Digital data sampling modules, part 1 Final report
Digital data sampling system with random access, distributed data gathering
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Nationwide forestry applications program: Procedure 1 applicability to rangeland classification
The author has identified the following significant results. An assumption that short prairie grass and salt grass could be differentiated on aircraft photographs was inaccurate for the Weld County site. However, rangeland could be differentiated using procedure 1 from LACIE. Estimates derived from either random or systematic sampling were satisfactory. Level 1 features were separated and mapped, and proportions were estimated with accompanying confidence statements.
Reeves, C. A.↗
On the constancy of the lunar cratering flux over the past 3.3 billion yr
Utilizing a method that minimizes random fluctuations in sampling crater populations, it can be shown that the ejecta deposit of Tycho, the floor of Copernicus, and the region surrounding the Apollo 12 landing site have incremental crater size-frequency distributions that can be expressed as log-log linear functions over the diameter range from 0.1 to 1 km. Slopes are indistinguishable for the three populations, probably indicating that the surfaces are dominated by primary craters. Treating the crater populations of Tycho, the floor of Copernicus, and Apollo 12 as primary crater populations contaminated, but not overwhelmed, with secondaries, allows an attempt at calibration of the post-heavy bombardment cratering flux. Using the age of Tycho as 109 m.y., Copernicus as 800 m.y., and Apollo 12 as 3.26 billion yr, there is no basis for assuming that the flux has changed over the past 3.3 billion yr. This result can be used for dating intermediate aged surfaces by crater density.
Guinness, E. A.↗
Confidence regions of planar cardiac vectors
A method for plotting the confidence regions of vectorial data obtained in electrocardiology is presented. The 90%, 95% and 99% confidence regions of cardiac vectors represented in a plane are obtained in the form of an ellipse centered at coordinates corresponding to the means of a sample selected at random from a bivariate normal distribution. An example of such a plot for the frontal plane QRS mean electrical axis for 80 horses is also presented.
Dubin, S.↗
Development of alternative data analysis techniques for improving the accuracy and specificity of natural resource inventories made with remote sensing data
The applicability of digital LANDSAT data in updating the Minnesota Lake Land Management Information System and in assessing the trophic status of lakes was investigated. Data from various combinations of training, classification, and geometric correction techniques were compared to a photointerpreted reference data set consisting of ground-verified samples and six randomly selected photographs covering approximately one quarter of the study area. For a reconnaissance inventory, the training via polygons selected from aerial photographs with a canonical analysis minimum distance classifier is the most accurate and efficient analysis technique. The applications test project resulted in disappointing thematic classification results per se, but did contribute to the development of mechanisms for implementing a LANDSAT data processing capability in the State Planning Agency on a permanent basis.
Lillesand, T. M.↗
Expected antenna utilization and overload
The trade-offs between the number of antennas at Deep Space Network (DSN) Deep-Space Communications Complex and the fraction of continuous coverage provided to a set of hypothetical spacecraft, assuming random placement of the space craft passes during the day. The trade-offs are fairly robust with respect to the randomness assumption. A sample result is that a three-antenna complex provides an average of 82.6 percent utilization of facilities and coverage of nine spacecraft that each have 8-hour passes, whereas perfect phasing of the passes would yield 100 percent utilization and coverage. One key point is that sometimes fewer than three spacecraft are visible, so an antenna is idle, while at other times, there aren't enough antennas, and some spacecraft do without service. This point of view may be useful in helping to size the network or to develop a normalization for a figure of merit of DSN coverage.
Posner, Edward C.↗
Ulysses observations of double ion beams associated with coronal mass ejections
Coronal mass ejections (CME's) are thought to result from the loss of stability within a magnetically confined coronal structure leading to its radial expansion into interplanetary space. As the CME expands into the corona current sheets will form between the expanding CME and surrounding field lines in the ambient wind. This configuration may lead to reconnection between the CME and adjacemt field lines. Such reconnection may produce double ion beams as has been observed in the terrrestrial magnetosphere. We examine all 24 distinct signatures of CME's observed by Ulysses during the in-ecliptic portion of the mission. In 5 of these 24 cases the ion spectra were not clear and thus the presence of double ion beams could not be determined. In 13 of the remaining 19 CME's double ion beams were found on the leading and/or trailing edge of the CME but not in the interior of the CME. In 3 of the CME's double ion beams were found throughout the CME while in the remaining 3 CME's double ion beams were not present near or just inside of the CME. In contrast in a control sample of 19 randomly chosen intervals, double ion beams were present at the leading and/or trailing edges of the random intervals in only 3 of the 19 cases. There appears to be no correlation between probability of occurrence of double ion beams and a magnetic cloud or non-cloud configuration of the CME and no correlation between the presence of the double ion beams at the edges of the CME and the CME being a fast or slow CME.
