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The effect of spatial resolution upon texture-based cloud field classifications

The loss of cloud-classification accuracy as a function of spatial resolution is assessed by investigating the variation of textural measures as a function of spatial resolution. Landsat MSS imagery is progressively averaged to produce degraded imagery of 1/8-km, 1/4-km, 1/2-km, and 1-km spatial resolution, and textural measures are computed from the Gray Level Difference Vector (GLDV) approach described by Chen et al. (1989). It is found that the classification accuracies obtained using the 1/8-km spatial resolution data are similar to those obtained using the full-resolution (1/16 km) texture measures, indicating that there is no advantage in using even higher spatial resolution 30-m Landsat Thematic Mapper and 10-m SPOT imagery for cloud classification.

Welch, R. M.

A discrepancy within primate spatial vision and its bearing on the definition of edge detection processes in machine vision

The visual perception of form information is considered to be based on the functioning of simple and complex neurons in the primate striate cortex. However, a review of the physiological data on these brain cells cannot be harmonized with either the perceptual spatial frequency performance of primates or the performance which is necessary for form perception in humans. This discrepancy together with recent interest in cortical-like and perceptual-like processing in image coding and machine vision prompted a series of image processing experiments intended to provide some definition of the selection of image operators. The experiments were aimed at determining operators which could be used to detect edges in a computational manner consistent with the visual perception of structure in images. Fundamental issues were the selection of size (peak spatial frequency) and circular versus oriented operators (or some combination). In a previous study, circular difference-of-Gaussian (DOG) operators, with peak spatial frequency responses at about 11 and 33 cyc/deg were found to capture the primary structural information in images. Here larger scale circular DOG operators were explored and led to severe loss of image structure and introduced spatial dislocations (due to blur) in structure which is not consistent with visual perception. Orientation sensitive operators (akin to one class of simple cortical neurons) introduced ambiguities of edge extent regardless of the scale of the operator. For machine vision schemes which are functionally similar to natural vision form perception, two circularly symmetric very high spatial frequency channels appear to be necessary and sufficient for a wide range of natural images. Such a machine vision scheme is most similar to the physiological performance of the primate lateral geniculate nucleus rather than the striate cortex.

Jobson, Daniel J.

High-latitude distributions of plasma waves and spatial irregularities from DE 2 alternating current electric field observations

The high-latitude spatial distributions of average signal intensities in 12 frequency channels between 4 Hz and 512 kHz as measured by the ac electric field spectrometers on the DE-2 spacecraft are analyzed for 18 mo of measurements. In MLT-INL (magnetic local time-invariant latitude) there are three distinct distributions that can be identified with 4-512 Hz signals from spatial irregularities and Alfven waves, 256-Hz to 4.1-kHz signals from ELF hiss, and 4.1-64 kHz signals from VLF auroral hiss, respectively. Overlap between ELF hiss and spatial irregularity signals occurs in the 256-512 Hz band. VLF hiss signals extend downward in frequency into the 1.0-4.1 kHz band and upward into the frequency range 128-512 kHz. The distinctly different spatial distribution patterns for the three bands, 4-256 Hz, 512-1204 Hz, and 4.1-64 kHz, indicate a lack of any causal relationships between VLF hiss, ELF hiss, and lower-frequency signals from spatial irregularities and Alfven waves.

Heppner, J. P.

The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Feind, Rand E.

