Post-heading heat stress and yield impact in winter wheat of China.

PubMed

Liu, Bing; Liu, Leilei; Tian, Liying; Cao, Weixing; Zhu, Yan; Asseng, Senthold

2014-02-01

Wheat is sensitive to high temperatures, but the spatial and temporal variability of high temperature and its impact on yield are often not known. An analysis of historical climate and yield data was undertaken to characterize the spatial and temporal variability of heat stress between heading and maturity and its impact on wheat grain yield in China. Several heat stress indices were developed to quantify heat intensity, frequency, and duration between heading and maturity based on measured maximum temperature records of the last 50 years from 166 stations in the main wheat-growing region of China. Surprisingly, heat stress between heading and maturity was more severe in the generally cooler northern wheat-growing regions than the generally warmer southern regions of China, because of the delayed time of heading with low temperatures during the earlier growing season and the exposure of the post-heading phase into the warmer part of the year. Heat stress between heading and maturity has increased in the last decades in most of the main winter wheat production areas of China, but the rate was higher in the south than in the north. The correlation between measured grain yields and post-heading heat stress and average temperature were statistically significant in the entire wheat-producing region, and explained about 29% of the observed spatial and temporal yield variability. A heat stress index considering the duration and intensity of heat between heading and maturity was required to describe the correlation of heat stress and yield variability. Because heat stress is a major cause of yield loss and the number of heat events is projected to increase in the future, quantifying the future impact of heat stress on wheat production and developing appropriate adaptation and mitigation strategies are critical for developing food security policies in China and elsewhere. © 2013 John Wiley & Sons Ltd.

Yield of bedrock wells in the Nashoba terrane, central and eastern Massachusetts

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and hydrogeologic factors that were individually related to well yield, in ways that are consistent with conceptual understanding of their effects, but the models explained only 21 percent (regional model for the entire terrane) and 30 percent (quadrangle model) of the overall variance in yield. Moreover, most of the explained variance was due to well characteristics rather than hydrogeologic factors. Hydrogeologic factors such as topography and geology are likely important. However, the overall high variability in the well-yield data, which results from the high variability in aquifer hydraulic properties as well as from limitations of the dataset, would make it difficult to use hydrogeologic factors to predict well yield in the study area. Geostatistical analysis (variograms), on the other hand, indicated that, although highly variable, the well-yield data are spatially correlated. The spatial continuity appears greater in the northeast-southwest direction and less in the southeast-northwest direction, directions that are parallel and perpendicular, respectively, to the regional geologic structural trends. Geostatistical analysis (kriging), used to estimate yield values throughout the study area, identified regional-scale areas of higher and lower yield that may be related to regional structural features—in particular, to a northeast-southwest trending regional fault zone within the Nashoba terrane. It also would be difficult to use kriging to predict yield at specific locations, however, because of the spatial variability in yield, particularly at small scales. The regional-scale analyses in this study, both with hydrogeologic variables and geostatistics, provide a context for understanding the variability in well yield, rather a basis for precise predictions, and site-specific information would be needed to understand local conditions.

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

PubMed Central

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2012-01-01

This research examines whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In three experiments, participants learned four-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the maps from imagined perspectives that were either aligned or misaligned with the maps as represented in working memory. Results from Experiments 1 and 2 revealed a highly similar pattern of latencies and errors between visual and haptic conditions. These findings extend the well known alignment biases for visual map learning to haptic map learning, provide further evidence of haptic updating, and most importantly, show that learning from the two modalities yields very similar performance across all conditions. Experiment 3 found the same encoding biases and updating performance with blind individuals, demonstrating that functional equivalence cannot be due to visual recoding and is consistent with an amodal hypothesis of spatial images. PMID:21299331

What Is the Role of Land-Use Compositions and Spatial Configurations in Sediment Yield from Mountainous Watershed?

NASA Astrophysics Data System (ADS)

Shi, Z. H.

2014-12-01

There are strong ties between land use and sediment yield in watersheds. Many studies have used multivariate regression techniques to explore the response of sediment yield to land-use compositions and spatial configurations in watersheds. However, one issue with the use of conventional statistical methods to address relationships between land-use compositions and spatial configurations and sediment yield is multicollinearity. This paper examines the combined effects of land-use compositions and land-use spatial configurations of the watershed on the specific sediment yield of the Upper Du River watershed (8,973 km2) in China using the Soil and Water Assessment Tool (SWAT) and partial least-squares regression (PLSR). The land-use compositions and spatial configurations of the watershed were calculated at the sub-watershed scale. The sediment yields from sub-watershed were evaluated using SWAT model. The first-order factors were identified by calculating the variable importance for the projection (VIP). The results revealed that the land-use compositions exerted the largest effects on the specific sediment yield and explained 61.2% of the variation in the specific sediment yield. Land-use spatial configurations were also found to have a large effect on the specific sediment yield and explained 21.7% of the observed variation in the specific sediment yield. The following are the dominant first-order factors of the specific sediment yield at the sub-watershed scale: the areal percentages of agriculture and forest, patch density, value of the Shannon's diversity index, contagion. The VIP values suggested that the Shannon's diversity index and contagion are important factors for sediment delivery.

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T

2013-08-01

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

USDA-ARS?s Scientific Manuscript database

A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

Spatially averaged flow over a wavy boundary revisited

USGS Publications Warehouse

McLean, S.R.; Wolfe, S.R.; Nelson, J.M.

1999-01-01

Vertical profiles of streamwise velocity measured over bed forms are commonly used to deduce boundary shear stress for the purpose of estimating sediment transport. These profiles may be derived locally or from some sort of spatial average. Arguments for using the latter procedure are based on the assumption that spatial averaging of the momentum equation effectively removes local accelerations from the problem. Using analogies based on steady, uniform flows, it has been argued that the spatially averaged velocity profiles are approximately logarithmic and can be used to infer values of boundary shear stress. This technique of using logarithmic profiles is investigated using detailed laboratory measurements of flow structure and boundary shear stress over fixed two-dimensional bed forms. Spatial averages over the length of the bed form of mean velocity measurements at constant distances from the mean bed elevation yield vertical profiles that are highly logarithmic even though the effect of the bottom topography is observed throughout the water column. However, logarithmic fits of these averaged profiles do not yield accurate estimates of the measured total boundary shear stress. Copyright 1999 by the American Geophysical Union.

Matching spatial property rights fisheries with scales of fish dispersal.

PubMed

White, Crow; Costello, Christopher

2011-03-01

Regulation of fisheries using spatial property rights can alleviate competition for high-value patches that hinders economic efficiency in quota-based, rights-based, and open-access management programs. However, efficiency gains erode when delineation of spatial rights constitutes incomplete ownership of the resource, thereby degrading its local value and promoting overexploitation. Incomplete ownership may be particularly prevalent in the spatial management of mobile fishery species. We developed a game-theoretic bioeconomic model of spatial property rights representing territorial user rights fisheries (TURF) management of nearshore marine fish and invertebrate species with mobile adult and larval life history stages. Strategic responses by fisheries in neighboring management units result in overexploitation of the stock and reduced yields for each fishery compared with those attainable without resource mobility or with coordination or sole control in fishing effort. High dispersal potential of the larval stage, a common trait among nearshore fishery species, coupled with scaling of management units to only capture adult mobility, a common characteristic of many nearshore TURF programs, in particular substantially reduced stock levels and yields. In a case study of hypothetical TURF programs of nearshore fish and invertebrate species, management units needed to be tens of kilometers in alongshore length to minimize larval export and generate reasonable returns to fisheries. Cooperation and quota regulations represent solutions to the problem that need to be quantified in cost and integrated into the determination of the acceptability of spatial property rights management of fisheries.

