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NASA NTRS2018

6DOF Testing of the SLS Inertial Navigation Unit

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). Because the navigation architecture for the SLS Block 1 vehicle is a purely inertial system, the accuracy of the achieved orbit relative to mission requirements is very sensitive to initial alignment accuracy. The assessment of this sensitivity and many others via simulation is a part of the SLS Model-Based Design and Model-Based Requirements approach. As a part of the aforementioned, 6DOF Monte Carlo simulation is used in large part to develop and demonstrate verification of program requirements. To facilitate this and the GN&C flight software design process, an SLS-Program-controlled Design Math Model (DMM) of the SLS INS was developed by the SLS Navigation Team. The SLS INS model implements all of the key functions of the hardware-namely, GCA, inertial navigation, and FDIR (Fault Detection, Isolation, and Recovery)-in support of SLS GN&C design requirements verification. Despite the strong sensitivity to initial alignment, GCA accuracy requirements were not verified by test due to program cost and schedule constraints. Instead, the system relies upon assessments performed using the SLS INS model. In order to verify SLS program requirements by analysis, the SLS INS model is verified and validated against flight hardware. In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Geohagan, Kevin↗

DOE OSTI2016

Ppb-level mid-infrared ethane detection based on three measurement schemes using a 3.34-μm continuous-wave interband cascade laser

A ppb-level mid-infrared ethane (C 2 H 6 ) sensor was developed using a continuous-wave, thermoelectrically cooled, distributed feedback interband cascade laser emitting at 3.34 μm and a miniature dense patterned multipass gas cell with a 54.6-m optical path length. The performance of the sensor was investigated using two different techniques based on the tunable interband cascade laser: direct absorption spectroscopy (DAS) and second-harmonic wavelength modulation spectroscopy (2f-WMS). Three measurement schemes, DAS, WMS and quasi-simultaneous DAS and WMS, were realized based on the same optical sensor core. A detection limit of ~7.92 ppbv with a precision of ±30 ppbv for the separate DAS scheme with an averaging time of 1 s and a detection limit of ~1.19 ppbv with a precision of about ±4 ppbv for the separate WMS scheme with a 4-s averaging time were achieved. An Allan–Werle variance analysis indicated that the precisions can be further improved to 777 pptv @ 166 s for the separate DAS scheme and 269 pptv @ 108 s for the WMS scheme, respectively. For the quasi-simultaneous DAS and WMS scheme, both the 2f signal and the direct absorption signal were simultaneously extracted using a LabVIEW platform, and four C 2 H 6 samples (0, 30, 60 and 90 ppbv with nitrogen as the balance gas) were used as the target gases to assess the sensor performance. A detailed comparison of the three measurement schemes is reported. Here, atmospheric C 2 H 6 measurements on the Rice University campus and a field test at a compressed natural gas station in Houston, TX, were conducted to evaluate the performance of the sensor system as a robust and reliable field-deployable sensor system.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

A 3D-Printed Microresonator Based on the Quartz-Enhanced Photoacoustic Spectroscopy Sensor for Methane Detection

A 3D-printed microresonator based on a quartz tuning fork has been developed. The sensor performance is evaluated by detection of methane with a fiber-coupled distributed feedback diode laser. In combination with wavelength modulation spectroscopy, a minimum detectable concentration of 15.6 ppb by volume is achieved at atmospheric pressure with an 8-mW average optical excitation power and a lock-in amplifier time constant of 1 s, which corresponds to a 1σ normalized noise equivalent absorption coefficient of 5·10{sup –9} cm{sup –1}·W/Hz{sup 1/2}. An Allan variance analysis shows that the system has long-term stability and can serve as the basis for a portable gas analyzer. Approaches to improve the current sensor performance are also discussed. This design greatly reduces the time of manufacturing the microresonator.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Partitioning of Recombinant Pseudomonas putida POS-F84 Proline Dehydrogenase in Aqueous Two-Phase Systems: Optimization Using Response Surface Methodology

