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NASA NTRS1996

(abstract) A High Throughput 3-D Inner Product Processor

A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated.

imaging parallel processing algorithms linear vect↗

NASA NTRS2004

Sensor Web for Spatio-Temporal Monitoring of a Hydrological Environment

The Sensor Web is a macroinstrument concept that allows for the spatio-temporal understanding of an environment through coordinated efforts between multiple numbers and types of sensing platforms, including, in its most general form, both orbital and terrestrial and both fixed and mobile. Each of these platforms, or pods, communicates within its local neighborhood and thus distributes information to the instrument as a whole. The result of sharing and continual processing of this information among all the Sensor Web elements will result in an information flow and a global perception of and reactive capability to the environment. As illustrated, the Sensor Web concept also allows for the recursive notion of a web of webs with individual distributed instruments possibly playing the role of a single node point on a larger Sensor Web instrument. In particular, the fusion of inexpensive, yet sophisticated, commercial technology from both the computation and telecommunication revolutions has enabled the development of practical, fielded, and embedded in situ systems that have been the focus of the NASA/JPL Sensor Webs Project (http://sensorwebs.jpl.nasa.gov/). These Sensor Webs are complete systems consisting of not only the pod elements that wirelessly communicate among themselves, but also interfacing and archiving software that allows for easy use by the end-user. Previous successful deployments have included environments as diverse as coastal regions, Antarctica, and desert areas. The Sensor Web has broad implications for Earth and planetary science and will revolutionize the way experiments and missions are conceived and performed. As part of our current efforts to develop a macrointelligence within the system, we have deployed a Sensor Web at the Central Avra Valley Storage and Recovery Project (CAVSARP) facility located west of Tucson, AZ. This particular site was selected because it is ideal for studying spatio-temporal phenomena and for providing a test site for more sophisticated hydrological studies in the future.

Delin, K. A.↗

NASA NTRS2013

Processing of KaRIn/SWOT Data

The Surface Water and Ocean Topography (SWOT) mission [1] is part of NASA’s Decadal Survey Program, and prepared jointly by NASA’s Jet Propulsion Laboratory (JPL), the French space agency (CNES), and the Canadian space agency (CSA). Launch is currently foreseen in 2020. The principal instrument KaRIn (Ka-band Radar Interferometer) would be a bistatic SAR system operating at Kaband, with 200 MHz bandwidth, covering 50 km wide near-nadir swaths (1-4° incidence) on both sides of the satellite track. The nominal payload also would include a conventional Ku/C-band nadir altimeter, a water vapor radiometer, and a precise orbit determination suite. Moreover, additional near-nadir channels from KaRIn to reduce the gap between the nominal swaths may be considered. The main mission goals would be to improve the spatio-temporal coverage of the oceans with respect to today’s nadir-looking altimeters (such as the Jason series), by providing measurements on a 1 km2 grid with virtually complete coverage up to ±78° latitude, while keeping a height precision of 1-2 cm, and to extend the altimetry measurements to continental water surfaces, including lakes, reservoirs and wetlands bigger than 250x250 m2 and rivers down to a width of 100 m (50 m as a goal), with a height precision of the order of 10 cm, represented with a horizontal point spacing of about 50 m. The fine scale of the measurements, with continuous acquisition over both oceans and continents, will result in huge data volumes, starting at the spacecraft and flowing through all links of the ground system. Furthermore, the centimetric height accuracy required means that all aspects of the processing must be considered carefully. In this article we give an overview of the foreseen data products and data processing chains for KaRIn on SWOT. Some particularly challenging processing steps are (will be) described in more detail.