The sensitivity of ecosystem service models to choices of input data and spatial resolution

USGS Publications Warehouse

Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

2018-01-01

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

Soil biota and agriculture production in conventional and organic farming

NASA Astrophysics Data System (ADS)

Schrama, Maarten; de Haan, Joj; Carvalho, Sabrina; Kroonen, Mark; Verstegen, Harry; Van der Putten, Wim

2015-04-01

Sustainable food production for a growing world population requires a healthy soil that can buffer environmental extremes and minimize its losses. There are currently two views on how to achieve this: by intensifying conventional agriculture or by developing organically based agriculture. It has been established that yields of conventional agriculture can be 20% higher than of organic agriculture. However, high yields of intensified conventional agriculture trade off with loss of soil biodiversity, leaching of nutrients, and other unwanted ecosystem dis-services. One of the key explanations for the loss of nutrients and GHG from intensive agriculture is that it results in high dynamics of nutrient losses, and policy has aimed at reducing temporal variation. However, little is known about how different agricultural practices affect spatial variation, and it is unknown how soil fauna acts this. In this study we compare the spatial and temporal variation of physical, chemical and biological parameters in a long term (13-year) field experiment with two conventional farming systems (low and medium organic matter input) and one organic farming system (high organic matter input) and we evaluate the impact on ecosystem services that these farming systems provide. Soil chemical (N availability, N mineralization, pH) and soil biological parameters (nematode abundance, bacterial and fungal biomass) show considerably higher spatial variation under conventional farming than under organic farming. Higher variation in soil chemical and biological parameters coincides with the presence of 'leaky' spots (high nitrate leaching) in conventional farming systems, which shift unpredictably over the course of one season. Although variation in soil physical factors (soil organic matter, soil aggregation, soil moisture) was similar between treatments, but averages were higher under organic farming, indicating more buffered conditions for nutrient cycling. All these changes coincide with pronounced shifts in soil fauna composition (nematodes, earthworms) and an increase in earthworm activity. Hence, more buffered conditions and shifts in soil fauna composition under organic farming may underlie the observed reduction in spatial variation of soil chemical and biological parameters, which in turn correlates positively with a long-term increase in yield. Our study highlights the need for both policymakers and farmers alike to support spatial stability-increasing farming.

Spatial and Time Coincidence Detection of the Decay Chain of Short-Lived Radioactive Nuclei

DOE Office of Scientific and Technical Information (OSTI.GOV)

Granja, Carlos; Jakubek, Jan; Platkevic, Michal

The quantum counting position sensitive pixel detector Timepix with per-pixel energy and time resolution enables to detect radioactive ions and register the consecutive decay chain by simultaneous position-and time-correlation. This spatial and timing coincidence technique in the same sensor is demonstrated by the registration of the decay chain {sup 8}He{yields}{sup {beta} 8}Li and {sup 8}Li{yields}{sup {beta}-} {sup 8}Be{yields}{alpha}+{alpha} and by the measurement of the {beta} decay half-lives. Radioactive ions, selectively obtained from the Lohengrin fission fragment spectrometer installed at the High Flux Reactor of the ILL Grenoble, are delivered to the Timepix silicon sensor where decays of the implanted ionsmore » and daughter nuclei are registered and visualized. We measure decay lifetimes in the range {>=}{mu}s with precision limited just by counting statistics.« less

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Crop yield response to climate change varies with crop spatial distribution pattern

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Crop yield response to climate change varies with crop spatial distribution pattern

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Huang, Maoyi

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Highly charged ion based time of flight emission microscope

DOEpatents

Barnes, Alan V.; Schenkel, Thomas; Hamza, Alex V.; Schneider, Dieter H.; Doyle, Barney

2001-01-01

A highly charged ion based time-of-flight emission microscope has been designed, which improves the surface sensitivity of static SIMS measurements because of the higher ionization probability of highly charged ions. Slow, highly charged ions are produced in an electron beam ion trap and are directed to the sample surface. The sputtered secondary ions and electrons pass through a specially designed objective lens to a microchannel plate detector. This new instrument permits high surface sensitivity (10.sup.10 atoms/cm.sup.2), high spatial resolution (100 nm), and chemical structural information due to the high molecular ion yields. The high secondary ion yield permits coincidence counting, which can be used to enhance determination of chemical and topological structure and to correlate specific molecular species.

Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

NASA Astrophysics Data System (ADS)

Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

2013-04-01

The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the assimilation of the remotely sensed GAI time series. The calibration process led to accurate spatial estimates of GAI, ETR as well as of biomass and yield over the study area (24 km x 24 km window). The results highlight the interest of using a combined approach (crop model coupled with high spatial and temporal resolution remote sensing data) for the estimation of agronomical variables. At local scale, the model reproduced correctly the biomass production and ETR for summer crops (with relative RMSE of 29% and 35%, respectively). At regional scale, estimated yield and water requirement for irrigation were compared to regional statistics of yield and irrigation inventories provided by the local water agency. Results showed good agreements for inter-annual dynamics of yield estimates. Differences between water requirement for irrigation and actual supply were lower than 10% and inter-annual variability was well represented as well. The work, initially focused on summer crops, is being adapted to winter crops.

Integrated model for predicting rice yield with climate change

NASA Astrophysics Data System (ADS)

Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

2018-04-01

Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production

NASA Astrophysics Data System (ADS)

Lipiec, Jerzy; Usowicz, Boguslaw

2017-04-01

Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).

Influence of management and environment on Australian wheat: information for sustainable intensification and closing yield gaps

NASA Astrophysics Data System (ADS)

Bryan, B. A.; King, D.; Zhao, G.

2014-04-01

In the future, agriculture will need to produce more, from less land, more sustainably. But currently, in many places, actual crop yields are below those attainable. We quantified the ability for agricultural management to increase wheat yields across 179 Mha of potentially arable land in Australia. Using the Agricultural Production Systems Simulator (APSIM), we simulated the impact on wheat yield of 225 fertilization and residue management scenarios at a high spatial, temporal, and agronomic resolution from 1900 to 2010. The influence of management and environmental variables on wheat yield was then assessed using Spearman’s non-parametric correlation test with bootstrapping. While residue management showed little correlation, fertilization strongly increased wheat yield up to around 100 kg N ha-1 yr-1. However, this effect was highly dependent on the key environment variables of rainfall, temperature, and soil water holding capacity. The influence of fertilization on yield was stronger in cooler, wetter climates, and in soils with greater water holding capacity. We conclude that the effectiveness of management intensification to increase wheat yield is highly dependent upon local climate and soil conditions. We provide context-specific information on the yield benefits of fertilization to support adaptive agronomic decision-making and contribute to the closure of yield gaps. We also suggest that future assessments consider the economic and environmental sustainability of management intensification for closing yield gaps.

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Microplume model of spatial-yield spectra. [applying to electron gas degradation in molecular nitrogen gas

NASA Technical Reports Server (NTRS)

Green, A. E. S.; Singhal, R. P.

1979-01-01

An analytic representation for the spatial (radial and longitudinal) yield spectra is developed in terms of a model containing three simple 'microplumes'. The model is applied to electron energy degradation in molecular nitrogen gas for 0.1 to 5 keV incident electrons. From the nature of the cross section input to this model it is expected that the scaled spatial yield spectra for other gases will be quite similar. The model indicates that each excitation, ionization, etc. plume should have its individual spatial and energy dependence. Extensions and aeronomical and radiological applications of the model are discussed.

Pd-Metalated Conjugated Nanoporous Polycarbazoles for Additive-Free Cyanation of Aryl Halides: Boosting Catalytic Efficiency through Spatial Modulation

DOE PAGES

Ding, Shunmin; Tian, Chengcheng; Zhu, Xiang; ...

