Engineering topics

Davis, Bruce

Publications and source records attributed to Davis, Bruce.

15 records

NASA NTRS2015

HVI Ballistic Limit Charaterization of Fused Silica Thermal Pane

The Orion spacecraft's windows are exposed to the micrometeroid and orbital debris (MMOD) space environments while in space as well as the Earth entry environment at the mission's conclusion. The need for a low-mass spacecraft window design drives the need to reduce conservatism when assessing the design for loss of crew due to MMOD impact and subsequent Earth entry. Therefore, work is underway at NASA and Lockheed Martin to improve characterization of the complete penetration ballistic limit of an outer fused silica thermal pane. Hypervelocity impact tests of the window configuration at up to 10 km/s and hydrocode modeling have been performed with a variety of projectile materials to enable refinement of the fused silica ballistic limit equation.

Bohl, William E.↗

NASA NTRS2011

Self-Cleaning Coatings and Materials for Decontaminating Field-Deployable Land and Water-Based Optical Systems

This technology exploits the organic decomposition capability and hydrophilic properties of the photocatalytic material titanium dioxide (TiO2), a nontoxic and non-hazardous substance, to address contamination and biofouling issues in field-deployed optical sensor systems. Specifically, this technology incorporates TiO2 coatings and materials applied to, or integrated as a part of, the optical surfaces of sensors and calibration sources, including lenses, windows, and mirrors that are used in remote, unattended, ground-based (land or maritime) optical sensor systems. Current methods used to address contamination or biofouling of these optical surfaces in deployed systems are costly, toxic, labor intensive, and non-preventative. By implementing this novel technology, many of these negative aspects can be reduced. The functionality of this innovative self-cleaning solution to address the problem of contamination or biofouling depends on the availability of a sufficient light source with the appropriate spectral properties, which can be attained naturally via sunlight or supplemented using artificial illumination such as UV LEDs (light emitting diodes). In land-based or above-water systems, the TiO2 optical surface is exposed to sunlight, which catalyzes the photocatalytic reaction, facilitating both the decomposition of inorganic and organic compounds, and the activation of superhydrophilic properties. Since underwater optical surfaces are submerged and have limited sunlight exposure, supplementary UV light sources would be required to activate the TiO2 on these optical surfaces. Nighttime operation of land-based or above-water systems would require this addition as well. For most superhydrophilic self-cleaning purposes, a rainwater wash will suffice; however, for some applications an attached rainwater collector/ dispenser or other fresh water dispensing system may be required to wash the optical surface and initiate the removal of contaminates. Deployment of this non-toxic,non-hazardous-technology will take advantage of environmental elements (i.e. rain and sunlight), increase the longevity of unattended optical systems, increase the amount of time between required maintenance, and improve the long-term accuracy of sensor measurements.

Ryan, Robert↗

NASA NTRS2011

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Davis, Bruce↗

NASA NTRS2006

Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources

This viewgraph presentation regards one element of a larger project on the integration of NASA science models and data into the Hazards U.S. Multi-Hazard (HAZUS-MH) Hurricane module for hurricane damage and loss risk assessment. HAZUS-MH is a decision support tool being developed by the National Institute of Building Sciences for the Federal Emergency Management Agency (FEMA). It includes the Hurricane Module, which employs surface roughness maps made from National Land Cover Data (NLCD) maps to estimate coastal hurricane wind damage and loss. NLCD maps are produced and distributed by the U.S. Geological Survey. This presentation discusses an effort to improve upon current HAZUS surface roughness maps by employing ASTER multispectral classifications with QuickBird "ground reference" imagery.

Spruce, Joe↗

NASA NTRS2004

Determining the Optimum Post Spacing of LIDAR-Derived Elevation Data in Varying Terrain for Flood Hazard Mapping Purposes in North Carolina and Texas