Desroches, Damien↗

NASA NTRS2011

The Impact of Rise of the Andes and Amazon Landscape Evolution on Diversification of Lowland terra-firme Forest Birds

Since the 19th Century, the unmatched biological diversity of Amazonia has stimulated a diverse set of hypotheses accounting for patterns of species diversity and distribution in mega-diverse tropical environments. Unfortunately, the evidence supporting particular hypotheses to date is at best described as ambiguous, and no generalizations have emerged yet, mostly due to the lack of comprehensive comparative phylogeographic studies with thorough trans-Amazonian sampling of lineages. Here we report on spatial and temporal patterns of diversification estimated from mitochondrial gene trees for 31 lineages of birds associated with upland terra-firme forest, the dominant habitat in modern lowland Amazonia. The results confirm the pervasive role of Amazonian rivers as primary barriers separating sister lineages of birds, and a protracted spatio-temporal pattern of diversification, with a gradual reduction of earlier (1st and 2nd) and older (> 2 mya) splits associated with each lineage in an eastward direction. (The easternmost tributaries of the Amazon, the Xingu and Tocantins Rivers, are not associated with any splits older than > 2 mya). For the suboscine passerines, maximum-likelihood estimates of rates of diversification point to an overall constant rate over the past 5 my (up to a significant downturn at 300,000 y ago). This "younging-eastward" pattern may have an abiotic explanation related to landscape evolution. Triggered by a new pulse of Andean uplift, it has been proposed that modern Amazon basin landscapes may have evolved successively eastward, away from the mountain chain, starting approximately 10 mya. This process was likely based on the deposition of vast fluvial sediment masses, known as megafans, that may have extended progressively and in series eastward from Andean sources. This process plausibly explains the progressive extinction of original Pebas wetland of western-central Amazonia by the present fluvial landsurfaces of a more terra-firme type. The youngest landsurfaces thus lie furthest from the mountains. In this scenario major drainages were also reoriented in wholesale fashion away from a northerly orientation generally towards the east and an Atlantic Ocean outlet. The advance of megafans is best seen by the location of axial rivers such as the Orinoco and Mamore which lie against the cratonic margins furthest from the Andes, at the distal ends of major megafan ramparts. More importantly, other major river courses in western-central Amazonia will have been established at progressively younger dates with distance eastward. If this landscape-sequence scenario is accurate, it parallels the progressive younging of the passerine lineages. The bird DNA data appears to confirm strongly the pervasive role of Amazonian rivers--as primary barriers separating sister lineages of birds, and thus probably as facilitaters of bird speciation. We show for the first time that a general spatio-temporal pattern of diversification for terra-firme lineages in the Amazon is associated with rivers ("younging-eastward"), and furthermore parallels a specific scenario of regional drainage evolution.

Aleixo, Alexandre↗

NASA NTRS2016

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

upscaling↗

NASA NTRS2022

Opportunistic Experiments to Constrain Aerosol Effective Radiative Forcing

Aerosol-cloud interactions (ACI) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The non-linearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well defined sources provide ‘opportunistic experiments’ (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatio-temporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors.We review the different experimental conditions and conduct a synthesis of the available satellite data sets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Matthew W Christensen↗