Spatial region filtering in IRAF/PROS

In order to analyze x ray data, it is nearly always necessary to extract source and background events from a data set. Typically, this is done by defining geometric spatial regions of the data set to describe the source and background. For example, one might wish to extract source events from a circular or elliptical region centered at a particular pixel, and background events from a circular or elliptical annulus whose inner radius matches the source region. At the same time, it might be necessary to exclude one or more nearby sources from the source or background region in question. Thus, it might be necessary to define a pie-shaped region or even an entirely irregularly-shaped region to exclude. A spatial filtering scheme called REGIONS was implemented in IRAF/PROS to support these and other types of spatial region extraction. It allows users to create a spatial mask by specifying one or more ASCII geometric shape descriptors (box, circle, ellipse, pie, point, annulus, and polygon) as regions to be included or excluded in the mask. In addition, two or more shapes can be combined using Boolean algebra to create an infinite variety of sophisticated regions. Each geometric shape has a specific set of parameters that describe that shape. For example, a circle is described by a center and a radius, while a box is described by a center, length, width, and rotation angle. These quantities can be specified in units of pixels or, in cases where the target image contains world coordinate system information, they can be described in units such as RA and Dec. Users can create region mask files by feeding an ASCII region descriptor to the IRAF/PROS plcreate task. Temporary masks can also be created from ASCII region descriptors by individual applications that call the routines in the region creation library. This library implements a yacc-based region parser that compiles the ASCII descriptors into 'software CPU' instructions which are then executed to create the mask. The mask created from these region descriptors is a standard IRAF PLIO mask. It can be combined with other PLIO masks (e.g., exposure masks) to provide complete spatial filtering capabilities. The capabilities of the region filtering scheme are described. It also discusses the design philosophy guiding our work, as well as our plans for the future.

Mandel, Eric

Spatial variability of outgoing longwave radiation

Data from the Earth Radiation Budget Experiment scanning radiometer aboard the NOAA-9 operational meteorological satellite are used to investigate the spatial variability of Outgoing Longwave Radiation (OLR). Daily and monthly radiation maps at 2.5 deg latitude-longitude scale are used as a basis for the study. The regions of greatest variability are in the tropics and subtropics. Storm tracks such as the South Pacific convergence zone appear as regions of high OLR variability. Spatial spectra in longitude show two regimes of OLR. At large scales (wavenumbers less than 6), the spatial spectrum is flat. For wavenumbers greater than 10, the spectra decrease as wavenumber to the -3 power. The spatial spectrum of daily anomalies from the mean is a strong function of latitude and season, with interesting features. Correlations of daily anomalies from the monthly mean decrease exponentially in latitude but have a damped-wave structure in longitude. The spatial variability of the daily maps, as measured by degree variance, have 10 times the power at degree 24 than the monthly maps, but at scales between 1 and 10, the degree variance is practically the same for daily as for monthly.

Smith, G. Louis

A Spatial Classifier for Multispectral Data Using Contextual Information

Connectivity describes the spatial relationship among pixels. A spatial classifier which employs the sigma probability concept of the Gaussian distribution and a type of contextual information connectivity of the pixels, is studied in this paper. This spatial classifier attempts to replicate the kind of spatial synthesis done by the human analyst during visual interpretation or to capture the spatial relationships inherent in an aerial photograph. Several classification results of the Landsat TM data using this classifier with different window sizes for capturing the contextual information are illustrated and compared.

Hung, Chih-Cheng

Hurricane Directional Wave Spectrum Spatial Variation in the Open Ocean and at Landfall

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 1.5 km height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. At 8 Hz, the SRA sweeps a radar beam of 1 E half-power width (two-way) across the aircraft ground track over a swath equal to 0.8 of the aircraft height, simultaneously measuring the backscattered power at its 36 GHz (8.3 mm) operating frequency and the range to the sea surface at 64 positions. These slant ranges are multiplied by the cosine of the incidence angles to determine the vertical distances from the aircraft to the sea surface. Subtracting these distances from the aircraft height produces the sea surface elevation map. The sea surface topography is interpolated to a uniform grid, transformed by a two-dimensional FFT, and Doppler corrected. The open-ocean data were acquired on 24 August 1998 when hurricane Bonnie was east of the Bahamas and moving slowly to the north. Individual waves with heights up to 18 m were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction. At some positions there were three different wave fields of comparable energy crossing each other. The NOAA aircraft spent over five hours within 180 km of the hurricane Bonnie eye, and made five eye penetrations. A 3-minute animation of the directional wave spectrum spatial variation over this period will be shown as well as summary plots of the wave field spatial variation. On 26 August 1998, the NOAA aircraft flew at 2.2 km height when hurricane Bonnie was making landfall near Wilmington, NC, documenting the directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft ground track included both segments along the shoreline and Pamlico Sound as well as far offshore. An animation of the directional wave spectrum spatial variation at landfall will be presented and contrasted with the spatial variation when Bonnie was in the open ocean on 24 August 1998.

Walsh, E. J.