Empirical modeling the partition behavior and recovery of a recombinant Pseudomonas putida POS-F84 proline dehydrogenase (ProDH) in aqueous two-phase systems (ATPS) was carried out by response surface methodology (RSM). Polyethylene glycol 1000 (PEG-1000) concentration, sodium carbonate concentration, and pH, which were the most important factors, were chosen for modeling the partition feature of enzyme. The adequacy of the models was investigated by means of variance analysis. Also, to confirm the efficiency of the ATPS in partition and purification of recombinant ProDH, purity and enzymatic activity was studied. After numerical optimization, an optimal ATPS composed of 14.33% PEG-1000 and 11.79% sodium carbonate at pH 7.48 was achieved. Yield, purification factor, and recovery were 81.41%, 60.82, and 270.82%, respectively. Purified recombinant ProDH was found as a single protein band into the upper PEG-rich phase and the specific activity was calculated to be 46.23 ± 2.1 U/mg. Collectively, our data showed that the RSM could be an appropriate and powerful tool to define the best ATPS system for recovery and purification of P. putida ProDH.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Developing methanogenic microbial consortia from diverse coal sources and environments

Biogenic gas production is a promising alternative or supplement to conventional methane extraction from coalbeds. Adsorbed and free gas, generated over geologic time, can be supplemented with biogenic gas during short-term engineering operations. There are two generic protocols for doing this. The first is to contact the coal with nutrients to support native bacterial development. The second approach is to inject appropriately cultured ex-situ consortia into subsurface coal accumulations. Research has mainly focused on the former: in-situ stimulation of native microbial communities with added nutrients. Relatively few studies have been conducted on the strategies for enriching ex-situ microbial populations under initial atmospheric exposure for subsequent injection into coal seams to stimulate biodegradation, and methanogenesis. In order to evaluate the feasibility of ex-situ cultivation, natural microbial populations were collected from various hydrocarbon-rich environments and locations characterized by natural methanogenesis. Different rank coals (i.e., lignite, sub-bituminous, bituminous), complex hydrocarbon sources (i.e., oil shale, waxy crude), hydrocarbon seeps, and natural biogenic environments were incorporated in the sampling. Three levels of screening (down-selection to high grade the most productive consortia) allowed selection of microbial populations, favorable nutrient amendments, sources of the microbial community, and quantification of methane produced from various coal types. Incubation periods of up to twenty-four weeks were evaluated at 23 °C. Headspace concentrations of CH 4 and CO 2 were analyzed by gas chromatography. After a two-week incubation period of the most promising microbes, generated headspace gas concentrations reached 873,400 ppm (154 sft 3 /ton or 4.8 scm 3 /g) for methane and 176,370 ppm (31 sft 3 /ton or 0.9 scm 3 /g) for carbon dioxide. Rudimentary statistical assessments – variance analysis (ANOVA) of a single factor - were used to identify trends and levels of significance or impact of the consortia enrichment. We then demonstrated that microbial communities from coal and lake sediments can be enriched and adapted to effectively generate methane under initial atmospheric exposure. The development and enrichment of these methanogenic consortia is described.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2015

Investigation and quantification of nonlinearity using surrogate data in a glow discharge plasma

Detection of nonlinearity has been carried out in periodic and aperiodic floating potential fluctuations of DC glow discharge plasma by generating surrogate data using iterative amplitude adjusted Fourier transform method. We introduce “delay vector variance” analysis (DVV) for the first time, which allows reliable detection of nonlinearity and provides some easy to interpret diagram conveying information about the nature of the experimental floating potential fluctuations (FPF). The method of false nearest neighbourhood is deployed on the FPF's to find a good embedding so as to be acquainted with the precise knowledge of m, which is desirable for carrying out DVV analysis. The emergence of nonlinearity with increase in discharge voltage has been ensured by taking into consideration the total energy present in different band of frequencies excited due to nonlinear processes. Rejection of null hypothesis has been verified by performing the rank test method that confirms the presence of nonlinearity quantitatively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Inferring thermal ion temperature and residual kinetic energy from nuclear measurements in inertial confinement fusion implosions

In inertial con finement fusion implosion experiments, the presence of residual anisotropic fluid motion within the stagnating hot spot leads to signifi cant variations in ion-temperature measurements using neutron time- of-flight detectors along different lines of sight. The minimum ion-temperature measurement is typically used as representative of the thermal temperature. In the presence of isotropic flows, however, even the minimum DT neutron-inferred ion temperature can be well above the plasma thermal temperature. Using both DD and DT neutron-inferred ion-temperature measurements, we show that it is possible to determine the contribution of isotropic flows and infer the DT burn-averaged thermal ion temperature. The contribution of large isotropic flows on driving the ratio of DD to DT neutron-inferred ion temperatures well below unity and approaching the lower bound of 0.8 is demonstrated in multimode simulations. The minimum DD neutron- inferred ion temperature is determined from the velocity variance analysis, accounting for the presence of isotropic flows. Being close to the DT burn-averaged thermal ion temperature, the inferred DD minimum ion temperatures demonstrate a strong correlation with the experimental yields in the OMEGA implosion database. An analytical expression is also derived to explain the effect of mode ℓ = 1 ion-temperature measurement asymmetry on yield degradations caused by the anisotropic flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2012

