is a typical ill-posed problem. The extra equations can be built by using linear or nonlinear relationship between neighbor band emissivities because the emissivity of every land surface type is almost constant for bands 11, 12, 13, and 14. The neural network (NN) can make full use of potential information between band emissivities through training data because the NN simultaneously owns function approximation, classification, optimization computation, and self-study ability. The training database can be built through simulation by MODTRAN4 or can be obtained from the reliable measured data. The average accuracy of the land surface temperature is about 0.24 K, and the average accuracy of emissivity in bands 11, 12, 13, and 14 is under 0.005 for test data. The retrieval result by the NN is, on average, higher by about 0.7 K than the ASTER standard product (AST08), and the application and comparison indicated that the retrieval result is better than the ASTER standard data product. To further evaluate self-study of the NN, the ASTER standard products are assumed as measured data. After using AST09, AST08, and AST05 (ASTER Standard Data Product) as the compensating training data, the average relative error of the land surface temperature is under 0.1 K relative to the AST08 product, and the average relative error of the emissivity in bands 11, 12, 13, and 14 is under 0.001 relative to AST05, which indicates that the NN owns a powerful self-study ability and is capable of suiting more conditions if more reliable and high-accuracy ASTER standard products can be compensated.     

夜间天空背景及云层红外辐射测量分析

采用中波、长波红外热像仪对夜间无云天空背景及云层背景红外辐射亮度进行了测量。无云天空背景中波波段辐射亮度在0.58~1.30 W·m-2·sr-1,长波波段辐射亮度在6.61~15.29 W·m-2·sr-1。由于夜间条件下无太阳辐射影响,相同俯仰观测角条件下,0°~360°各个方向天空背景辐射亮度基本一致。从无云区到有云区,随着云层厚度的增加,其辐射亮度逐渐增大。相对于无云背景,中波波段云层中心辐射亮度增加了1.5%,长波波段云层中心辐射亮度增加了14.2%,长波波段云层对天空背景辐射影响更加显著。     

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 DEM performance

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument onboard the National Aeronautics and Space Administration's Terra spacecraft has an along-track stereoscopic capability using its a near-infrared spectral band to acquire the stereo data. ASTER has two telescopes, one for nadir-viewing and another for backward-viewing, with a base-to-height ratio of 0.6. The spatial resolution is 15 m in the horizontal plane. Parameters such as the line-of-sight vectors and the pointing axis were adjusted during the initial operation period to generate Level-1 data products with a high-quality stereo system performance. The evaluation of the digital elevation model (DEM) data was carried out both by Japanese and U.S. science teams separately using different DEM generation software and reference databases. The vertical accuracy of the DEM data generated from the Level-1A data is 20 m with 95% confidence without ground control point (GCP) correction for individual scenes. Geolocation accuracy that is important for the DEM datasets is better than 50 m. This appears to be limited by the spacecraft position accuracy. In addition, a slight increase in accuracy is observed by using GCPs to generate the stereo data.     

Design and preflight performance of ASTER instrument protoflightmodel

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an advanced multispectral imager with high spatial, spectral, and radiometric resolution, built to fly on the EOS-AM1 spacecraft along with four other instruments, which will be launched in 1998. The ASTER instrument covers a wide spectral region, from visible to thermal infrared with 14 spectral bands. To meet the wide spectral coverage, optical sensing units of ASTER are separated into three subsystems: visible and near-infrared (VNIR) subsystem, shortwave infrared (SWIR) subsystem, and thermal infrared (TIR) subsystem. ASTER also has an along-track stereoscopic viewing capability using one of the near-infrared bands. To acquire the stereo data, the VNIR subsystem has two telescopes, one for nadir and another for backward viewing. Several new technologies are adopted as design challenges to realize high performance. Excellent observational performances are obtained by a pushbroom VNIR radiometer with a high spatial resolution of 15 m, a pushbroom SWIR radiometer with high spectral resolution, and a whiskbroom-type TIR radiometer with high spatial, spectral, and radiometric resolutions. The preflight performance is evaluated through a protoflight model (PFM)     

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.     