In-Flight Edge Response Measurements for High Spatial Resolution Remote Sensing Systems

In-flight measurement of spatial resolution were conducted as part of the ASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. Characterization included remote sensing systems with ground sample distance (GSD) of 1 meter or less, such as the panchromatic imager on-board the ICONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effect of both the image acquisition system (e.g., optics, electronics, motion, jitter, atmosphere) and image post-processing (e.g., resampling, modulation trasfer function (MTF) compensator). Spatial resolution was characterized by full width at half maximum (FWHM) of an edge response-derived line spread function. This was found to be a more robust measure of spatial resolution than the value of NTF at Nyquist frequency The edge responses were analysed using the tilted-edge technique that ovecomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as traps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. Numerous edge target images were analyzed for each of the tested sensors. The effect of such factors as acquisition geometry, temporal variability, MTF compensation, and GSD on spatial resolution were investigated.

Blonski, Slawomir

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

NASA Discipline Life Support Systems

Ecosystem Impacts of Woody Encroachment In Texas: A Spatial Analysis Using AVIRIS

Woody encroachment, the increase of woody plant density relative to herbaceous vegetation, has been documented in drylands of Texas as well as worldwide (Archer 1994, Harrington and Harman 1995, Moleele et al. 2002). Over-grazing, fire suppression and climate change are implicated in the shift from open grasslands to ecosystems now populated by trees and shrubs (Scholes and Archer 1997, Archer et al. 2001), such as Prosopis glandulosa var. glandulosa (honey mesquite) in north Texas (Teague et al. 1997, Ansley et al. 2001, Asner et al. 2003a). Several studies have examined changes in ecosystem properties accompanying woody vegetation encroachment in the Southwest U.S., with research focused on increases in plant and soil carbon (C) and nitrogen (N) stores (Hoffman and Jackson 2000, Asner et al. 2003a), isotopic shifts in these pools (Boutton 1999, Archer et al. 2001), and increases in N cycling rates (Rundel et al. 1982, Hibbard et al. 2001). However, little is known regarding the impact of woody encroachment on N trace gas emissions from dryland regions such as Texas. NOx is produced in the soil during the processes of nitrification and denitrification (Firestone and Davidson 1989). The total N efflux from soils is most directly influenced by the internal cycling of N, which at a regionalscale, is controlled by the inputs and availability of N from vegetation via litterfall and subsequent decomposition (Robertson et al. 1989). Although plot-scale studies are critical to understanding controls over N oxide emissions, regionalization of the measurements is impeded by spatial variation in the factors contributing most to N cycling processes: soil properties (affecting soil moisture regimes and N stocks) and vegetation cover (affecting litter inputs and N uptake). While broad patterns in ecosystem structure and vegetation composition co-vary with general patterns of trace gas emissions (Matson 1997), there is no easily measured index of N availability that can be applied for regional-scale studies of N oxide fluxes. Remote sensing is arguably the only approach available to develop a spatially-explicit understanding of ecosystem processes. More specifically, remotely detectable spatial patterns in the distal controls over soil N properties, such as vegetation cover, land use and soil type (Robertson et al. 1989), should be exploited for regional studies of N oxide emissions. The woody encroachment phenomenon provides an opportunity to test the strength of the relationship between N oxide emissions and those factors controlling the fluxes that can be remotely measured. If such linkages can be firmly established, and if the spatial pattern of distal controls is relevant, then the combination of field measurements and remote sensing offers to improve regional-scale N oxide estimates. The paper presents the utility of linking field based sampling of soil NOx emissions with very high resolution remote sensing estimates of woody vegetation cover from the NASA AVIRIS, Airborne Visible-Infrared Imaging Spectrometer (Green et al. 1998, Asner and Green 2001) and automated spectral mixture analysis (Asner and Lobell 2000, Asner and Heidebrecht 2002) that provide a means to spatially extrapolate soil NOx emissions to the regional scale.

Martin, Roberta E.