2017-03-23

Transition-metal-catalyzed cyanation of aryl halides is a common route to benzonitriles, which are integral to many industrial procedures. However, traditional homogeneous catalysts for such processes are expensive and suffer poor recyclability, so a heterogeneous analogue is highly desired. A novel spatial modulation approach has been developed in this paper to fabricate a heterogeneous Pd-metalated nanoporous polymer, which catalyzes the cyanation of aryl halides without need for ligands. Finally, the catalyst displays high activity in the synthesis of benzonitriles, including high product yields, excellent stability and recycling, and broad functional-group tolerance.

Tracking historical increases in nitrogen-driven crop production possibilities

NASA Astrophysics Data System (ADS)

Mueller, N. D.; Lassaletta, L.; Billen, G.; Garnier, J.; Gerber, J. S.

2015-12-01

The environmental costs of nitrogen use have prompted a focus on improving the efficiency of nitrogen use in the global food system, the primary source of nitrogen pollution. Typical approaches to improving agricultural nitrogen use efficiency include more targeted field-level use (timing, placement, and rate) and modification of the crop mix. However, global efficiency gains can also be achieved by improving the spatial allocation of nitrogen between regions or countries, due to consistent diminishing returns at high nitrogen use. This concept is examined by constructing a tradeoff frontier (or production possibilities frontier) describing global crop protein yield as a function of applied nitrogen from all sources, given optimal spatial allocation. Yearly variation in country-level input-output nitrogen budgets are utilized to parameterize country-specific hyperbolic yield-response models. Response functions are further characterized for three ~15-year eras beginning in 1961, and series of calculations uses these curves to simulate optimal spatial allocation in each era and determine the frontier. The analyses reveal that excess nitrogen (in recent years) could be reduced by ~40% given optimal spatial allocation. Over time, we find that gains in yield potential and in-country nitrogen use efficiency have led to increases in the global nitrogen production possibilities frontier. However, this promising shift has been accompanied by an actual spatial distribution of nitrogen use that has become less optimal, in an absolute sense, relative to the frontier. We conclude that examination of global production possibilities is a promising approach to understanding production constraints and efficiency opportunities in the global food system.

Gas scintillation glass GEM detector for high-resolution X-ray imaging and CT

NASA Astrophysics Data System (ADS)

Fujiwara, T.; Mitsuya, Y.; Fushie, T.; Murata, K.; Kawamura, A.; Koishikawa, A.; Toyokawa, H.; Takahashi, H.

2017-04-01

A high-spatial-resolution X-ray-imaging gaseous detector has been developed with a single high-gas-gain glass gas electron multiplier (G-GEM), scintillation gas, and optical camera. High-resolution X-ray imaging of soft elements is performed with a spatial resolution of 281 μm rms and an effective area of 100×100 mm. In addition, high-resolution X-ray 3D computed tomography (CT) is successfully demonstrated with the gaseous detector. It shows high sensitivity to low-energy X-rays, which results in high-contrast radiographs of objects containing elements with low atomic numbers. In addition, the high yield of scintillation light enables fast X-ray imaging, which is an advantage for constructing CT images with low-energy X-rays.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Influence of hydration and annealing on structure, PSL yield and spatial resolution of pressed powder imaging plates of the X-ray storage phosphor CsBr:Eu2+

NASA Astrophysics Data System (ADS)

Kersting, E.; von Seggern, H.

2017-08-01

A new production route for europium doped cesium bromide (CsBr:Eu2+) imaging plates has been developed, synthesizing CsBr:Eu2+ powder from a precipitation reaction of aqueous CsBr solution with ethanol. This new route allows the control of features like homogeneous grain size and grain shape of the obtained powder. After drying and subsequent compacting the powder, disk-like samples were fabricated, and their resulting photostimulated luminescence (PSL) properties like yield and spatial resolution were determined. It will be shown that hydration of such disks causes the CsBr:Eu2+ powder to recrystallize starting from the humidity exposed surfaces to the sample interior up to a completely polycrystalline sample resulting in a decreasing PSL yield and an increasing resolution. Subsequent annealing leads to grain refinement combined with a large PSL yield increment and a minor effect on the spatial resolution. By first annealing the "as made" disk, one observes a strong increment of the PSL yield and almost no effect on the spatial resolution. During subsequent hydration, the recrystallization is hindered by minor structural changes of the grains. The related PSL yield drops slightly with increasing hydration time, and the spatial resolution drops considerably. The obtained PSL properties with respect to structure will be discussed with a simple model.

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

2017-10-01

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

Atmospheric water mapping with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Mountain Pass, California

NASA Technical Reports Server (NTRS)

Conel, James E.; Green, Robert O.; Carrere, Veronique; Margolis, Jack S.; Alley, Ronald E.; Vane, Gregg; Bruegge, Carol J.; Gary, Bruce L.

1988-01-01

Observations are given of the spatial variation of atmospheric precipitable water using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over a desert area in eastern California, derived using a band ratio method and the 940 nm atmospheric water band and 870 nm continuum radiances. The ratios yield total path water from curves of growth supplied by the LOWTRAN 7 atmospheric model. An independent validation of the AVIRIS-derived column abundance at a point is supplied by a spectral hygrometer calibrated with respect to radiosonde observations. Water values conform to topography and fall off with surface elevation. The edge of the water vapor boundary layer defined by topography is thought to have been recovered. The ratio method yields column abundance estimates of good precision and high spatial resolution.

Trading carbon for food: global comparison of carbon stocks vs. crop yields on agricultural land.

PubMed

West, Paul C; Gibbs, Holly K; Monfreda, Chad; Wagner, John; Barford, Carol C; Carpenter, Stephen R; Foley, Jonathan A

2010-11-16

Expanding croplands to meet the needs of a growing population, changing diets, and biofuel production comes at the cost of reduced carbon stocks in natural vegetation and soils. Here, we present a spatially explicit global analysis of tradeoffs between carbon stocks and current crop yields. The difference among regions is striking. For example, for each unit of land cleared, the tropics lose nearly two times as much carbon (∼120 tons·ha(-1) vs. ∼63 tons·ha(-1)) and produce less than one-half the annual crop yield compared with temperate regions (1.71 tons·ha(-1)·y(-1) vs. 3.84 tons·ha(-1)·y(-1)). Therefore, newly cleared land in the tropics releases nearly 3 tons of carbon for every 1 ton of annual crop yield compared with a similar area cleared in the temperate zone. By factoring crop yield into the analysis, we specify the tradeoff between carbon stocks and crops for all areas where crops are currently grown and thereby, substantially enhance the spatial resolution relative to previous regional estimates. Particularly in the tropics, emphasis should be placed on increasing yields on existing croplands rather than clearing new lands. Our high-resolution approach can be used to determine the net effect of local land use decisions.

Farmers Extension Program Effects on Yield Gap in North China Plain

NASA Astrophysics Data System (ADS)

Sum, N.; Zhao, Y.

2015-12-01

Improving crop yield of the lowest yielding smallholder farmers in developing countries is essential to both food security of the country and the farmers' livelihood. Although wheat and maize production in most developed countries have reached 80% or greater of yield potential determined by simulated models, yield gap remains high in the developing world. One of these cases is the yield gap of maize in the North China Plain (NCP), where the average farmer's yield is 41% of his or her potential yield. This large yield gap indicates opportunity to raise yields substantially by improving agronomy, especially in nutrition management, irrigation facility, and mechanization issues such as technical services. Farmers' agronomic knowledge is essential to yield performance. In order to propagate such knowledge to farmers, agricultural extension programs, especially in-the-field guidance with training programs at targeted demonstration fields, have become prevalent in China. Although traditional analyses of the effects of the extension program are done through surveys, they are limited to only one to two years and to a small area. However, the spatial analysis tool Google Earth Engine (GEE) and its extensive satellite imagery data allow for unprecedented spatial temporal analysis of yield variation. We used GEE to analyze maize yield in Quzhou county in the North China Plain from 2007 to 2013. We based our analysis on the distance from a demonstration farm plot, the source of the farmers' agronomic knowledge. Our hypothesis was that the farther the farmers' fields were from the demonstration plot, the less access they would have to the knowledge, and the less increase in yield over time. Testing this hypothesis using GEE helps us determine the effectiveness of the demonstration plot in disseminating optimal agronomic practices in addition to evaluating yield performance of the demonstration field itself. Furthermore, we can easily extend this methodology to analyze the whole NCP and any other parts of the world for any type of crop.