光学遥感成像系统全链路仿真框架研究

针对光学遥感成像系统的全链路仿真在我国刚刚起步。通过分析能量在大气、场景和遥感器之间传递时发生的各种相互作用,将整个仿真过程分为三维场景构建与组织、遥感器入瞳处辐亮度图像模拟、遥感器效果模拟三部分,分析了框架中各个模块的功能和模块之间的概念数据流向。最后分析了地形起伏和观测角度变化对成像的影响,计算显示：像元高度从0增至1 km时,入瞳处辐亮度的最大相对差异可达170%;观测天顶角分别从180°变为124.4°时,辐亮度的相对差异最大可接近50%。     

AIRS/AMSU/HSB validation

The Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for Brazil (AIRS/AMSU/HSB) instrument suite onboard Aqua observes infrared and microwave radiances twice daily over most of the planet. AIRS offers unprecedented radiometric accuracy and signal to noise throughout the thermal infrared. Observations from the combined suite of AIRS, AMSU, and HSB are processed into retrievals of atmospheric parameters such as temperature, water vapor, and trace gases under all but the cloudiest conditions. A more limited retrieval set based on the microwave radiances is obtained under heavy cloud cover. Before measurements and retrievals from AIRS/AMSU/HSB instruments can be fully utilized they must be compared with the best possible in situ and other ancillary "truth" observations. Validation is the process of estimating the measurement and retrieval uncertainties through comparison with a set of correlative data of known uncertainties. The ultimate goal of the validation effort is retrieved product uncertainties constrained to those of radiosondes: tropospheric rms uncertainties of 1.0 degC over a 1-km layer for temperature, and 10% over 2-km layers for water vapor. This paper describes the data sources and approaches to be used for validation of the AIRS/AMSU/HSB instrument suite, including validation of the forward models necessary for calculating observed radiances, validation of the observed radiances themselves, and validation of products retrieved from the observed radiances. Constraint of the AIRS product uncertainties to within the claimed specification of 1 K/1 km over well-instrumented regions is feasible within 12 months of launch, but global validation of all AIRS/AMSU/HSB products may require considerably more time due to the novelty and complexity of this dataset and the sparsity of some types of correlative observations.     

Quantifying Uncertainty in Modeling Snow Microwave Radiance for a Mountain Snowpack at the Point-Scale, Including Stratigraphic Effects

Merging microwave radiances and modeled estimates of snowpack states in a data assimilation scheme is a potential method for snowpack characterization. A radiance assimilation scheme for snow requires a land surface model (LSM) coupled to a radiative transfer model (RTM). In this paper, we explore the degree of model fidelity required in order for radiance assimilation to yield benefits for snowpack characterization. Specifically, we characterize the uncertainty of Microwave Emission Model for Layered Snowpacks (MEMLS) radiance predictions by quantifying model accuracy and sensitivity to the following: (1) the LSM snowpack layering scheme and (2) the properties of the snow layers, including melt-refreeze ice layers. MEMLS was consistent with the measured brightness temperatures at 18.7 and 36.5 GHz with a bias (mean absolute error) of 0.1 K (3.1 K) for the vertical polarization and 3.4 K (9.3 K) for the horizontal polarization. An error in the predictions at horizontal polarization is due to uncertainty in ice-layer properties. It was found that in order for predicted brightness temperatures from the coupled LSM and RTM to be adequate for radiance assimilation purposes, the following must be satisfied: (1) the LSM snowpack layering scheme must accurately represent the stratigraphic snowpack layers; (2) dynamics of melt-refreeze ice layers must be modeled explicitly, and the predicted density of melt-refreeze layers must be accurate within ; and (3) the MEMLS correlation length must be predicted within 0.016 mm, or effective optical grain diameter must be predicted within 0.045 mm. Recommendations for future field measurements are made.