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At least 91 records · Page 5

Spatial quantification of maps or images - Cell size or pixel size implications

The paper discusses spatial quantification of maps or images. Spatial accuracies evaluated by mapping and inventory measures were observed with a range of cell sizes for a 10.36 sq km soil survey segment. The distribution of interboundary distances in a map was evaluated as unique, characterizing information; experimentally observed relationships between accuracy and cell size and interboundary distance distribution parameters and cell size led to a model of the process of spatial quantization. Grid positioning effects were evaluated and were significant only at the level of individual mapping units; two generations of 'universal' process models were derived, implemented, and evaluated.

Wehde, M. E.↗

Feeding Ten Billion People Is Possible Within Four Terrestrial Planetary Boundaries

Global agriculture puts heavy pressure on planetary boundaries, posing the challenge to achieve future food security without compromising Earth system resilience. On the basis of process-detailed, spatially explicit representation of four interlinked planetary boundaries (biosphere integrity, land-system change, freshwater use, nitrogen flows) and agricultural systems in an internally consistent model framework, we here show that almost half of current global food production depends on planetary boundary transgressions. Hotspot regions, mainly in Asia, even face simultaneous transgression of multiple underlying local boundaries. If these boundaries were strictly respected, the present food system could provide a balanced diet (2,355 kcal per capita per day) for 3.4 billion people only. However, as we also demonstrate, transformation towards more sustainable production and consumption patterns could support 10.2 billion people within the planetary boundaries analysed. Key prerequisites are spatially redistributed cropland, improved water–nutrient management, food waste reduction and dietary changes. Adoption of the Sustainable Development Goals by all nations in 2015 is the first ever commitment to a world development path that safeguards the stability of the Earth system as a prerequisite for meeting universal human standards1. The longstanding challenge of achieving food security through sustainable agriculture is particularly acute in this context as world agriculture is a leading cause for the current transgressions of multiple planetary boundaries (PBs) globally and regionally2–5. The PB framework is a comprehensive scientific attempt to synoptically define our planet’s biogeophysical limits to anthropogenic interference. It suggests bounds to nine interacting processes that together delineate a Holocene-like Earth system state. The Holocene is chosen as the reference state as it is the only period known to provide a safe operating space for a world population of several billion people, and according to a precautionary principle, the PBs are set in sufficient distance from processes that may critically undermine Earth system resilience and global sustainability. A challenging question, thus, is whether human development goals such as food security can be met while maintaining multiple PBs along with their subglobal manifestations. Further PB transgressions could jeopardize the chances of providing sufficient food for a world population projected to be wealthier and reach >9 billion by 2050. This conundrum portrays a tradeoff between Earth’s biophysical carrying capacity and humankind’s rising food demand, calling in response for radical rethinking of food production and consumption patterns6–9. Yield gap closures, avoidance of excessive input use, shifts towards less resource-demanding diets, food waste reductions and efficient international trade are crucial options for sustainably increasing the food supply10–15. For example, enhancing water-use efficiency on irrigated and rain-fed farms can triple or quadruple crop yields in low-performing systems, suggesting possible global gains of >20% (ref. 16). Even higher gains appear feasible through globally optimized configurations of the land-use pattern17, and cutting food losses by half could generate food for another billion people18. Thus, collective large-scale implementation of such options could sustain food for a further growing world population19. Yet achieving this within a safe operating space as defined by PBs requires not only a halt to but actually a reversal of existing PB transgressions. Previous studies suggest that such a reconciliation might be possible, but these were based on aggregate representations of PBs (not accounting for the spatial patterns of limits, transgressions and interactions) or considered only one boundary in isolation17,20–23. Here, we systematically quantify to what extent current food production depends on local to global transgressions of the PBs for biosphere integrity, land-system change, freshwater use and nitrogen (N) flows, along with the potential of a range of solutions to avoid these transgressions and still increase food supply (Table 1). To this end, we configured an internally consistent process-based model of the terrestrial biosphere including agriculture (LPJmL) with multiple spatially distributed PBs and their interactions. LPJmL is among the longest-established and best-evaluated biosphere models, showing robust performance regarding simulation of, for example, carbon, water and crop yield dynamics (Supplementary Figs. 1 and 2 and Supplementary Table 1; see ref. 24 for a comprehensive benchmarking and Supplementary Methods for more detail on model evaluations). In principle following established definitions4, we refine the computation of some PBs with respect to their regional patterns and interactions (Methods), providing globally gridded precautionary limits to human interference with the Earth system at a level of great detail. In particular, we account for the evidence that many PBs need to be represented spatially explicitly4 to cover their