MORPHOLOGICAL EVOLUTION OF A THREE-DIMENSIONAL CORONAL MASS EJECTION CLOUD RECONSTRUCTED FROM THREE VIEWPOINTS

The propagation properties of coronal mass ejections (CMEs) are crucial to predict its geomagnetic effect. A newly developed three-dimensional (3D) mask fitting reconstruction method using coronagraph images from three viewpoints has been described and applied to the CME ejected on 2010 August 7. The CME's 3D localization, real shape, and morphological evolution are presented. Due to its interaction with the ambient solar wind, the morphology of this CME changed significantly in the early phase of evolution. Two hours after its initiation, it was expanding almost self-similarly. The CME's 3D localization is quite helpful to link remote sensing observations to in situ measurements. The investigated CME was propagating to Venus with its flank just touching STEREO B. Its corresponding interplanetary CME in the interplanetary space shows a possible signature of a magnetic cloud with a preceding shock in Venus Express (VEX) observations, while from STEREO B only a shock is observed. We have calculated three principal axes for the reconstructed 3D CME cloud. The orientation of the major axis is, in general, consistent with the orientation of a filament (polarity inversion line) observed by SDO/AIA and SDO/HMI. The flux rope axis derived by the Minimal Variance Analysis from VEX indicates a radial-directed axis orientation. It might be that locally only the leg of the flux rope passed through VEX. The height and speed profiles from the Sun to Venus are obtained. We find that the CME speed possibly had been adjusted to the speed of the ambient solar wind flow after leaving the COR2 field of view and before arriving at Venus. A southward deflection of the CME from the source region is found from the trajectory of the CME geometric center. We attribute it to the influence of the coronal hole where the fast solar wind emanated from.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Solar Cell Metallization Wear is Sensitive to Loading Frequency

Here, we performed cyclic loading of photovoltaic laminates with precracked silicon cells to explore if and how loading frequency and contact pressure influence the ensuing gridline wear-out process. A measurement of parallel resistance across cracked gridlines on a laminated cell coupon was used as the metric for gridline electrical contact degradation. A statistical analysis of variance (ANOVA) analysis of the experimental results discerned that loading frequency is a more significant factor than contact pressure for gridline degradation.

14 SOLAR ENERGY↗

DOE OSTI2015

SU-E-P-48: Evaluation of Intensity Modulated Radiotherapy (IMRT) with Three Different Commercial Planning Systems for the Treatment of Cervical Cancer

Purpose: To investigate the performances of three commercial treatment planning systems (TPS) for intensity modulated radiotherapy (IMRT) optimization regarding cervical cancer. Methods: For twenty cervical cancer patients, three IMRT plans were retrospectively re-planned: one with Pinnacle TPS,one with Oncentra TPS and on with Eclipse TPS. The total prescribed dose was 50.4 Gy delivered for PTV and 58.8 Gy for PTVnd by simultaneous integrated boost technique. The treatments were delivered using the Varian 23EX accelerator. All optimization schemes generated clinically acceptable plans. They were evaluated based on target coverage, homogeneity (HI) and conformity (CI). The organs at risk (OARs) were analyzed according to the percent volume under some doses and the maximum doses. The statistical method of the collected data of variance analysis was used to compare the difference among the quality of plans. Results: IMRT with Eclipse provided significant better HI, CI and all the parameters of PTV. However, the trend was not extension to the PTVnd, it was still significant better at mean dose, D50% and D98%, but plans with Oncentra showed significant better in the hight dosage volume, such as maximum dose and D2%. For the bladder wall, there were not notable difference among three groups, although Pinnacle and Oncentra systems provided a little lower dose sparing at V50Gy of bladder and rectal wall and V40Gy of bladder wall, respectively. V40Gy of rectal wall (p=0.037), small intestine (p=0.001 for V30Gy, p=0.010 for maximum dose) and V50Gy of right-femoral head (p=0.019) from Eclipse plans showed significant better than other groups. Conclusion: All SIB-IMRT plans were clinically acceptable which were generated by three commercial TPSs. The plans with Eclipse system showed advantages over the plans with Oncentra and Pinnacle system in the overwhelming majority of the dose coverage for targets and dose sparing of OARs in cervical cancer.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A linear, separable two-parameter model for dual energy CT imaging of proton stopping power computation

