Engineering topics

Rickman, Doug

Publications and source records attributed to Rickman, Doug.

51 records · Page 3

NASA NTRS2007

NASA'S Simulant Development Program Evolution and Overview

Since its origination under NASA's previous Human System Research and Technology program, the Lunar Simulant Development Program has undergone several changes. NASA recognized as early as the Apollo Program, and even more so as a result of the Apollo missions, that a viable dust and lunar simulant program is critical to the success of its space exploration goals. Unfortunately, this program has suffered the same problems that all programs share from time to time including uncertain budgets, shifting of priorities, and schedule fluctuations. To compound the problem, the process for developing simulants is being redefined and is not a trivial pursuit. Before now, NASA had not attempted to develop a suitable standard simulant since the 1990s when JSC-1 was produced. Although several other simulants have been developed by various groups both before and after the production of JSC-1, JSC-1 had become the de facto standard even though it has some limitations. The development and production of new simulants will address some of these limitations by starting with an assessment of NASA's needs and understanding the required processing in order to make these simulants.

McLemore, Carole↗

NASA NTRS2006

Utility of MODIS Aerosol Optical Depth for Estimating PM2.5 Exposure in Environmental Public Health Surveillance

As part of the National Environmental Public Health Tracking Network (EPHTN) the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project called Health and Environment Linked for Information Exchange (HELIX-Atlanta). The goal of developing the National Environmental Public Health Tracking Network is to improve the health of communities. Currently, few systems exist at the state or national level to concurrently track many of the exposures and health effects that might be associated with environmental hazards. An additional challenge is estimating exposure to environmental hazards such as particulate matter whose aerodynamic diameter is less than or equal to 2.5 micrometers (PM(2.5)) HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of Metropolitan Atlanta, GA (Clayton, Cobb, DeKalb, Fulton, and Gwinnett counties). Under HELIX-Atlanta, pilot projects are being conducted to develop methods to characterize exposure; link health and environmental data; analyze the relationship between health and environmental factors; and communicate findings. NASA Marshall Space Flight Center (NASA/MSFC) is collaborating with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of PM(2.5) concentrations that can be linked with clinic visits for asthma. From 1999-2000 there were over 9,400 hospitalizations per year in Georgia with asthma as the primary diagnosis. The majority of these hospitalizations occurred in medical facilities in the five most populous Metro-Atlanta counties. Hospital charges resulting from asthma in Georgia are approximately $59 million dollars annually. There is evidence in the research literature that asthmatic persons are at increased risk of developing asthma exacerbations with exposure to environmental factors, including PM(2.5). Thus, HELIX-Atlanta is focusing on methods for characterizing population exposure to PM(2.5) for the Atlanta metropolitan area that could be used in on-going surveillance. While use of the Air Quality System, (AQS) PM(2.5) data alone could meet HELIX Atlanta, specifications, there are only five AQS sites in the Atlanta area, thus the spatial coverage is not ideal. Also, the AQS ground observations are made at time intervals ranging from one hour to six days leaving some temporal gaps. NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Depth (AOD) data have the potential for estimating daily ground level PM(2.5) at 10 km resolution over the metropolitan Atlanta area supplementing the AQS ground observations and filling their spatial and temporal gaps.

Al-Hamdan, Mohammad↗

NASA NTRS2006

Materials Requirements for Standard Lunar Highlands Regolith Simulants as Defined by the NASA Simulant Development Program

The development of surface technologies for NASA's human and robotic lunar program beyond 2010 has begun. The multitude of projects underway and future ones will soon rely on the availability of lunar regolith simulant materials chosen to simulate the characteristics of lunar regoliths in order to design, test and qualify prototype hardware and flight equipment. The selection and development of standard lunar regolith simulants (SLRS) for the use of NASA technology programs was one of the main recommendations of the 2005 Workshop on Lunar Regolith Simulant Materials at Marshall Space Flight Center. The realization of that objective is now underway through the NASA simulant development program at the Marshall Space Flight Center. The approach adopted to define materials requirements for standard simulants of regolith from the Highlands regions of the Moon will be presented along with a discussion of limitations inherent to such an endeavor.