Subsurface Chloride Transport in Shallow Groundwater

USDA-ARS?s Scientific Manuscript database

High soil spatial heterogeneity was observed at the USDA-ARS Beltsville OPE3 field site using geophysical surveys (ground-penetrating radar) and soil textural analysis. This was confirmed with data on crop yields and pesticide concentrations in wells. To assess effects of soil heterogeneity on soil ...

Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.

PubMed

Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen

2013-12-01

Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.

Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

NASA Astrophysics Data System (ADS)

Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.

2017-08-01

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield due to flood events during the growing season. Using a 2011 Missouri River flood event as a case study, field-level flood impact map on corn yield throughout the flooded regions was produced and an overall agreement of over 82.2% was achieved when compared with the reference impact map. The future research direction of this dissertation research would be to examine other major crops outside the Corn Belt region of the U.S.

Encoding spatial images: A fuzzy set theory approach

NASA Technical Reports Server (NTRS)

Sztandera, Leszek M.

1992-01-01

As the use of fuzzy set theory continues to grow, there is an increased need for methodologies and formalisms to manipulate obtained fuzzy subsets. Concepts involving relative position of fuzzy patterns are acknowledged as being of high importance in many areas. In this paper, we present an approach based on the concept of dominance in fuzzy set theory for modelling relative positions among fuzzy subsets of a plane. In particular, we define the following spatial relations: to the left (right), in front of, behind, above, below, near, far from, and touching. This concept has been implemented to define spatial relationships among fuzzy subsets of the image plane. Spatial relationships based on fuzzy set theory, coupled with a fuzzy segmentation, should therefore yield realistic results in scene understanding.

LPE grown LSO:Tb scintillator films for high-resolution X-ray imaging applications at synchrotron light sources

NASA Astrophysics Data System (ADS)

Cecilia, A.; Rack, A.; Douissard, P.-A.; Martin, T.; Dos Santos Rolo, T.; Vagovič, P.; Hamann, E.; van de Kamp, T.; Riedel, A.; Fiederle, M.; Baumbach, T.

2011-08-01

Within the project ScinTAX of the 6th framework program (FP6) of the European Commission (SCINTAX—STRP 033 427) we have developed a new thin single crystal scintillator for high-resolution X-ray imaging. The scintillator is based on a Tb-doped Lu2SiO5 (LSO) film epitaxially grown on an adapted substrate. The high density, effective atomic number and light yield of the scintillating LSO significantly improves the efficiency of the X-ray imaging detectors currently used in synchrotron micro-imaging applications. In this work we present the characterization of the scintillating LSO films in terms of their spatial resolution performance and we provide two examples of high spatial and high temporal resolution applications.

Satellite-based studies of maize yield spatial variations and their causes in China

NASA Astrophysics Data System (ADS)

Zhao, Y.

2013-12-01

Maize production in China has been expanding significantly in the past two decades, but yield has become relatively stagnant in the past few years, and needs to be improved to meet increasing demand. Multiple studies found that the gap between potential and actual yield of maize is as large as 40% to 60% of yield potential. Although a few major causes of yield gap have been qualitatively identified with surveys, there has not been spatial analysis aimed at quantifying relative importance of specific biophysical and socio-economic causes, information which would be useful for targeting interventions. This study analyzes the causes of yield variation at field and village level in Quzhou county of North China Plain (NCP). We combine remote sensing and crop modeling to estimate yields in 2009-2012, and identify fields that are consistently high or low yielding. To establish the relationship between yield and potential factors, we gather data on those factors through a household survey. We select targeted survey fields such that not only both extremes of yield distribution but also all soil texture categories in the county is covered. Our survey assesses management and biophysical factors as well as social factors such as farmers' access to agronomic knowledge, which is approximated by distance to the closest demonstration plot or 'Science and technology backyard'. Our survey covers 10 townships, 53 villages and 180 fields. Three to ten farmers are surveyed depending on the amount of variation present among sub pixels of each field. According to survey results, we extract the amount of variation within as well as between villages and or soil type. The higher within village or within field variation, the higher importance of management factors. Factors such as soil type and access to knowledge are more represented by between village variation. Through regression and analysis of variance, we gain more quantitative and thorough understanding of causes to yield variation at village scale, which further explains the gap between average and highest achieved yield.

Spatial arrangement, population density and legume species effect of yield of forage sorghum-legume intercropping

USDA-ARS?s Scientific Manuscript database

Sorghum (Sorghum bicolor) is a stress tolerant forage crop grown extensively in the Southern High Plains. However, sorghum forage quality is lower than that of corn. Intercropping sorghum with legumes can improve quality and productivity of forage. However, tall statured sorghum limits the resources...

Switchgrass Compositional Variations Arising from Spatial Distribution and Legume Intercropping

USDA-ARS?s Scientific Manuscript database

Switchgrass (Panicum virgatum) is a high–yielding, second-generation feedstock that can be grown on marginal land with minimal inputs. Due to the high genetic diversity within and among cultivars of this species, there may be a great amount of genotype x environment-induced differences among seconda...

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

NASA Technical Reports Server (NTRS)

Ponomarev, Artem; Cucinotta, F.

2011-01-01

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Spatial frequency filtered images reveal differences between masked and unmasked processing of emotional information.

PubMed

Rohr, Michaela; Wentura, Dirk

2014-10-01

High and low spatial frequency information has been shown to contribute differently to the processing of emotional information. In three priming studies using spatial frequency filtered emotional face primes, emotional face targets, and an emotion categorization task, we investigated this issue further. Differences in the pattern of results between short and masked, and short and long unmasked presentation conditions emerged. Given long and unmasked prime presentation, high and low frequency primes triggered emotion-specific priming effects. Given brief and masked prime presentation in Experiment 2, we found a dissociation: High frequency primes caused a valence priming effect, whereas low frequency primes yielded a differentiation between low and high arousing information within the negative domain. Brief and unmasked prime presentation in Experiment 3 revealed that subliminal processing of primes was responsible for the pattern observed in Experiment 2. The implications of these findings for theories of early emotional information processing are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

On the Importance of Spatial Resolution for Flap Side Edge Noise Prediction

NASA Technical Reports Server (NTRS)

Mineck, Raymond E.; Khorrami, Mehdi R.

2017-01-01

A spatial resolution study of flap tip flow and the effects on the farfield noise signature for an 18%-scale, semispan Gulfstream aircraft model are presented. The NASA FUN3D unstructured, compressible Navier-Stokes solver was used to perform the highly resolved, time-dependent, detached eddy simulations of the flow field associated with the flap for this high-fidelity aircraft model. Following our previous work on the same model, the latest computations were undertaken to determine the causes of deficiencies observed in our earlier predictions of the steady and unsteady surface pressures and off-surface flow field at the flap tip regions, in particular the outboard tip area, where the presence of a cavity at the side-edge produces very complex flow features and interactions. The present results show gradual improvement in steady loading at the outboard flap edge region with increasing spatial resolution, yielding more accurate fluctuating surface pressures, off-surface flow field, and farfield noise with improved high-frequency content when compared with wind tunnel measurements. The spatial resolution trends observed in the present study demonstrate that the deficiencies reported in our previous computations are mostly caused by inadequate spatial resolution and are not related to the turbulence model.

High resolution crop growth simulation for identification of potential adaptation strategies under climate change

NASA Astrophysics Data System (ADS)

Kim, K. S.; Yoo, B. H.