Purpose: To evaluate the accuracy and robustness of a simple, linear, separable, two-parameter model (basis vector model, BVM) in mapping proton stopping powers via dual energy computed tomography (DECT) imaging. Methods: The BVM assumes that photon cross sections (attenuation coefficients) of unknown materials are linear combinations of the corresponding radiological quantities of dissimilar basis substances (i.e., polystyrene, CaCl{sub 2} aqueous solution, and water). The authors have extended this approach to the estimation of electron density and mean excitation energy, which are required parameters for computing proton stopping powers via the Bethe–Bloch equation. The authors compared the stopping power estimation accuracy of the BVM with that of a nonlinear, nonseparable photon cross section Torikoshi parametric fit model (VCU tPFM) as implemented by the authors and by Yang et al. [“Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues,” Phys. Med. Biol. 55, 1343–1362 (2010)]. Using an idealized monoenergetic DECT imaging model, proton ranges estimated by the BVM, VCU tPFM, and Yang tPFM were compared to International Commission on Radiation Units and Measurements (ICRU) published reference values. The robustness of the stopping power prediction accuracy of tissue composition variations was assessed for both of the BVM and VCU tPFM. The sensitivity of accuracy to CT image uncertainty was also evaluated. Results: Based on the authors’ idealized, error-free DECT imaging model, the root-mean-square error of BVM proton stopping power estimation for 175 MeV protons relative to ICRU reference values for 34 ICRU standard tissues is 0.20%, compared to 0.23% and 0.68% for the Yang and VCU tPFM models, respectively. The range estimation errors were less than 1 mm for the BVM and Yang tPFM models, respectively. The BVM estimation accuracy is not dependent on tissue type and proton energy range. The BVM is slightly more vulnerable to CT image intensity uncertainties than the tPFM models. Both the BVM and tPFM prediction accuracies were robust to uncertainties of tissue composition and independent of the choice of reference values. This reported accuracy does not include the impacts of I-value uncertainties and imaging artifacts and may not be achievable on current clinical CT scanners. Conclusions: The proton stopping power estimation accuracy of the proposed linear, separable BVM model is comparable to or better than that of the nonseparable tPFM models proposed by other groups. In contrast to the tPFM, the BVM does not require an iterative solving for effective atomic number and electron density at every voxel; this improves the computational efficiency of DECT imaging when iterative, model-based image reconstruction algorithms are used to minimize noise and systematic imaging artifacts of CT images.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

SU-F-T-113: Inherent Functional Dependence of Spinal Cord Doses of Variable Irradiated Volumes in Spine SBRT

Purpose: Spinal cord tolerance for SBRT has been recommended for the maximum point dose level or at irradiated volumes such as 0.35 mL or 10% of contoured volumes. In this study, we investigated an inherent functional relationship that associates these dose surrogates for irradiated spinal cord volumes of up to 3.0 mL. Methods: A hidden variable termed as Effective Dose Radius (EDR) was formulated based on a dose fall-off model to correlate dose at irradiated spinal cord volumes ranging from 0 mL (point maximum) to 3.0 mL. A cohort of 15 spine SBRT cases was randomly selected to derive an EDR-parameterized formula. The mean prescription dose for the studied cases was 21.0±8.0 Gy (range, 10–40Gy) delivered in 3±1 fractions with target volumes of 39.1 ± 70.6 mL. Linear regression and variance analysis were performed for the fitting parameters of variable EDR values. Results: No direct correlation was found between the dose at maximum point and doses at variable spinal cord volumes. For example, Pearson R{sup 2} = 0.643 and R{sup 2}= 0.491 were obtained when correlating the point maximum dose with the spinal cord dose at 1 mL and 3 mL, respectively. However, near perfect correlation (R{sup 2} ≥0.99) was obtained when corresponding parameterized EDRs. Specifically, Pearson R{sup 2}= 0.996 and R{sup 2} = 0.990 were obtained when correlating EDR (maximum point dose) with EDR (dose at 1 mL) and EDR(dose at 3 mL), respectively. As a result, high confidence level look-up tables were established to correlate spinal cord doses at the maximum point to any finite irradiated volumes. Conclusion: An inherent functional relationship was demonstrated for spine SBRT. Such a relationship unifies dose surrogates at variable cord volumes and proves that a single dose surrogate (e.g. point maximum dose) is mathematically sufficient in constraining the overall spinal cord dose tolerance for SBRT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

