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NASA NTRS1990

Motion detection, novelty filtering, and target tracking using an interferometric technique with a GaAs phase conjugate mirror

A method and apparatus is disclosed for detecting and tracking moving objects in a noise environment cluttered with fast-and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photo-refractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the inter-ferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Cheng, Li-Jen↗

NASA NTRS1990

Use of laser range finders and range image analysis in automated assembly tasks

A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.

Alvertos, Nicolas↗

NASA NTRS1992

Plasmasphere refilling - Recent observations and modeling

The phenomenon of plasmasphere refilling and general considerations of plasmasphere structure and plasmasphere-ionosphere coupling have received increased attention in recent years in terms of both observational considerations and modeling investigations. 'Global' observational and modeling studies of the plasmasphere structure are in the process of demonstrating the complex manner in which refilling and the spatial and temporal variations of convection interplay to produce complex structure in the plasmasphere; these studies are particularly timely as they could be extremely helpful for interpreting results from proposed imaging of plasmaspheric He(+). This review highlights the observational and theoretical/modeling progress during the past few years as well as introduces and places in context the particular contributions contained in this special section.

Singh, M.↗

NASA NTRS1993

Nonlinear waves and solitons in molecular clouds

We begin a study of nonlinear wave phenomena in molecular clouds. These clouds exhibit highly nonlinear structure that is often described in terms of 'clumps' and 'filaments' which are bouncing around, twisting, and colliding within the cloud. These clouds are important because they ultimately produce the initial conditions for the star formation process. Our motivation is to explore the possibility that solitons (i.e., spatially localized, single-hump wave entities which often exhibit remarkable stability) can live in these molecular clouds and produce their observed structure. In this paper we focus on the case of one spatial dimension, and we show that a rich variety of nonlinear waves can exist in molecular cloud fluid systems (where self-gravity is included). We show that in the absence of magnetic fields no true soliton solutions are allowed, although highly nonlinear waves (whose crests become widely spaced and thus soliton-like) do exist. For clouds with embedded magnetic fields, we derive a model equation which describes the behavior of wave phenomena; this model equation allows solutions which correspond to nonlinear waves, solitons, and topological solitons. We briefly consider the stability of these wave entities and discuss the possible role they play in molecular cloud dynamics.

Adams, Fred C.↗

NASA NTRS1993

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗

NASA NTRS1993

EOS SAR: A new approach

Viewgraphs on Earth Observing System (EOS) Synthetic Aperture Radar (SAR) are presented. The goal of the EOS is to develop the modeling and observational capabilities to predict and/or monitor atmospheric, terrestrial, and oceanic processes that are either causing global change or resulting from global change. The EOS SAR goal is to provide important geophysical products to the EOS data set to improve our understanding of the state and functioning of the Earth system. The EOS SAR strategy is to define the instrument requirements based on required input to geophysical algorithms, to provide the processing capability and algorithms to generate such products on the required spatial (global) and temporal (3-5 days) scales, and to provide the spaceborne instrumentation with international partnerships.

Way, Jobea↗

NASA NTRS1993

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.

Brugel, E. W.↗

NASA NTRS1994

Pinatubo Aerosol Evolution: Using Composite Data Sets to Build the Global- To Micro-Scale Picture and Assess Consistency of Different Measurements

This paper brings together experimental evidence required to build realistic models of the global evolution of physical, chemical, and optical properties of the aerosol resulting from the 1991 Pinatubo volcanic eruption. Such models are needed to compute the effects of the aerosol on atmospheric chemistry, dynamics, radiation, and temperature. Whereas there is now a large and crowing body of post-Pinatubo measurements by a variety of techniques, some results are in conflict, and a self-consistent, unified picture is needed, along with an assessment of remaining uncertainties. This paper examines, data from photometers, radiometers, impactors, optical counter/sizers, and lidars operated on the ground, aircraft, balloons, and spacecraft. Example data sources include: (1) Tracking sunphotometers and lidars at Mauna Loa Observatory (MLO) and on the DC-8. (2) Particle spectrometers and wire impactors on the ER-2 and DC-8. (3) Dustsondes (particle counter/sizers on balloons). and (3) SAGE II, SAM II, AVHRR, CLAES, and ISAMS sensors on a variety of satellites. We assess the mutual consistency of these disparate data sets and recommend 'consensus' properties and uncertainties in the process of developing a composite data set. Recommended properties include the spatial and temporal evolution of particle chemical composition, shape, wavelength-and temperature-dependent refractive index, size distribution, and optical depth spectra. Supporting references are cited and representative data shown.