2016-12-01

Impact assessment of climate change on crop production would facilitate planning of adaptation strategies. Because socio-environmental conditions would differ by local areas, it would be advantageous to assess potential adaptation measures at a specific area. The objectives of this study was to develop a crop growth simulation system at a very high spatial resolution, e.g., 30 m, and to assess different adaptation options including shift of planting date and use of different cultivars. The Decision Support System for Agrotechnology Transfer (DSSAT) model was used to predict yields of soybean and maize in Korea. Gridded data for climate and soil were used to prepare input data for the DSSAT model. Weather input data were prepared at the resolution of 30 m using bilinear interpolation from gridded climate scenario data. Those climate data were obtained from Korean Meteorology Administration. Spatial resolution of temperature and precipitation was 1 km whereas that of solar radiation was 12.5 km. Soil series data at the 30 m resolution were obtained from the soil database operated by Rural Development Administration, Korea. The SOL file, which is a soil input file for the DSSAT model was prepared using physical and chemical properties of a given soil series, which were available from the soil database. Crop yields were predicted by potential adaptation options based on planting date and cultivar. For example, 10 planting dates and three cultivars were used to identify ideal management options for climate change adaptation. In prediction of maize yield, combination of 20 planting dates and two cultivars was used as management options. Predicted crop yields differed by site even within a relatively small region. For example, the maximum of average yields for 2001-2010 seasons differed by sites In a county of which areas is 520 km2 (Fig. 1). There was also spatial variation in the ideal management option in the region (Fig. 2). These results suggested that local assessment of climate change impact on crop production would be useful for planning adaptation options.

Assessing and modelling ecohydrologic processes at the agricultural field scale

NASA Astrophysics Data System (ADS)

Basso, Bruno

2015-04-01

One of the primary goals of agricultural management is to increase the amount of crop produced per unit of fertilizer and water used. World record corn yields demonstrated that water use efficiency can increase fourfold with improved agronomic management and cultivars able to tolerate high densities. Planting crops with higher plant density can lead to significant yield increases, and increase plant transpiration vs. soil water evaporation. Precision agriculture technologies have been adopted for the last twenty years but seldom have the data collected been converted to information that led farmers to different agronomic management. These methods are intuitively appealing, but yield maps and other spatial layers of data need to be properly analyzed and interpreted to truly become valuable. Current agro-mechanic and geospatial technologies allow us to implement a spatially variable plan for agronomic inputs including seeding rate, cultivars, pesticides, herbicides, fertilizers, and water. Crop models are valuable tools to evaluate the impact of management strategies (e.g., cover crops, tile drains, and genetically-improved cultivars) on yield, soil carbon sequestration, leaching and greenhouse gas emissions. They can help farmers identify adaptation strategies to current and future climate conditions. In this paper I illustrate the key role that precision agriculture technologies (yield mapping technologies, within season soil and crop sensing), crop modeling and weather can play in dealing with the impact of climate variability on soil ecohydrologic processes. Case studies are presented to illustrate this concept.

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Electrical resistivity tomography to delineate greenhouse soil variability

NASA Astrophysics Data System (ADS)

Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.

2013-03-01

Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development

PubMed Central

Shafian, Sanaz; Schnell, Ronnie; Bagavathiannan, Muthukumar; Valasek, John; Shi, Yeyin; Olsenholler, Jeff

2018-01-01

Unmanned Aerial Vehicles and Systems (UAV or UAS) have become increasingly popular in recent years for agricultural research applications. UAS are capable of acquiring images with high spatial and temporal resolutions that are ideal for applications in agriculture. The objective of this study was to evaluate the performance of a UAS-based remote sensing system for quantification of crop growth parameters of sorghum (Sorghum bicolor L.) including leaf area index (LAI), fractional vegetation cover (fc) and yield. The study was conducted at the Texas A&M Research Farm near College Station, Texas, United States. A fixed-wing UAS equipped with a multispectral sensor was used to collect image data during the 2016 growing season (April–October). Flight missions were successfully carried out at 50 days after planting (DAP; 25 May), 66 DAP (10 June) and 74 DAP (18 June). These flight missions provided image data covering the middle growth period of sorghum with a spatial resolution of approximately 6.5 cm. Field measurements of LAI and fc were also collected. Four vegetation indices were calculated using the UAS images. Among those indices, the normalized difference vegetation index (NDVI) showed the highest correlation with LAI, fc and yield with R2 values of 0.91, 0.89 and 0.58 respectively. Empirical relationships between NDVI and LAI and between NDVI and fc were validated and proved to be accurate for estimating LAI and fc from UAS-derived NDVI values. NDVI determined from UAS imagery acquired during the flowering stage (74 DAP) was found to be the most highly correlated with final grain yield. The observed high correlations between UAS-derived NDVI and the crop growth parameters (fc, LAI and grain yield) suggests the applicability of UAS for within-season data collection of agricultural crops such as sorghum. PMID:29715311

Linking Watershed Nitrogen Sources with Nitrogen Dynamics in Rivers of Western Oregon, USA

NASA Astrophysics Data System (ADS)

Sobota, D. J.; Compton, J.; Goodwin, K. E.

2012-12-01

We constructed contemporary nitrogen (N) budgets for 25 river basins in the Willamette River Basin (WRB) of western Oregon, USA, to improve the understanding of how recent trends in human-driven N loading have influenced riverine N dynamics in the region. Nearly 20% of WRB stream length is currently in fair or poor condition because of high N concentrations. Additionally, nitrate contamination of drinking water affects at least 8,000 people in the WRB. We hypothesized that 1) the majority of N inputs in the WRB would originate from agricultural activities in lowland portions of watersheds, 2) annual riverine N yield (kg/ha/yr) would correspond to annual per area watershed N inputs, and 3) riverine N yields would be seasonal and highest during winter due to the region's Mediterranean climate. We calculated average annual N inputs for each study basin by summing newly available datasets describing spatially explicit N inputs of synthetic fertilizer, atmospheric deposition, crop biological N2 fixation, biological N2 fixation by red alder (Alnus rubra Bong.), livestock manure, and point sources for the period 1996 - 2007. Annual and seasonal riverine N exports were estimated with the USGS model LOADEST calibrated to N concentration data collected during the study period. We estimated that two-thirds of total N input to the WRB study basins in the 2000s came from synthetic fertilizer application. Nearly all fertilizer application occurred on the lowlands near watershed mouths. We found a wide range of riverine N yields from the study basins, ranging from one to 70 kg N/ha/yr. Across the study basins, N export was more strongly correlated to fertilizer application rates than to percent of agricultural area in the watershed. Low watershed N yields reflected a high proportion of watershed area in the forested Cascade Mountain Range, which received low N inputs mainly from atmospheric deposition. N yields from study basins were strongly seasonal, with at least 50%, and often 75%, of annual N yield occurring in fall and winter months. Our results suggest that that spatially explicit data on specific crop types and crop practices are valuable for explaining spatial and temporal variation of nutrient concentrations in WRB rivers. This emphasizes the need for careful tracking of non-point N inputs to inform water quality monitoring and management.