Effects of Artificial Gravity and Bed Rest on Spatial Orientation and Balance Control

While the vestibular system should be well-adapted to bed rest (a condition it experiences approximately 8/24 hrs each day), questions remain regarding the degree to which repeated exposures to the unusual gravito-inertial force environment of a short-radius centrifuge might affect central processing of vestibular information used in spatial orientation and balance control. Should these functions be impaired by intermittent AG, its feasibility as a counter-measure would be diminished. We, therefore, examined the effects of AG on spatial orientation and balance control in 15 male volunteers before and after 21 days of 6 HDT bed rest (BR). Eight of the subjects were treated with daily 1hr AG exposures (2.5g at the feet; 1.0g at the heart) aboard a short radius (3m) centrifuge, while the other seven served as controls (C). Spatial orientation was assessed by measures of ocular counter-rolling (OCR; rotation of the eye about the line of sight, an otolith-mediated reflex) and subjective visual vertical (SVV; perception of the spatial upright). Both OCR and SVV measurements were made with the subject upright, lying on their left sides, and lying on their right sides. OCR was measured from binocular eye orientation recordings made while the subjects fixated for 10s on a point target directly in front of the face at a distance of 1 m. SVV was assessed by asking subjects (in the dark) to adjust to upright (using a handheld controller) the orientation of a luminous bar randomly perturbed (15) to either side of the vertical meridian. Balance control performance was assessed using a computerized dynamic posturography (CDP) protocol similar to that currently required for all returning crew members. During each session, the subjects completed a combination of trials of sensory organization test (SOT) 2 (eyes closed, fixed platform) and SOT 5 (eyes closed, sway-referenced platform) with and without static and dynamic pitch plane head movements (plus or minus 20 deg., dynamic paced by an audible tone at 0.33Hz). OCR and CDP performance were unaffected by BR and BR+AG; post-BR measures were unchanged from baseline for both AG and C groups. Similarly, BR did not affect SVV in the C group. However, BR+AG disrupted one measure of spatial orientation: SVV error was significantly increased on R+0 and R+1 following BR in the AG group. These results suggest a transient untoward effect on central vestibular processing may accompany repeated exposure to intermittent AG, a potential side-effect that should be studied more closely in future studies.

Paloski, William H.

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Quattrochi, Dale A.

Using the Space Glove to Teach Spatial Thinking

The challenge of extending students' skills in spatial thinking to astronomical scales was the central focus of our K-8 curriculum development. When the project's lead teacher requested a curriculum that cumulatively built on each prior year's learning in a spiral fashion, I knew exactly what the school was asking for. Second and third graders began by noticing the cyclical patters that the sun, moon, and stars make in the sky. Fourth graders explored the phases of the moon by taking turns modeling and sketching them in their classroom and then comparing them to the real sky. Sixth !graders used real telescopes to observe a moving model of our solar system and walked a scale model of the planets' orbits. The curriculum is designed to expand students' capacity to visualize space in a hierarchical fashion that asks them to imagine themselves from a broader number of spatial perspectives through hands-on activities. The "situational awareness" Peter's story describes is a hallmark of high-performance engineering and innovation. Keeping in mind the potential outcomes of multiple paths of pursuit from multiple perspectives while keeping track of their relative merits and performance requirements is a demanding spatial task. What made it possible for Peter to transform the failure of his first glove into triumph was the mental space in which that failure provided exactly the information needed for a new breakthrough. In at least two cases, Peter could immediately "see" the full implications of what his hands were telling him. He tells the story of how putting his hands in a Phase VI astronaut glove instantly transformed his understanding of the glove challenge. Six months into his development, the failure of circumferentially wrapped cords to produce a sufficiently flexible glove again forced him to abandon his assumptions. His situational awareness was so clear and compelling it became a gut-level response. Peter's finely developed spatial skills enabled him to almost instinctively focus his full energy on a carefully constructed set of experiments. The finger's ability to sense pressure, force, and work gave him the immediate feedback required to solve this one central problem. Once properly understood, his failure quickly led to the magical "Aha!" moment of discovery; the rest is history. Just as children need opportunities to develop hands-on understanding, engineers need to explore new possibilities through incremental hands-on failure. High-performance innovation is all about learning to make maximum use of thinking spatially to direct this process. Peter Homer's glove also reminds us that efficient engineering decisions need to be made as close to the hardware as possible. Whether we're doing hands-on education or hands-on engineering, it is when we trust in our ability to "feel our way" through failure that we reach our highest potential.

Lord, Peter

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Estes, Maurice G., Jr.

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

Lawton, Robert M.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty

Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles

The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.

Kenny, Jeremy