Russell, Philip B.↗

NASA NTRS1994

Pinatubo Aerosol Evolution: Using Composite Data Sets to Build the Global- to Micro-Scale Picture and Assess Consistency of Different Measurements

This paper brings together experimental evidence required to build realistic models of the global evolution of physical, chemical, and optical properties of the aerosol resulting from the 1991 Pinatubo volcanic eruption. Such models are needed to compute the effects of the aerosol on atmospheric chemistry, dynamics, radiation, and temperature. Whereas there is now a large and growing body of post-Pinatubo measurements by a variety of techniques, some results are in conflict, and a self-consistent, unified picture is needed, along with an assessment of remaining uncertainties. This paper examines data from photometers, radiometers, impactors, optical counters/sizers, and lidars operated on the ground, aircraft, balloons, and spacecraft. Example data sources include: - Tracking sunphotometers and lidars at Mauna Loa Observatory (MLO) and on the DC-8 - Particle spectrometers and wire impactors on the ER-2 and DC-8 - Dustsondes (particle counters/sizers on balloons) - SAGE II, SAM II, AVHRR, CLAES, and ISAMS sensors on a variety of satellites. We assess the mutual consistency of these disparate data sets and recommend 'consensus" properties and uncertainties in the process of developing a composite data set. Recommended properties include the spatial and temporal evolution of particle chemical composition, shape, wavelength and temperature-dependent refractive index, size distribution, and optical depth spectra. Supporting references are cited and representative data shown.

Russell, P. B.↗

NASA NTRS2007

The Many Worlds of Transition Research.

The transition from laminar to turbulent flow in a boundary layer is a complex phenomenon that may take different routes, each involving distinct stages governed by different, often not-yet unraveled dynamical principles. There are, surprisingly, questions concerning virtually every stage in the process, beginning with receptivity to external disturbances, the linear stability of spatially developing flows, different possible nonlinear end games, the formation and propagation of turbulent spots and the emergence of fully developed turbulent flow. There seems no doubt that the flow has to be seen as a forced, nonlinear spatio-temporal system, but the system is so complex that to extract simple insights is still very difficult.

Narasimha, R.↗

NASA NTRS1991

Motion detection, novelty filtering, and target tracking using an interferometric technique with GaAs phase conjugate mirror

A method and apparatus for detecting and tracking moving objects in a noise environment cluttered with fast- and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photorefractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the interferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Cheng, Li-Jen↗

NASA NTRS2006

New Raman Water Vapor and Temperature Lidar at JPL Table Mountain Facility: Optimization, Validations and Sonde Intercomparison

Jet Propulsion Laboratory currently operates lidar systems at Table Mountain Facility (TMF), California (34.4 deg N, 117.7 deg W at 2300m) and Mauna Loa Observatory (MLO), Hawaii (19.5 deg N, 155.6 deg W at 3400m) under the Network for the Detection of Atmospheric Composition Change (NDACC, formerly NDSC). To complement existing NDACC lidars at TMF, which acts as a primary site for inter-comparisons, a new water vapor and temperature lidar has begun routine operation with typically 3-4 nightly profiles per week. As water vapor is a key greenhouse gas, and is highly variable on annual and seasonal cycles, accurate long term measurements are necessary for predictions of climate change and to increase our understanding of the atmospheric processes it contributes to. The new TMF lidar has demonstrated high spatial and temporal resolution, with a high degree of optimization being achieved over the past year, although the authors believe further improvement may yet be possible. The lidar has been designed for accuracies of 5% up to 12km in the free troposphere with the capability to measure to the tropopause and lower stratosphere with accuracies of 1 ppm. It is anticipated that the data sets produced will be used for Aura validation and for incorporation into NDACC archives. Validation results for the optimized system are presented with intercomparisons using Vaisala RS92-K radiosondes.

water vapor↗

NASA NTRS2014

Science Goals and Mission Concept for the Future Exploration of Titan and Enceladus

Saturn׳s moons, Titan and Enceladus, are two of the Solar System׳s most enigmatic bodies and are prime targets for future space exploration. Titan provides an analogue for many processes relevant to the Earth, more generally to outer Solar System bodies, and a growing host of newly discovered icy exoplanets. Processes represented include atmospheric dynamics, complex organic chemistry, meteorological cycles (with methane as a working fluid), astrobiology, surface liquids and lakes, geology, fluvial and aeolian erosion, and interactions with an external plasma environment. In addition, exploring Enceladus over multiple targeted flybys will give us a unique opportunity to further study the most active icy moon in our Solar System as revealed by Cassini and to analyse in situ its active plume with highly capable instrumentation addressing its complex chemistry and dynamics. Enceladus׳ plume likely represents the most accessible samples from an extra-terrestrial liquid water environment in the Solar system, which has far reaching implications for many areas of planetary and biological science. Titan with its massive atmosphere and Enceladus with its active plume are prime planetary objects in the Outer Solar System to perform in situ investigations. In the present paper, we describe the science goals and key measurements to be performed by a future exploration mission involving a Saturn-Titan orbiter and a Titan balloon, which was proposed to ESA in response to the call for definition of the science themes of the next Large-class mission in 2013. The mission scenario is built around three complementary science goals: (A) Titan as an Earth-like system; (B) Enceladus as an active cryovolcanic moon; and (C) Chemistry of Titan and Enceladus - clues for the origin of life. The proposed measurements would provide a step change in our understanding of planetary processes and evolution, with many orders of magnitude improvement in temporal, spatial, and chemical resolution over that which is possible with Cassini-Huygens. This mission concept builds upon the successes of Cassini-Huygens and takes advantage of previous mission heritage in both remote sensing and in situ measurement technologies.