NASA NTRS2001

The Cool Flames Experiment

A space-based experiment is currently under development to study diffusion-controlled, gas-phase, low temperature oxidation reactions, cool flames and auto-ignition in an unstirred, static reactor. At Earth's gravity (1g), natural convection due to self-heating during the course of slow reaction dominates diffusive transport and produces spatio-temporal variations in the thermal and thus species concentration profiles via the Arrhenius temperature dependence of the reaction rates. Natural convection is important in all terrestrial cool flame and auto-ignition studies, except for select low pressure, highly dilute (small temperature excess) studies in small vessels (i.e., small Rayleigh number). On Earth, natural convection occurs when the Rayleigh number (Ra) exceeds a critical value of approximately 600. Typical values of the Ra, associated with cool flames and auto-ignitions, range from 104-105 (or larger), a regime where both natural convection and conduction heat transport are important. When natural convection occurs, it alters the temperature, hydrodynamic, and species concentration fields, thus generating a multi-dimensional field that is extremely difficult, if not impossible, to be modeled analytically. This point has been emphasized recently by Kagan and co-workers who have shown that explosion limits can shift depending on the characteristic length scale associated with the natural convection. Moreover, natural convection in unstirred reactors is never "sufficiently strong to generate a spatially uniform temperature distribution throughout the reacting gas." Thus, an unstirred, nonisothermal reaction on Earth does not reduce to that generated in a mechanically, well-stirred system. Interestingly, however, thermal ignition theories and thermokinetic models neglect natural convection and assume a heat transfer correlation of the form: q=h(S/V)(T(bar) - Tw) where q is the heat loss per unit volume, h is the heat transfer coefficient, S/V is the surface to volume ratio, and (T(bar) - Tw ) is the spatially averaged temperature excess. This Newtonian form has been validated in spatially-uniform, well-stirred reactors, provided the effective heat transfer coefficient associated with the unsteady process is properly evaluated. Unfortunately, it is not a valid assumption for spatially-nonuniform temperature distributions induced by natural convection in unstirred reactors. "This is why the analysis of such a system is so difficult." Historically, the complexities associated with natural convection were perhaps recognized as early as 1938 when thermal ignition theory was first developed. In the 1955 text "Diffusion and Heat Exchange in Chemical Kinetics", Frank-Kamenetskii recognized that "the purely conductive theory can be applied at sufficiently low pressure and small dimensions of the vessel when the influence of natural convection can be disregarded." This was reiterated by Tyler in 1966 and further emphasized by Barnard and Harwood in 1974. Specifically, they state: "It is generally assumed that heat losses are purely conductive. While this may be valid for certain low pressure slow combustion regimes, it is unlikely to be true for the cool flame and ignition regimes." While this statement is true for terrestrial experiments, the purely conductive heat transport assumption is valid at microgravity (mu-g). Specifically, buoyant complexities are suppressed at mu-g and the reaction-diffusion structure associated with low temperature oxidation reactions, cool flames and auto-ignitions can be studied. Without natural convection, the system is simpler, does not require determination of the effective heat transfer coefficient, and is a testbed for analytic and numerical models that assume pure diffusive transport. In addition, mu-g experiments will provide baseline data that will improve our understanding of the effects of natural convection on Earth.

Pearlman, Howard↗

NASA NTRS2010

Reception of Multiple Telemetry Signals via One Dish Antenna

A microwave aeronautical-telemetry receiver system includes an antenna comprising a seven-element planar array of receiving feed horns centered at the focal point of a paraboloidal dish reflector that is nominally aimed at a single aircraft or at multiple aircraft flying in formation. Through digital processing of the signals received by the seven feed horns, the system implements a method of enhanced cancellation of interference, such that it becomes possible to receive telemetry signals in the same frequency channel simultaneously from either or both of two aircraft at slightly different angular positions within the field of view of the antenna, even in the presence of multipath propagation. The present system is an advanced version of the system described in Spatio- Temporal Equalizer for a Receiving-Antenna Feed Array NPO-43077, NASA Tech Briefs, Vol. 34, No. 2 (February 2010), page 32. To recapitulate: The radio-frequency telemetry signals received by the seven elements of the array are digitized, converted to complex baseband form, and sent to a spatio-temporal equalizer that consists mostly of a bank of seven adaptive finite-impulse-response (FIR) filters (one for each element in the array) plus a unit that sums the outputs of the filters. The combination of the spatial diversity of the feedhorn array and the temporal diversity of the filter bank affords better multipath suppression performance than is achievable by means of temporal equalization alone. The FIR filter bank adapts itself in real time to enable reception of telemetry at a low bit error rate, even in the presence of frequency-selective multipath propagation like that commonly found at flight-test ranges. The combination of the array and the filter bank makes it possible to constructively add multipath incoming signals to the corresponding directly arriving signals, thereby enabling reductions in telemetry bit-error rates.

Mukai, Ryan↗

NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