Sibille, Laurent↗

NASA NTRS2006

Development Issues for Lunar Regolith Simulants

Significant challenges and logistical issues exist for the development of standardized lunar regolith simulant (SLRS) materials for use in the development and testing of flight hardware for upcoming NASA lunar missions. A production program at Marshall Space Flight Center (MSFC) for the deployment of lunar mare basalt simulant JSC-lA is underway. Root simulants have been proposed for the development of a low-T mare basalt simulant and a high-Ca highland anorthosite simulant, as part of a framework of simulant development outlined in the 2005 Lunar Regolith Simulant Materials Workshop held at MSFC. Many of the recommendation for production and standardization of simulants have already been documented by the MSFC team. But there are a number of unanswered questions related to geology which need ta be addressed prior to the creation of the simulants.

Rickman, Doug↗

NASA NTRS2006

Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration

Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.

Faruque, Fazlay↗

NASA NTRS2006

Requirements and Techniques for Developing and Measuring Simulant Materials

The 1989 workshop report entitled Workshop on Production and Uses of Simulated Lunar Materials and the Lunar Regolith Simulant Materials: Recommendations for Standardization, Production, and Usage, NASA Technical Publication identify and reinforced a need for a set of standards and requirements for the production and usage of the lunar simulant materials. As NASA need prepares to return to the moon, a set of requirements have been developed for simulant materials and methods to produce and measure those simulants have been defined. Addressed in the requirements document are: 1) a method for evaluating the quality of any simulant of a regolith, 2) the minimum Characteristics for simulants of lunar regolith, and 3) a method to produce lunar regolith simulants needed for NASA's exploration mission. A method to evaluate new and current simulants has also been rigorously defined through the mathematics of Figures of Merit (FoM), a concept new to simulant development. A single FoM is conceptually an algorithm defining a single characteristic of a simulant and provides a clear comparison of that characteristic for both the simulant and a reference material. Included as an intrinsic part of the algorithm is a minimum acceptable performance for the characteristic of interest. The algorithms for the FoM for Standard Lunar Regolith Simulants are also explicitly keyed to a recommended method to make lunar simulants.

Rickman, Doug↗

NASA NTRS2005

Algorithm for Identifying Erroneous Rain-Gauge Readings

An algorithm analyzes rain-gauge data to identify statistical outliers that could be deemed to be erroneous readings. Heretofore, analyses of this type have been performed in burdensome manual procedures that have involved subjective judgements. Sometimes, the analyses have included computational assistance for detecting values falling outside of arbitrary limits. The analyses have been performed without statistically valid knowledge of the spatial and temporal variations of precipitation within rain events. In contrast, the present algorithm makes it possible to automate such an analysis, makes the analysis objective, takes account of the spatial distribution of rain gauges in conjunction with the statistical nature of spatial variations in rainfall readings, and minimizes the use of arbitrary criteria. The algorithm implements an iterative process that involves nonparametric statistics.

Rickman, Doug↗

NASA NTRS2005

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Sullivan, Dana↗

NASA NTRS2005

Aircraft Based Remotely Sensed Albedo and Surface Temperatures for Three US Cities

High spatial resolution thermal infrared and visible data obtained from aircraft were used to measure, map, and model the surface energy budget characteristics of surfaces typical of the urban landscape for three US cities. Aircraft data collected from the Advanced Thermal and Land Applications Sensor (ATLAS) scanner allowed a detail analysis of the city, determining its surface thermal and visible reflectance properties. These data are critical in providing data that can be used to evaluate the overall "fabric" of the cities in relation to the urban heat island and air quality modeling.

Luvall, Jeffrey C.↗

NASA NTRS2005

Using Remote Sensing Data to Evaluate Surface Soil Properties in Alabama Ultisols

Evaluation of surface soil properties via remote sensing could facilitate soil survey mapping, erosion prediction and allocation of agrochemicals for precision management. The objective of this study was to evaluate the relationship between soil spectral signature and surface soil properties in conventionally managed row crop systems. High-resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil organic carbon, particle size distribution, and citrate dithionite extractable iron content. Surface roughness, soil water content, and crusting were also measured during sampling. Two methods of analysis were evaluated: 1) multiple linear regression using common spectral band ratios, and 2) partial least squares regression. Our data show that thermal infrared spectra are highly, linearly related to soil organic carbon, sand and clay content. Soil organic carbon content was the most difficult to quantify in these highly weathered systems, where soil organic carbon was generally less than 1.2%. Estimates of sand and clay content were best using partial least squares regression at the Valley site, explaining 42-59% of the variability. In the Coastal Plain, sandy surfaces prone to crusting limited estimates of sand and clay content via partial least squares and regression with common band ratios. Estimates of iron oxide content were a function of mineralogy and best accomplished using specific band ratios, with regression explaining 36-65% of the variability at the Valley and Coastal Plain sites, respectively.