Hammond, C. M.↗
Progressive Response Surfaces
Response surface functions are often used as simple and inexpensive replacements for computationally expensive computer models that simulate the behavior of a complex system over some parameter space. Progressive response surfaces are ones that are built up progressively as global information is added from new sample points in the parameter space. As the response surfaces are globally upgraded based on new information, heuristic indications of the convergence of the response surface approximation to the exact (fitted) function can be inferred. Sampling points can be incrementally added in a structured fashion, or in an unstructured fashion. Whatever the approach, at least in early stages of sampling it is usually desirable to sample the entire parameter space uniformly. At later stages of sampling, depending on the nature of the quantity being resolved, it may be desirable to continue sampling uniformly over the entire parameter space (Progressive response surfaces), or to switch to a focusing/economizing strategy of preferentially sampling certain regions of the parameter space based on information gained in early stages of sampling (Adaptive response surfaces). Here we consider Progressive response surfaces where a balanced indication of global response over the parameter space is desired.We use a variant of Moving Least Squares to fit and interpolate structured and unstructured point sets over the parameter space. On a 2-D test problem we compare response surface accuracy for three incremental sampling methods: Progressive Lattice Sampling; Simple-Random Monte Carlo; and Halton Quasi-Monte-Carlo sequences. We are ultimately after a system for constructing efficiently upgradable response surface approximations with reliable error estimates.
Romero, V. J.↗
Measures and Models for Estimating and Predicting Cognitive Fatigue
We analyzed EEG and ERPs in a fatiguing mental task and created statistical models for single subjects. Seventeen subjects (4 F, 18-38 y) viewed 4-digit problems (e.g., 3+5-2+7=15) on a computer, solved the problems, and pressed keys to respond (intertrial interval = 1 s). Subjects performed until either they felt exhausted or three hours had elapsed. Re- and post-task measures of mood (Activation Deactivation Adjective Checklist, Visual Analogue Mood Scale) confirmed that fatigue increased and energy decreased over time. We tested response times (RT); amplitudes of ERP components N1, P2, P300, readiness potentials; and amplitudes of frontal theta and parietal alpha rhythms for change as a function of time. For subjects who completed 3 h (n=9) we analyzed 12 15-min blocks. For subjects who completed at least 1.5 h (n=17), we analyzed the first-, middle-, and last 100 error-free trials. Mean RT rose from 6.7 s to 8.5 s over time. We found no changes in the amplitudes of ERP components. In both analyses, amplitudes of frontal theta and parietal alpha rose by 30% or more over time. We used 30-channel EEG frequency spectra to model the effects of time in single subjects using a kernel partial least squares classifier. We classified 3.5s EEG segments as being from the first 100 or the last 100 trials, using random sub-samples of each class. Test set accuracies ranged from 63.9% to 99.6% correct. Only 2 of 17 subjects had mean accuracies lower than 80%. The results suggest that EEG accurately classifies periods of cognitive fatigue in 90% of subjects.
Trejo, Leonard J.↗
Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data
In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50 500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. The results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.
Markus, Thorsten↗
Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit
We report a free space laser communication experiment from the satellite laser ranging (SLR) station at NASA Goddard Space Flight Center (GSFC) to the Lunar Reconnaissance Orbiter (LRO) in lunar orbit through the on board one-way Laser Ranging (LR) receiver. Pseudo random data and sample image files were transmitted to LRO using a 4096-ary pulse position modulation (PPM) signal format. Reed-Solomon forward error correction codes were used to achieve error free data transmission at a moderate coding overhead rate. The signal fading due to the atmosphere effect was measured and the coding gain could be estimated.
fee-space optical communication↗
Intensity-based rock detection for acquiring onboard rover science
Missions to Mars already under study call for very long autonomous traverses (on the order of hundreds of meters per sol) during which there will be limited contact with Earth. The onboard Autonomous Science Investigation System (OASIS) is a technology for increasing science return during rover traverses by prioritizing science opportunities. By prioritizing data for downlink onboard, it is expected that the set of images selected for downlink by OASIS will have a consistently higher scientific interest then any set of equal number of images of the same traverse obtained using random or periodic sampling. Thus, OASIS can be used to increase the science returned from a long traverse. OASIS prioritizes data and identifies science opportunities by extracting information from image data and then using this information to prioritize the data and identify potential new science opportunities. Currently, the information extracted from the images is the location of the rocks in the image and several properties of these rocks such as size, albedo, texture and shape, In this paper we give an overview of the role of rock detection in the OASIS system and describe the functionality of the rock detector. We then present results on representative images
Judd, Michele↗
A Sample/Jitter Monte Carlo Technique for Main Parachute Loads Predictions
Models for Orion parachute performance are based on reconstructions of the Capsule Parachute Assembly System (CPAS) drop test campaign and were documented in the CPAS “Model Memo.” Experience with similar Commercial Crew Program (CCP) parachute systems resulted in some updates to the Orion models in preparation for Artemis missions. The reefing cutter dispersion model for the drogues and mains had been overly-conservative by producing wide timing differences within clusters. A higher-fidelity timing model was generated by separating out in-lot variation and temperature effects. The main parachute inflation model had accounted for some correlations between parameters using complicated 2-D geometric bounding, but the results tended to exaggerate individual peak loads from fast (leading) inflations and under-emphasize actual lagging experience. Several flight tests were reconstructed again with an emphasis on matching peak load magnitudes using a search algorithm. A simpler method for generating inflation parameters uses the 3-D correlated reconstructed “samples” with some random “jitter” applied. Dispersed Monte Carlo inputs are then checked against flight test data to evaluate whether they represent reality.