MAVTgsa: An R Package for Gene Set (Enrichment) Analysis

Gene set analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q -value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.

Chien, Chih-Yi↗

DOE OSTI2015

Ppb-level formaldehyde detection using a CW room-temperature interband cascade laser and a miniature dense pattern multipass gas cell

A ppb-level formaldehyde (H 2 CO) sensor was developed using a thermoelectrically cooled (TEC), continuous-wave (CW) room temperature interband cascade laser (ICL) emitting at 3.59 μm and a miniature dense pattern multipass gas cell with >50 m optical path length. Performance of the sensor was investigated with two measurement schemes: direct absorption (DAS) and wavelength modulation spectroscopy (WMS). With an integration time of less than 1.5 second, a detection limit of ~3 ppbv for H 2 CO measurement with precision of 1.25 ppbv for DAS and 0.58 ppbv for WMS, respectively, was achieved without zero air based background subtraction. An Allan-Werle variance analysis indicated that the precisions can be further improved to 0.26 ppbv @ 300s for DAS and 69 pptv @ 90 s for WMS, respectively. Finally, a side-by-side comparison between two measurement schemes is also discussed in detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

The extreme ultraviolet variability of quasars

We study the extreme ultraviolet (EUV) variability (rest frame wavelengths 500–920 Å) of high-luminosity quasars using Hubble Space Telescope (HST) (low to intermediate redshift sample) and Sloan Digital sky Survey (SDSS) (high redshift sample) archives. The combined HST and SDSS data indicates a much more pronounced variability when the sampling time between observations in the quasar rest frame is >2×10{sup 7} s compared to <1.5×10{sup 7} s. Based on an excess variance analysis, for time intervals <2×10{sup 7} s in the quasar rest frame, 10% of the quasars (4/40) show evidence of EUV variability. Similarly, for time intervals >2×10{sup 7} s in the quasar rest frame, 55% of the quasars (21/38) show evidence of EUV variability. The propensity for variability does not show any statistically significant change between 2.5×10{sup 7} s and 3.16×10{sup 7} s (1 year). The temporal behavior is one of a threshold time interval for significant variability as opposed to a gradual increase on these timescales. A threshold timescale can indicate a characteristic spatial dimension of the EUV region. We explore this concept in the context of the slim disk models of accretion. We find that for rapidly spinning black holes, the radial infall time to the plunge region of the optically thin surface layer of the slim disk that is responsible for the preponderance of the EUV flux emission (primarily within 0–7 black hole radii from the inner edge of the disk) is consistent with the empirically determined variability timescale.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1972

Unsupervised classification of remote multispectral sensing data

The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

Su, M. Y.↗

NASA NTRS1972

Mapping of terrain by computer clustering techniques using multispectral scanner data and using color aerial film

Two clustering techniques were used for terrain mapping by computer of test sites in Yellowstone National Park. One test was made with multispectral scanner data using a composite technique which consists of (1) a strictly sequential statistical clustering which is a sequential variance analysis, and (2) a generalized K-means clustering. In this composite technique, the output of (1) is a first approximation of the cluster centers. This is the input to (2) which consists of steps to improve the determination of cluster centers by iterative procedures. Another test was made using the three emulsion layers of color-infrared aerial film as a three-band spectrometer. Relative film densities were analyzed using a simple clustering technique in three-color space. Important advantages of the clustering technique over conventional supervised computer programs are (1) human intervention, preparation time, and manipulation of data are reduced, (2) the computer map, gives unbiased indication of where best to select the reference ground control data, (3) use of easy to obtain inexpensive film, and (4) the geometric distortions can be easily rectified by simple standard photogrammetric techniques.

Smedes, H. W.↗

NASA NTRS1972

Unsupervised classification of earth resources data.

A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.

Su, M. Y.↗