Sullivan, Dana G.↗

NASA NTRS2004

Mapping Surface Soil Organic Carbon for Crop Fields with Remote Sensing

The organic C concentration of surface soil can be used in agricultural fields to vary crop production inputs. Organic C is often highly spatially variable, so that maps of soil organic C can be used to vary crop production inputs using precision farming technology. The objective of this research was to demonstrate the feasibility of mapping soil organic C on three fields, using remotely sensed images of the fields with a bare surface. Enough soil samples covering the range in soil organic C must be taken from each field to develop a satisfactory relationship between soil organic C content and image reflectance values. The number of soil samples analyzed in the three fields varied from 22 to 26. The regression equations differed between fields, but gave highly significant relationships with R2 values of 0.93, 0.95, and 0.89 for the three fields. A comparison of predicted and measured values of soil organic C for an independent set of 2 soil samples taken on one of the fields gave highly satisfactory results, with a comparison equation of % organic C measured + 1.02% organic C predicted, with r2 = 0.87.

Chen, Feng↗

NASA NTRS2001

Captain, sensors report ...: Correction of Remote Sensing Data

Remote sensing data acquired by airborne and satellite Systems have many impressive virtues for ecology and other sciences. They are synoptic. They are extremely cheap per data point. They cover large areas. They are not subjective. They detect features that are of clear and obvious interest for many uses. But, they also yield totally irreproducible measurements. Sensors that operate in the visible, near infrared and thermal portions of the spectrum are sensitive to a host of phenomena that are usually of little interest to the average user. Fully recognizing the power and sophistication of the algorithms currently available to users of remote sensing, the authors as long time developers (20+ years) of such algorithms, demonstrate that a host of other signals are convolved with the typical data set, and that many of these signals are very commonly not even recognized, and that these signals are often larger than the signal from the putative target. These derive from both geometric and radiometric sources as well as fundamental flaws in sensor engineering. Until such extraneous factors can be controlled or eliminated the utility of the data is greatly restricted. Finally, the authors lay out a design elements for a rational sensor and methods of deconvolving the complexity of the real world data using such a sensor.

Rickman, Doug↗

NASA NTRS1991

A superior edge preserving filter with a systematic analysis

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Holladay, Kenneth W.↗

NASA NTRS1989

Georeferencing airborne imagery over new deltas in Louisiana

An experiment to study the hypothesis that winter cold fronts are more important that violent summer storms in moving sediment in midlatitude coastal river deltas. The experiment is based on Calibrated Airborne Multispectral Scanner (CAMS) data. A new approach for the georeferencing of aircraft imagery has been developed for use in this experiment. The software for the approach uses the aircraft inertial navigation data and is able to automatically map a three-channel 1600 line file through a 90 deg rotation in less than 14 minutes. Results from tests of the technique show rms errors of less than 2/3 of a pixel.

Rickman, Doug↗

NASA NTRS1986

Atmospheric correction of TIMS data

The Thermal Infrared Multispectral Scanner (TIMS) is a unique sensor for two reasons, it is multispectral in the thermal-infrared and it has on board, active calibration sources. The existence of the calibration permits the recorded DNs to be converted unambiguously to absolute energy units. However, to relate the data to energy originating from a target on the ground it is necessary to remove the atmospheric contribution to the signal, specifically its transmittance and emittance. These can be obtained fairly easily by use of the atmospheric model provided by LOWTRAN-6 and the data from the U.S. Weather Service network of bidaily radiosondes. Using these data with the TIMS responsivity curves an equation can be obtained which permits the unambiguous correction of the TIMS data for the atmosphere.

Rickman, Doug↗