parachutes↗
Southern Rockies Western Slope Agriculture: Identifying Drivers of Rangeland Production for Drought Planning on the Western Slope of the Southern Rockies
Over the last decade, the southern Rocky Mountains of the United States have experienced increasingly severe and variable drought. Local ranchers and landowners have reported strain on their operations, citing decreasing forage production for their cattle and a need to adjust their business models, even considering abandoning their businesses altogether. The study identified Major Land Resource Area-48 (MLRA-48) and northwestern Colorado as the key region for analysis. NASA DEVELOP partnered with the BLM Colorado River Field Office, Colorado State University Extension, USDA Forest Service, and the National Drought Mitigation Center to address stakeholder concerns of the efficacy of existing remotely sensed rangeland production estimation platforms and explore possible early warning climatic indicators of drought. The study identified two key rangeland platforms, the Rangeland Production Monitoring Service (RPMS) and Rangeland Analysis Platform (RAP) and used in-situ data to statistically validate their efficacy. RAP outperformed RPMS in estimating in-situ biomass and was therefore used in our climate modeling. Our study performed a random forest analysis, sampling 1500 points across the study area, comparing monthly RAP biomass estimates to a variety of climatic variables, including mean precipitation, temperature, palmer drought severity index, snow water equivalent, wind speed and direction, and vapor pressure deficit. After analysis, our study determined that vapor pressure deficit is a key indicator in predicting forage production in MLRA-48. Our study recommends the use of RAP in estimating potential forage, with caution for its tendency to overestimate. Our climate analysis provided our partners with greater understanding of the influence of various climatic factors in determining forage production and allows them to assist landowners in planning for future drought.
Addie Gonzalez↗
Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System
GMAO Sub/Seasonal prediction system (S2S) is being readied for a major upgrade to GEOS-S2S Version 3. An important factor in successful extended range forecast is the definition of an ensemble For initialization of the ensemble we propose a combination of lagged and burst initial conditions. We plan to run a relatively large ensemble of 40 members for sub-seasonal forecast (up to 3 months), at which point we sub-sample the ensemble, and continue the forecast with 10 members (up to 12 months). Here we present the results of the extensive testing of various ways to generate the perturbations to the initial conditions and the validation of the stratified sampling strategy we chose.To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states separated by 1-10 days, randomly chosen from a corresponding season. We considered perturbing separately only the atmospheric fields or only the ocean or both of the forecast initial conditions. Considering varying separation times between the analysis states, we were able to produce perturbations sampling various modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread.Our ensemble size for sub-seasonal forecasts was determined as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes, NAO, PNA and AO. It is not feasible to run equally large ensemble for seasonal forecasts. Using a stratified sampling procedure we can identify the emerging directions of error growth. By comparing the stratified ensemble with randomly sampled ensemble of the same size, we were able to show that the former better estimates the mean of the original large ensemble.
Borovikov, Anna↗
Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References
Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.
Racette, Paul↗
Visualizing Time-Varying Distribution Data in EOS Application
In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.
Shen, Han-Wei↗
Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System
The NASA Global Modeling and Assimilation Office (GMAO) Sub-seasonal to Seasonal (S2S) prediction system is being readied for a major upgrade. An important factor in successful extended range forecasting is the definition of the ensemble. Our overall strategy is to run a relatively large ensemble of about 40 members up to 3 months (focusing on the sub-seasonal forecast problem), after which we sub-sample the ensemble, and continue the forecast with about 10 members (up to 12 months). Here we present the results of our testing of various ways to generate the initial perturbations and the validation of a stratified sampling approach for choosing the members of the smaller ensemble. For the initialization of the ensemble we propose a combination of lagged and burst initial conditions. To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states (chosen randomly from the corresponding season) separated by 1-10 days. We consider perturbing separately the atmosphere and the ocean, or both. By varying the separation times between the analysis states, we are able to produce perturbations that resemble well-known modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread with, however, considerable differences in the timing of the impacts on spread for the atmospheric and oceanic perturbations.Our initial (larger) ensemble size was determined so as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes (namely the NAO, PNA and AO). Since it is not feasible for us to run with the larger ensemble beyond about 3 months, we employ a stratified sampling procedure that identifies the emerging directions of error growth to subset the ensemble. By comparing the results from the stratified ensemble with that of the randomly sampled ensemble of the same size, we find that the former provides substantially better estimates the mean of the original large ensemble.
Borovikov, Anna↗