future missions↗

NASA NTRS2014

NASA World Wind: Visualization Technology for Spatial Data

Spatial information intelligence is a global issue that will increasingly affect our ability to survive as a species. Collectively we must better appreciate the complex relationships that make life on Earth possible. Providing spatial information in its native context can accelerate our ability to process that information. To maximize this ability to process information, three basic elements are required: data delivery (server technology), data access (client technology), and data processing (information intelligence). NASA World Wind provides the open source client technology based on open standards. The possibilities for data processing and data sharing are enhanced by this inclusive infrastructure for geographic information. It is interesting that this open source and open standards approach, unfettered by proprietary constraints, provides for unlimited innovation with this technology.

Geospatial↗

NASA NTRS2019

Evaluating Combinations of Sentinel-2 Data and Machine-Learning Algorithms for Mangrove Mapping in West Africa

Creating a national baseline for natural resources, such as mangrove forests, and monitoring them regularly often requires a consistent and robust methodology. With freely available satellite data archives and cloud computing resources, it is now more accessible to conduct such large-scale monitoring and assessment. Yet, few studies examine the reproducibility of such mangrove monitoring frameworks, especially in terms of generating consistent spatial extent. Our objective was to evaluate a combination of image processing approaches to classify mangrove forests along the coast of Senegal and The Gambia. We used freely available global satellite data (Sentinel-2), and cloud computing platform (Google Earth Engine) to run two machine learning algorithms, random forest (RF), and classification and regression trees (CART). We calibrated and validated the algorithms using 800 reference points collected using high-resolution images. We further re-ran 10 iterations for each algorithm, utilizing unique subsets of the initial training data. While all iterations resulted in thematic mangrove maps with over 90% accuracy, the mangrove extent ranges between 827-2807 km2 for Senegal and 245-1271 km2 for The Gambia with one outlier for each country. We further report "Places of Agreement" (PoA) to identify areas where all iterations for both methods agree (506.6 km2 and 129.6 km2 for Senegal and The Gambia, respectively), thus have a high confidence in predicting mangrove extent. While we acknowledge the time- and cost-effectiveness of such methods for the landscape managers, we recommend utilizing them with utmost caution, as well as post-classification on-the-ground checks, especially for decision making.

Mondal, Pinki↗

NASA NTRSDate not supplied

MONITORING ECO-HYDROLOGICAL SPRING ONSET OVER ALASKA AND NORTHERN CANADA WITH COMPLEMENTARY SATELLITE REMOTE SENSING DATA

Youngwook Kim↗

NASA NTRS2021

Monitoring Eco-Hydrological Spring Onset Over Alaska and Northern Canada With Complementary Satellite Remote Sensing Data

More than half of the global land area undergoes seasonal freeze/thaw (FT) transitions in spring. Spatial patterns and timing of spring thawing influence eco-hydrological processes and landscape moisture availability over arctic and boreal ecosystems. The seasonal progression of spring thawing coincides with warmer temperatures, snowmelt, and a rapid increase in soil moisture, which initiates the growing season for ecosystem productivity. In this study, we utilize complementary satellite observations to determine the pattern and order of occurrence in landscape thawing, soil moisture increase, and ecosystem productivity that collectively define the eco-hydrological spring onset across Alaska and Northern Canada. Satellite data utilized include landscape FT status from SMAP and AMSR-2, OCO-2 derived solar-induced chlorophyll fluorescence (GOSIF), and gross primary production (GPP) and soil moisture from SMAP. The resulting spring onset maps showed spring thawing as the precursor to growing season onset, indicated by a rapid rise in available soil moisture and GPP. Our results indicated an average spring transition period of 3±2 (SD) weeks between initial landscape thawing and growing season onset. A rapid increase in soil moisture generally followed landscape thawing but occurred before the subsequent seasonal rise in GPP. Spring onset generally occurred earlier in boreal forest (DOY 102±14) than arctic tundra (DOY 124±22).

Derksen, Chris↗

NASA NTRS2006

Optimization as a Tool for Consistency Maintenance in Multi-Resolution Simulation

The need for new approaches to the consistent simulation of related phenomena at multiple levels of resolution is great. While many fields of application would benefit from a complete and approachable solution to this problem, such solutions have proven extremely difficult. We present a multi-resolution simulation methodology that uses numerical optimization as a tool for maintaining external consistency between models of the same phenomena operating at different levels of temporal and/or spatial resolution. Our approach follows from previous work in the disparate fields of inverse modeling and spacetime constraint-based animation. As a case study, our methodology is applied to two environmental models of forest canopy processes that make overlapping predictions under unique sets of operating assumptions, and which execute at different temporal resolutions. Experimental results are presented and future directions are addressed.

TEMPORAL RESOLUTION↗