The major flood events in the United States in the past few years have made it apparent that many floodplain maps being used by State governments are outdated and inaccurate. In response, many Stated have begun to update their Federal Emergency Management Agency (FEMA) Digital Flood Insurance Rate Maps. Accurate topographic data is one of the most critical inputs for floodplain analysis and delineation. Light detection and ranging (LIDAR) altimetry is one of the primary remote sensing technologies that can be used to obtain high-resolution and high-accuracy digital elevation data suitable for hydrologic and hydraulic (H&H) modeling, in part because of its ability to "penetrate" various cover types and to record geospatial data from the Earth's surface. However, the posting density or spacing at which LIDAR collects the data will affect the resulting accuracies of the derived bare Earth surface, depending on terrain type and land cover type. For example, flat areas are thought to require higher or denser postings than hilly areas to capture subtle changes in the topography that could have a significant effect on flooding extent. Likewise, if an area has dense understory and overstory, it may be difficult to receive LIDAR returns from the Earth's surface, which would affect the accuracy of that bare Earth surface and thus would affect flood model results. For these reasons, NASA and FEMA have partnered with the State of North Carolina and with the U.S./Mexico Foundation in Texas to assess the effect of LIDAR point density on the characterization of topographic variation and on H&H modeling results for improved floodplain mapping. Research for this project is being conducted in two areas of North Carolina and in the City of Brownsville, Texas, each with a different type of terrain and varying land cover/land use. Because of various project constraints, LIDAR data were acquired once at a high posting density and then decimated to coarser postings or densities. Quality assurance/quality control analyses were performed on each dataset. Cross sections extracted form the high density and then the decimated datasets were individually input into an H&H model to determine the model's sensitivity to topographic variation and the effect of that variation on the resulting water profiles. Additional analysis was performed on the Brownsville, Texas, LIDAR data to determine the percentage of returns that "penetrated" various types of canopy or vegetative cover. It is hoped that the results of these studies will benefit state and local communities as they consider the post spacing at which to acquire LIDAR data (which affects cost) and will benefit FEMA as the Agency assesses the use of different technologies for updating National Flood Insurance Program and related products.

Berglund, Judith↗

NASA NTRS2003

Parameters Describing Earth Observing Remote Sensing Systems

The Earth science community needs to generate consistent and standard definitions for spatial, spectral, radiometric, and geometric properties describing passive electro-optical Earth observing sensors and their products. The parameters used to describe sensors and to describe their products are often confused. In some cases, parameters for a sensor and for its products are identical; in other cases, these parameters vary widely. Sensor parameters are bound by the fundamental performance of a system, while product parameters describe what is available to the end user. Products are often resampled, edge sharpened, pan-sharpened, or compressed, and can differ drastically from the intrinsic data acquired by the sensor. Because detailed sensor performance information may not be readily available to an international science community, standardization of product parameters is of primary performance. Spatial product parameters described include Modulation Transfer Function (MTF), point spread function, line spread function, edge response, stray light, edge sharpening, aliasing, ringing, and compression effects. Spectral product parameters discussed include full width half maximum, ripple, slope edge, and out-of-band rejection. Radiometric product properties discussed include relative and absolute radiometry, noise equivalent spectral radiance, noise equivalent temperature diffenence, and signal-to-noise ratio. Geometric product properties discussed include geopositional accuracy expressed as CE90, LE90, and root mean square error. Correlated properties discussed include such parameters as band-to-band registration, which is both a spectral and a spatial property. In addition, the proliferation of staring and pushbroom sensor architectures requires new parameters to describe artifacts that are different from traditional cross-track system artifacts. A better understanding of how various system parameters affect product performance is also needed to better ascertain the utility of existing datasets and products as well as to specify the performance of new sensors and products. Examples of simulations performed for the Landsat Data Continuity Mission illustrate how various parameters affect system and product performance. Specific examples include the effects of ground sample distance, MTF, and band-to-band registration on various products.

Zanoni, Vicki↗

NASA NTRS2002

Remote Sensing Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properties such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization and band-to-band registration drive sensor platform and spacecraft system architecture and cost, analysis of these criteria is important to optimize system design objectively. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy and geopositional accuracy affect the complexity and cost of calibration methods. However, few studies have quantified the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at the John C. Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated datasets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood.

Zanoni, Vicki↗

NASA NTRS2002

Measurement Sets and Sites Commonly used for Characterizations

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

Pagnutti, Mary↗

NASA NTRS2002

NASA Scientific Data Purchase

The paper discusses the folloving: 1. 50 Million ,Appropriation - Acquire science data from commercial sources. 2. Demonstration Project - Test new way of doing business. Tap new sources of data. Support Earth science research. Support commercial remote sensing industry. 3. Phase I - Review simulated/prototypical datasets (10 companies). 4. Phase II - 3-year purchase/distribution of select data (5 companies). 5. FY01 $20M Appropriation - Commercial Imagery Office Proposed continuation and new contracts.