Environmental factors controlling spatial variation in sediment yield in a central Andean mountain area

NASA Astrophysics Data System (ADS)

Molina, Armando; Govers, Gerard; Poesen, Jean; Van Hemelryck, Hendrik; De Bièvre, Bert; Vanacker, Veerle

2008-06-01

A large spatial variability in sediment yield was observed from small streams in the Ecuadorian Andes. The objective of this study was to analyze the environmental factors controlling these variations in sediment yield in the Paute basin, Ecuador. Sediment yield data were calculated based on sediment volumes accumulated behind checkdams for 37 small catchments. Mean annual specific sediment yield (SSY) shows a large spatial variability and ranges between 26 and 15,100 Mg km - 2 year - 1 . Mean vegetation cover (C, fraction) in the catchment, i.e. the plant cover at or near the surface, exerts a first order control on sediment yield. The fractional vegetation cover alone explains 57% of the observed variance in ln(SSY). The negative exponential relation (SSY = a × e- b C) which was found between vegetation cover and sediment yield at the catchment scale (10 3-10 9 m 2), is very similar to the equations derived from splash, interrill and rill erosion experiments at the plot scale (1-10 3 m 2). This affirms the general character of an exponential decrease of sediment yield with increasing vegetation cover at a wide range of spatial scales, provided the distribution of cover can be considered to be essentially random. Lithology also significantly affects the sediment yield, and explains an additional 23% of the observed variance in ln(SSY). Based on these two catchment parameters, a multiple regression model was built. This empirical regression model already explains more than 75% of the total variance in the mean annual sediment yield. These results highlight the large potential of revegetation programs for controlling sediment yield. They show that a slight increase in the overall fractional vegetation cover of degraded land is likely to have a large effect on sediment production and delivery. Moreover, they point to the importance of detailed surface vegetation data for predicting and modeling sediment production rates.

Projecting crop yield in northern high latitude area.

PubMed

Matsumura, Kanichiro

2014-01-01

Changing climatic conditions on seasonal and longer time scales influence agricultural production. Improvement of soil and fertilizer is a strong factor in agricultural production, but agricultural production is influenced by climate conditions even in highly developed countries. It is valuable if fewer predictors make it possible to conduct future projections. Monthly temperature and precipitation, wintertime 500hPa geopotential height, and the previous year's yield are used as predictors to forecast spring wheat yield in advance. Canadian small agricultural divisions (SAD) are used for analysis. Each SAD is composed of a collection of Canadian Agricultural Regions (CAR) of similar weather and growing conditions. Spring wheat yields in each CAR are forecast from the following variables: (a) the previous year's yield, (b) earlier stages of the growing season's climate conditions and, (c) the previous year's wintertime northern hemisphere 500hPa geopotential height field. Arctic outflow events in the Okanagan Valley in Canada are associated with episodes of extremely low temperatures during wintertime. Principal component analysis (PCA) is applied for wintertime northern hemisphere 500hPa geopotential height anomalies. The spatial PCA mode1 is defined as Arctic Oscillation and it influences prevailing westerlies. The prevailing westerlies meanders and influences climatic conditions. The spatial similarity between wintertime top 5 Arctic outflow event year's composites of 500hPa geopotential height anomalies and mode 3's spatial pattern is found. Mode 3's spatial pattern looks like the Pacific/North American (PNA) pattern which describes the variation of atmospheric circulation pattern over the Pacific Ocean and North America. Climate conditions from April to June, May to July, mode 3's time coefficients, and previous year's yield are used for forecasting spring wheat yield in each SAD. Cross-validation procedure which generates eight sets of models for the eight validation periods is used. To show the reproducing projection between observed and calculated values, the root mean squared error for skill score (RMSE SS) with the persistence model serving as the reference model is used. The persistence model is used as a benchmark. The results show that SADs near USA border show better RMSE SS values and mode 3's time coefficients can be a useful predictor especially for inland province such as Manitoba. Among 27 Canadian Prairie's SADs with perfect yield data, 67% of Alberta's SADs, 86% of Manitoba's SADs, and 77% of Saskatchewan's SADs can get positive skill scores. In each SAD, future yield projection is calculated applying predictors in 2013 for the obtained eight sets of models and eight sets of forecasted values in 2013 are averaged and a near future projection result is obtained. Series of outputs including calculated forecasted yield value in each SAD is provided by smart phone application. A system for providing climatic condition for a point with a permission of Climatic Research Unit - University of East Anglia and for obtaining patent is proposed. There are several patented systems similar to the system proposed in this paper. However, these patents are different in essence. The system proposed in this paper consists of two parts. First part is to estimate equations using time series data. The second part is to acquire and apply latest climatic conditions for obtained equations and calculate future projection. If the procedure is refined and devices are originally developed, series of idea can be patented. For future work, crop index, Hokkaido is also introduced.

Spatial and object-based attention modulates broadband high-frequency responses across the human visual cortical hierarchy.

PubMed

Davidesco, Ido; Harel, Michal; Ramot, Michal; Kramer, Uri; Kipervasser, Svetlana; Andelman, Fani; Neufeld, Miri Y; Goelman, Gadi; Fried, Itzhak; Malach, Rafael

2013-01-16

One of the puzzling aspects in the visual attention literature is the discrepancy between electrophysiological and fMRI findings: whereas fMRI studies reveal strong attentional modulation in the earliest visual areas, single-unit and local field potential studies yielded mixed results. In addition, it is not clear to what extent spatial attention effects extend from early to high-order visual areas. Here we addressed these issues using electrocorticography recordings in epileptic patients. The patients performed a task that allowed simultaneous manipulation of both spatial and object-based attention. They were presented with composite stimuli, consisting of a small object (face or house) superimposed on a large one, and in separate blocks, were instructed to attend one of the objects. We found a consistent increase in broadband high-frequency (30-90 Hz) power, but not in visual evoked potentials, associated with spatial attention starting with V1/V2 and continuing throughout the visual hierarchy. The magnitude of the attentional modulation was correlated with the spatial selectivity of each electrode and its distance from the occipital pole. Interestingly, the latency of the attentional modulation showed a significant decrease along the visual hierarchy. In addition, electrodes placed over high-order visual areas (e.g., fusiform gyrus) showed both effects of spatial and object-based attention. Overall, our results help to reconcile previous observations of discrepancy between fMRI and electrophysiology. They also imply that spatial attention effects can be found both in early and high-order visual cortical areas, in parallel with their stimulus tuning properties.

Plans for a new rio-imager experiment in Northern Scandinavia

NASA Astrophysics Data System (ADS)

Nielsen, E.; Hagfors, T.

1997-05-01

To observe the spatial variations and dynamics of charged particle precipitation in the high latitude ionosphere, a riometer experiment is planned, which from the ground will image the precipitation regions over an area of 300 × 300 km with a spatial resolution of 6 km in the zenith, increasing to 12 km at 60° zenith angle. The time resolution is one second. The spatial resolution represents a considerable improvement over existing imaging systems. The experiment employs a Mill's Cross technique not used before in riometer work: two 32 element rows of antennas form the antenna array, two 32 element Butler Matrices achieve directionality, and cross-correlation yield the directional intensities.

High-resolution Imaging of Deuterium-Tritium Capsule Implosions on the National Ignition Facility

NASA Astrophysics Data System (ADS)

Bachmann, Benjamin; Rygg, Ryan; Collins, Gilbert; Patel, Pravesh

2017-10-01

Highly-resolved 3-D simulations of inertial confinement fusion (ICF) implosions predict a hot spot plasma that exhibits complex micron-scale structure originating from a variety of 3-D perturbations. Experimental diagnosis of these conditions requires high spatial resolution imaging techniques. X-ray penumbral imaging can improve the spatial resolution over pinhole imaging while simultaneously increasing the detected photon yield at x-ray energies where the ablator opacity becomes negligible. Here we report on the first time-integrated x-ray penumbral imaging experiments of ICF capsule implosions at the National Ignition Facility that achieved spatial resolution as high as 4 micrometer. 6 to 30 keV hot spot images from layered DT implosions will be presented from a variety of experimental ICF campaigns, revealing previously unseen detail. It will be discussed how these and future results can be used to improve our physics understanding of inertially confined fusion plasmas by enabling spatially resolved measurements of hot spot properties, such as radiation energy, temperature or derived quantities. This work performed under the auspices of the U.S. Department of Energy by LLNL under Contract DE-AC52-07NA27344.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

Projecting water resources changes in potential large-scale agricultural investment areas of the Kafue River Basin in Zambia

NASA Astrophysics Data System (ADS)

Kim, Y.; Trainor, A. M.; Baker, T. J.