Gerten, Dieter↗

Behavioral Assessment of Spaceflight Effects on Neurocognitive Performance: Extent and Longevity

Exposure to the microgravity environment during spaceflight missions impacts crewmembers' sensorimotor function. Bock et al. [1] studied the cognitive demands of human sensorimotor performance and dual tasking during long duration missions and concluded that both stress and scarcity of cognitive resources required for sensorimotor adaptation may be responsible for these deficits during spaceflight. Therefore, in consideration of the health and performance of crewmembers in- and post-flight, we are conducting this study to investigate the effects of spaceflight on the extent, longevity and neural bases of sensorimotor, cognitive, and neural changes. The data presented will focus on the behavioral measures that were collected pre-, in- and post-flight including spatial cognition, processing speed, bimanual coordination, functional mobility, computerized dynamic posturography (CDP), and vibrotactile induced vestibular evoked myogenic potential (VEMP). To date, data were collected over the course of two pre-flight sessions and four post-flight sessions on five crewmembers (n=13) using the protocol described in Koppelmans et al. [2]. Balance control was assessed using CDP, with eyes closed and a sway-referenced base of support (Sensory Organization Test 5), with and without head movements in the pitch plane. Spatial working memory was assessed using Thurston's Card Rotation Test and a Mental Rotation Test. The Rod and Frame Test was performed to test visual dependence. The Digit Symbol Substitution Test was performed to evaluate processing speed, and the Purdue Pegboard Task was performed to test bimanual coordination. Vestibular function was assessed by eliciting ocular VEMP via a hand held striker on the side of the head as subjects lay supine on a gurney. Subjects also performed the Functional Mobility Test of walking through an obstacle course to assess rate of early motor learning. Data were also collected on the same crewmembers during three in-flight sessions on the International Space Station (ISS). In-flight, spatial working memory was assessed using the Mental Rotation Test, adaptation to visuo-motor transformation in manual control was assessed using the Sensorimotor Adaptation Test, and multi-tasking ability was assessed using the Dual Task Test. These three tests were performed in a strapped-in configuration mimicking a seated position - waist bungees pulled the crewmember toward the "floor" with feet secured in foot loops. The Mental Rotation Test was also performed in a free-floating configuration while the crewmember floated while holding on to the gamepad controller used to provide input that was secured to the equipment rack on the ISS. Preliminary findings from data collected to date, will be included in the presentation. Eventual comparison to results from supporting bed rest and longitudinal studies will enable the parsing out of the multiple mechanisms contributing to any observed spaceflight-induced sensorimotor and cognitive behavioral changes.

De Dios, Y. E.↗

Agent-based modeling of microbes in space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).

Jessica A Lee↗

Agent-Based Modeling of Microbes in Space

Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal gravity, and much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER growth curves recapitulate experimental results, and allow comparison between direct effects (DNA damage) and indirect effects (reactive oxygen species generation, metabolic impairment) of radiation.

microbiology↗

Regulatory gene networks and the properties of the developmental process

Genomic instructions for development are encoded in arrays of regulatory DNA. These specify large networks of interactions among genes producing transcription factors and signaling components. The architecture of such networks both explains and predicts developmental phenomenology. Although network analysis is yet in its early stages, some fundamental commonalities are already emerging. Two such are the use of multigenic feedback loops to ensure the progressivity of developmental regulatory states and the prevalence of repressive regulatory interactions in spatial control processes. Gene regulatory networks make it possible to explain the process of development in causal terms and eventually will enable the redesign of developmental regulatory circuitry to achieve different outcomes.