Davis, Bruce↗

NASA NTRS2002

Measurement Sets and Sites Commonly Used for Characterization

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Pagnutti, Mary↗

NASA NTRS2002

Remote Sensing System Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properites such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization, and band-to-band registration drive sensor platform and spaceraft system architecture and cost, analysis of these criteria is important to objectively optimize system design. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy, and geopositional accuracy affect the complexity and cost of calibration methods. However, there are few studies that quantify the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated data sets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution, and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood. This paper describes the ART and its applicability for rigorously deriving remote sensing data requirements.

Zanoni, Vicki↗

NASA NTRS2001

Nutrient Stress Detection in Corn, Using Neural Networks and AVIRIS Hyperspectral Imagery

The US Department of Agriculture (USDA) Agricultural Research Service (ARS) Variable Rate (VRAT) Nitrogen Application site in Shelton, Nebraska, represents a well-documented, corn-growing quarter section. The USDA VRAT site is used to systematically study nutrient stress in corn by varying sub-plot application of fertilizer. The field has four replicates of five blocks that vary by nitrogen treatment from 0-kg/ha to 200-kg/ha in 50-kg/ha increments. The treatment blocks are set out in a randomized, complete block design. Typically, the VRAT is planted in a ridge till, monoculture corn and is watered by a central pivot irrigation system on a three-day period. Since water stress can increase spectral reflectance from corn leaves, it is important that the N-application plots be adequately watered so that only nutrient-related stress will predominate. A figure shows imagery of the USDA VRAT site with the fertilizer amounts for each block shown. Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery was acquired over the Shelton, Nebraska, VRAT site on July 22, 1999. The overflight produced 3-meter pixels with 224 spectral bands. Ground personnel supported the mission with measurements at the time of the overflight. The image data was pre-processed at JPL before being sent out to an investigator. The data arrived radiometrically corrected, allowing ready application of an atmospheric correction procedure. The Atmosphere Removal Program (ATREM) was used to perform an atmospheric correction. The AVIRIS imagery after ATREM correction was output as relative reflectance. This relative reflectance file was scaled by an empirical line procedure to provide reflectances that matched closely those measured in the field.

Estep, Lee↗

NASA NTRS2001

Earth Science Applications Briefing Package

An overview of the Earth Science Enterprise program is given. The mission is to enhance the near term socioeconomic benefit of NASA'S earth science investment.

Davis, Bruce↗

NASA NTRS2001

Development of Ground Reference GIS for Assessing Land Cover Maps of Northeast Yellowstone National Park

GIS technology and ground reference data often play vital roles in assessing land cover maps derived from remotely sensed data. This poster illustrates these roles, using results from a study done in Northeast Yellowstone National Park. This area holds many forest, range, and wetland cover types of interest to park managers. Several recent studies have focused on this locale, including the NASA Earth Observations Commercial Applications Program (EOCAP) hyperspectral project performed by Yellowstone Ecosystems Studies (YES) on riparian and in-stream habitat mapping. This poster regards a spin-off to the EOCAP project in which YES and NASA's Earth Science Applications Directorate explored the potential for synergistic use of hyperspecral, synthetic aperture radar, and multiband thermal imagery in mapping land cover types. The project included development of a ground reference GIS for site-specific data needed to evaluate maps from remotely sensed imagery. Field survey data included reflectance of plant communities, native and exotic plant species, and forest health conditions. Researchers also collected GPS points, annotated aerial photographs, and took hand held photographs of reference sites. The use of ESRI, ERDAS, and ENVI software enabled reference data entry into a GIS for comparision to georeferenced imagery and thematic maps. The GIS-based ground reference data layers supported development and assessment of multiple maps from remotely sensed data sets acquired over the study area.

Spruce, Joe↗

NASA NTRS1993

The development of a natural language interface to a geographical information system

This paper will discuss a two and a half year long project undertaken to develop an English-language interface for the geographical information system GRASS. The work was carried out for NASA by a small business, Netrologic, based in San Diego, California, under Phase 1 and 2 Small Business Innovative Research contracts. We consider here the potential value of this system whose current functionality addresses numerical, categorical and boolean raster layers and includes the display of point sets defined by constraints on one or more layers, answers yes/no and numerical questions, and creates statistical reports. It also handles complex queries and lexical ambiguities, and allows temporarily switching to UNIX or GRASS.

Toledo, Sue Walker↗