2017-12-01

Climate change impacts regional water availability through the spatial and temporal redistribution of available water resources. This study focuses on understanding possible response of water resources to climate change in regions where potentials for large-scale agricultural investments are planned in the upper and middle Kafue River Basin in Zambia. We used historical and projected precipitation and temperature to assess changes in water yield, using the Soil and Water Assessment Tool (SWAT) hydrological model. Some of the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model outputs for the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios project a temperature warming range from 1.8 - 5.7 °C over the region from 2020 to 2095. Precipitation projection patterns vary monthly but tend toward drier dry seasons with a slight increase in precipitation during the rainy season as compared to the historical time series. The best five calibrated parameter sets generated for the historical record (1965 - 2005) were applied for two future periods, 2020 - 2060 and 2055 - 2095, to project water yield change. Simulations projected that the 90th percentile water yield would be exceeded across most of the study area by up to 800% under the medium-low (RCP4.5) CO2 emission scenario, whereas the high (RCP8.5) CO2 emission scenario resulted in a more spatially varied pattern mixed with increasing (up to 500%) and decreasing (up to -54%) trends. The 10th percentile water yield indicated spatially varied pattern across the basin, increasing by as much as 500% though decreasing in some areas by 66%, with the greatest decreases during the dry season under RCP8.5. Overall, available water resources in the study area are projected to trend toward increased floods (i.e. water yields far exceeding 90th percentile) as well as increasing drought (i.e. water yield far below 10th percentile) vulnerability. Because surface water is a primary source for agriculture in this region, planning must focus on simulating the potential range in spatial and temporal variability of water resources for different agricultural production schemes, their infrastructure requirements, and attendant influence on water resources in the basin.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status.

PubMed

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain.

Soil Tillage Management Affects Maize Grain Yield by Regulating Spatial Distribution Coordination of Roots, Soil Moisture and Nitrogen Status

PubMed Central

Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming

2015-01-01

The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain. PMID:26098548

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

Temporally dependent pollinator competition and facilitation with mass flowering crops affects yield in co-blooming crops

PubMed Central

Grab, Heather; Blitzer, Eleanor J.; Danforth, Bryan; Loeb, Greg; Poveda, Katja

2017-01-01

One of the greatest challenges in sustainable agricultural production is managing ecosystem services, such as pollination, in ways that maximize crop yields. Most efforts to increase services by wild pollinators focus on management of natural habitats surrounding farms or non-crop habitats within farms. However, mass flowering crops create resource pulses that may be important determinants of pollinator dynamics. Mass bloom attracts pollinators and it is unclear how this affects the pollination and yields of other co-blooming crops. We investigated the effects of mass flowering apple on the pollinator community and yield of co-blooming strawberry on farms spanning a gradient in cover of apple orchards in the landscape. The effect of mass flowering apple on strawberry was dependent on the stage of apple bloom. During early and peak apple bloom, pollinator abundance and yield were reduced in landscapes with high cover of apple orchards. Following peak apple bloom, pollinator abundance was greater on farms with high apple cover and corresponded with increased yields on these farms. Spatial and temporal overlap between mass flowering and co-blooming crops alters the strength and direction of these dynamics and suggests that yields can be optimized by designing agricultural systems that avoid competition while maximizing facilitation. PMID:28345653

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River.

PubMed

Ouyang, Wei; Hao, Fanghua; Skidmore, Andrew K; Toxopeus, A G

2010-12-15

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area. Copyright © 2010 Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiong, Wei; Balkovic, Juraj; van der Velde, M.

Crop models are increasingly used to assess impacts of climate change/variability and management practices on productivity and environmental performance of alternative cropping systems. Calibration is an important procedure to improve reliability of model simulations, especially for large area applications. However, global-scale crop model calibration has rarely been exercised due to limited data availability and expensive computing cost. Here we present a simple approach to calibrate Environmental Policy Integrated Climate (EPIC) model for a global implementation of rice. We identify four parameters (potential heat unit – PHU, planting density – PD, harvest index – HI, and biomass energy ratio – BER)more » and calibrate them regionally to capture the spatial pattern of reported rice yield in 2000. Model performance is assessed by comparing simulated outputs with independent FAO national data. The comparison demonstrates that the global calibration scheme performs satisfactorily in reproducing the spatial pattern of rice yield, particularly in main rice production areas. Spatial agreement increases substantially when more parameters are selected and calibrated, but with varying efficiencies. Among the parameters, PHU and HI exhibit the highest efficiencies in increasing the spatial agreement. Simulations with different calibration strategies generate a pronounced discrepancy of 5–35% in mean yields across latitude bands, and a small to moderate difference in estimated yield variability and yield changing trend for the period of 1981–2000. Present calibration has little effects in improving simulated yield variability and trends at both regional and global levels, suggesting further works are needed to reproduce temporal variability of reported yields. This study highlights the importance of crop models’ calibration, and presents the possibility of a transparent and consistent up scaling approach for global crop simulations given current availability of global databases of weather, soil, crop calendar, fertilizer and irrigation management information, and reported yield.« less

Examining the roles that changing harvested areas, closing yield-gaps, and increasing yield ceilings have had on crop production

NASA Astrophysics Data System (ADS)

Johnston, M.; Ray, D. K.; Mueller, N. D.; Foley, J. A.

2011-12-01

With an increasing and increasingly affluent population, there has been tremendous effort to examine strategies for sustainably increasing agricultural production to meet this surging global demand. Before developing new solutions from scratch, though, we believe it is important to consult our recent agricultural history to see where and how agricultural production changes have already taken place. By utilizing the newly created temporal M3 cropland datasets, we can for the first time examine gridded agricultural yields and area, both spatially and temporally. This research explores the historical drivers of agricultural production changes, from 1965-2005. The results will be presented spatially at the global-level (5-min resolution), as well as at the individual country-level. The primary research components of this study are presented below, including the general methodology utilized in each phase and preliminary results for soybean where available. The complete assessment will cover maize, wheat, rice, soybean, and sugarcane, and will include country-specific analysis for over 200 countries, states, territories and protectorates. Phase 1: The first component of our research isolates changes in agricultural production due to variation in planting decisions (harvested area) from changes in production due to intensification efforts (yield). We examine area/yield changes at the pixel-level over 5-year time-steps to determine how much each component has contributed to overall changes in production. Our results include both spatial patterns of changes in production, as well as spatial maps illustrating to what degree the production change is attributed to area and/or yield. Together, these maps illustrate where, why, and by how much agricultural production has changed over time. Phase 2: In the second phase of our research we attempt to determine the impact that area and yield changes have had on agricultural production at the country-level. We calculate a production-weighted result of area and yield contributions for each country, at each time-step. As part of our research we will generate historic figures and tabular data for every country-crop combination. Phase 3: In the final phase of our research, we attempt to demonstrate how different yield performers (for example, those growing crops at the yield floor vs. the yield ceiling) have utilized different area/yield strategies to increase agricultural production. To group individual pixels into performance quintiles, we utilize binning strategies from previous spatial yield-gap assessments. The results from this step will illustrate how the yield ceiling has improved over time vis-à-vis improvements in the yield floor. As we look forward to a more sustainable and productive agricultural future, we hope the results of this global analysis of our agricultural past can be utilized to identify both optimal and adverse strategies for agricultural growth.