Non-NASA Center↗

Visual Orientation in Unfamiliar Gravito-Inertial Environments

The goal of this project is to better understand the process of spatial orientation and navigation in unfamiliar gravito-inertial environments, and ultimately to use this new information to develop effective countermeasures against the orientation and navigation problems experienced by astronauts. How do we know our location, orientation, and motion of our body with respect to the external environment ? On earth, gravity provides a convenient "down" cue. Large body rotations normally occur only in a horizontal plane. In space, the gravitational down cue is absent. When astronauts roll or pitch upside down, they must recognize where things are around them by a process of mental rotation which involves three dimensions, rather than just one. While working in unfamiliar situations they occasionally misinterpret visual cues and experience striking "visual reorientation illusions" (VRIs), in which the walls, ceiling, and floors of the spacecraft exchange subjective identities. VRIs cause disorientation, reaching errors, trigger attacks of space motion sickness, and potentially complicate emergency escape. MIR crewmembers report that 3D relationships between modules - particularly those with different visual verticals - are difficult to visualize, and so navigating through the node that connects them is not instinctive. Crew members learn routes, but their apparent lack of survey knowledge is a concern should fire, power loss, or depressurization limit visibility. Anecdotally, experience in mockups, parabolic flight, neutral buoyancy and virtual reality (VR) simulators helps. However, no techniques have been developed to quantify individual differences in orientation and navigation abilities, or the effectiveness of preflight visual. orientation training. Our understanding of the underlying physiology - for example how our sense of place and orientation is neurally coded in three dimensions in the limbic system of the brain - is incomplete. During the 16 months that this human and animal research project has been underway, we have obtained several results that are not only of basic research interest, but which have practical implications for the architecture and layout of spacecraft interiors and for the development of astronaut spatial orientation training countermeasures.

Oman, Charles M.↗

Quantitative modeling of soil genesis processes

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

Levine, E. R.↗

Validating spatial structure in canopy water content using geostatistics

Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.

Sanderson, E. W.↗

A Virtual Audio Guidance and Alert System for Commercial Aircraft Operations

Our work in virtual reality systems at NASA Ames Research Center includes the area of aurally-guided visual search, using specially-designed audio cues and spatial audio processing (also known as virtual or "3-D audio") techniques (Begault, 1994). Previous studies at Ames had revealed that use of 3-D audio for Traffic Collision Avoidance System (TCAS) advisories significantly reduced head-down time, compared to a head-down map display (0.5 sec advantage) or no display at all (2.2 sec advantage) (Begault, 1993, 1995; Begault & Pittman, 1994; see Wenzel, 1994, for an audio demo). Since the crew must keep their head up and looking out the window as much as possible when taxiing under low-visibility conditions, and the potential for "blunder" is increased under such conditions, it was sensible to evaluate the audio spatial cueing for a prototype audio ground collision avoidance warning (GCAW) system, and a 3-D audio guidance system. Results were favorable for GCAW, but not for the audio guidance system.

Begault, Durand R.↗

Pushing the Limits of Aquatic Remote Sensing: Synthetic Data and Deep Learning for Fast Inverse Emulation of A Coupled Ocean-Atmosphere Radiative Transfer Model

The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.

Jeremy Alan Kravitz↗

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗

Optical-noise supression unit: A concept

Device is used with coherent optical-processing spatial-filtering computer. It is isexpensive to manufacture and is made from readily available standard components. Its alignment is not critical.

Horner, J. L.↗

A two-dimensional finite difference solution for the transient thermal behavior of tubular solar collector

A numerical procedure was established using the finite-difference technique in the determination of the time-varying temperature distribution of a tubular solar collector under changing solar radiancy and ambient temperature. Three types of spatial discretization processes were considered and compared for their accuracy of computations and for selection of the shortest computer time and cost. The stability criteria of this technique was analyzed in detail to give the critical time increment to ensure stable computations. The results of the numerical analysis were in good agreement with the analytical solution previously reported. The numerical method proved to be a powerful tool in the investigation of the collector sensitivity to two different flow patterns and several flow control mechanisms.

Lansing, F. L.↗

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

Tom, C.↗

A two-dimensional finite-difference solution for the transient thermal behavior of a tubular solar collector

A numerical procedure was established using the finite-difference technique in the determination of the time-varying temperature distribution of a tubular solar collector under changing solar radiancy and ambient temperature. Three types of spatial discretization processes were considered and compared for their accuracy of computations and for selection of the shortest computer time and cost. The stability criteria of this technique were analyzed in detail to give the critical time increment to ensure stable computations. The results of the numerical analysis were in good agreement with the analytical solution previously reported. The numerical method proved to be a powerful tool in the investigation of the collector sensitivity to two different flow patterns and several flow control mechanisms.

Lansing, F. L.↗