A Geostatistical Approach to the Trickle Irrigation Design in a Heterogeneous Soil 2. A Field Test

NASA Astrophysics Data System (ADS)

Russo, David

1984-05-01

In a heterogeneous field in which the soil water properties vary under a "deterministic" uniform trickle irrigation system, the midway soil-water pressure head hc and the yield of a crop also differ from place to place. These differences may, in turn, reduce the average (over the field) yield relative to the yield that would be obtained if the soil was uniform throughout the field. A field experiment was conducted to test the hypothesis that this yield reduction may be eliminated by using a spatially variable trickle irrigation system. Twenty-five plots (200 m2 each) were established on a 30-m2 grid. Half of each plot was equipped with a standard trickle irrigation system with constant spacing between emitters of d = 50 cm (control plots), and the other half was equipped with a trickle irrigation system for which the spacing between the emitters was selected by using the pertinent hydraulic properties (the saturated hydraulic conductivity Ks and the soil parameter α) according to the procedure of Bresler (1978) as described in paper 1 (Russo, 1983b). Values of hc measured at different times, as well as the total fruit yield Y of bell pepper (Capsicum frutescens var. "Maor"), were used to estimate the seasonal and the spatial distributions of hc and the spatial distribution of Y and their moments. The variograms of hc and Y were calculated and used to estimate their integral scales. It was found that the use of a spatially variable d relative to the use of a uniform d did not change the seasonal behavior of hc but reduced the spatial variability in hc and Y by 35% and 11%, respectively, and increased the integral scale of hc and Y by 30% and 10%, respectively, but increased the average total fruit yield by only 1.9%. The use of a spatially variable d reduced the dependence of Y on hc. This indicates that when the emitters are properly spaced, it is not the water but other factors that most influence yield. When a constant d was used, the dependence of Y of hc decreased with time. This and the relatively good agreement between the values of hc measured at the initial stages of the growing season and those calculated in paper 1 demonstrate that the concept of hc is important in the early stages of the plant's growth, when the root system is not fully developed. Both the theoretical (paper 1) and the experimental results showed that although Ks and α, as well as hc, varied considerably in the field the spatial variability of the crop yield was relatively small. This explains why the use of a spatially variable d essentially was not an improvement over the fixed d. It is suggested that this study will be considered as a methodological one, which can be adapted to solve practical problems associated with field spatial variability.

Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data.

PubMed

Ogutu, Booker O; Dash, Jadunandan; Dawson, Terence P

2013-09-01

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2)  > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2)  > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution. © 2013 John Wiley & Sons Ltd.

Cluster secondary ion mass spectrometry microscope mode mass spectrometry imaging.

PubMed

Kiss, András; Smith, Donald F; Jungmann, Julia H; Heeren, Ron M A

2013-12-30

Microscope mode imaging for secondary ion mass spectrometry is a technique with the promise of simultaneous high spatial resolution and high-speed imaging of biomolecules from complex surfaces. Technological developments such as new position-sensitive detectors, in combination with polyatomic primary ion sources, are required to exploit the full potential of microscope mode mass spectrometry imaging, i.e. to efficiently push the limits of ultra-high spatial resolution, sample throughput and sensitivity. In this work, a C60 primary source was combined with a commercial mass microscope for microscope mode secondary ion mass spectrometry imaging. The detector setup is a pixelated detector from the Medipix/Timepix family with high-voltage post-acceleration capabilities. The system's mass spectral and imaging performance is tested with various benchmark samples and thin tissue sections. The high secondary ion yield (with respect to 'traditional' monatomic primary ion sources) of the C60 primary ion source and the increased sensitivity of the high voltage detector setup improve microscope mode secondary ion mass spectrometry imaging. The analysis time and the signal-to-noise ratio are improved compared with other microscope mode imaging systems, all at high spatial resolution. We have demonstrated the unique capabilities of a C60 ion microscope with a Timepix detector for high spatial resolution microscope mode secondary ion mass spectrometry imaging. Copyright © 2013 John Wiley & Sons, Ltd.

Jet formation in cerium metal to examine material strength

DOE PAGES

Jensen, B. J.; Cherne, F. J.; Prime, M. B.; ...

2015-11-18

Examining the evolution of material properties at extreme conditions advances our understanding of numerous high-pressure phenomena from natural events like meteorite impacts to general solid mechanics and fluid flow behavior. Some recent advances in synchrotron diagnostics coupled with dynamic compression platforms have introduced new possibilities for examining in-situ, spatially resolved material response with nanosecond time resolution. In this work, we examined jet formation from a Richtmyer-Meshkov instability in cerium initially shocked into a transient, high-pressure phase, and then released to a low-pressure, higher-temperature state. Cerium's rich phase diagram allows us to study the yield stress following a shock induced solid-solidmore » phase transition. X-ray imaging was used to obtain images of jet formation and evolution with 2–3 μm spatial resolution. And from these images, an analytic method was used to estimate the post-shock yield stress, and these results were compared to continuum calculations that incorporated an experimentally validated equation-of-state (EOS) for cerium coupled with a deviatoric strength model. Reasonable agreement was observed between the calculations and the data illustrating the sensitivity of jet formation on the yield stress values. Finally, the data and analysis shown here provide insight into material strength during dynamic loading which is expected to aid in the development of strength aware multi-phase EOS required to predict the response of matter at extreme conditions.« less

[Applicability of established drought index in Huang-Huai-Hai region based on actual evapotranspiration.

PubMed

Wang, Ying; Wu, Rong Jun; Guo, Zhao Bing

2016-05-01

Based on the modeled products of actual evapotranspiration with NOAH land surface model, the temporal and spatial variations of actual evapotranspiration were analyzed for the Huang-Huai-Hai region in 2002-2010. In the meantime, the agricultural drought index, namely, drought severity index (DSI) was constructed, incorporated with products of MOD17 potential evapotranspiration and MOD13 NDVI. Furthermore, the applicability of established DSI in this region in the whole year of 2002 was investigated based on the Palmer drought severity index (PDSI), the yield reduction rate of winter wheat, and drought severity data. The results showed that the annual average actual evapotranspiration within the survey region increased from the northwest to the southeast, with the maximum of 800-900 mm in the southeast and the minimum less than 300 mm in the northwest. The DSI and PDSI had positive correlation (R 2 =0.61) and high concordance in change trend. They all got the low point (-0.61 and -1.33) in 2002 and reached the peak (0.81 and 0.92) in 2003. The correlation between DSI and yield reduction rate of winter wheat (R 2 =0.43) was more significant than that between PDSI and yield reduction rate of winter wheat (R 2 =0.06). So, the DSI reflected a high spatial resolution of drought pattern and could reflect the region agricultural drought severity and intensity more accurately.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sinistore, Julie C.; Reinemann, D. J.; Izaurralde, Roberto C.

Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combinedmore » with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.« less

Method to optimize patch size based on spatial frequency response in image rendering of the light field

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Yanan; Zhu, Zhenhao; Su, Jinhui

2018-05-01

A focused plenoptic camera can effectively transform angular and spatial information to yield a refocused rendered image with high resolution. However, choosing a proper patch size poses a significant problem for the image-rendering algorithm. By using a spatial frequency response measurement, a method to obtain a suitable patch size is presented. By evaluating the spatial frequency response curves, the optimized patch size can be obtained quickly and easily. Moreover, the range of depth over which images can be rendered without artifacts can be estimated. Experiments show that the results of the image rendered based on frequency response measurement are in accordance with the theoretical calculation, which indicates that this is an effective way to determine the patch size. This study may provide support to light-field image rendering.

Evolution of the spatiotemporal pattern of PM2.5 concentrations in China - A case study from the Beijing-Tianjin-Hebei region

NASA Astrophysics Data System (ADS)

Yan, Dan; Lei, Yalin; Shi, Yukun; Zhu, Qing; Li, Li; Zhang, Zhien

2018-06-01

Atmospheric haze pollution has become a global concern because of its severe effects on human health and the environment. The Beijing-Tianjin-Hebei urban agglomeration is located in northern China, and its haze is the most serious in China. The high concentration of PM2.5 is the main cause of haze pollution, and thus investigating the temporal and spatial characteristics of PM2.5 is important for understanding the mechanisms underlying PM2.5 pollution and for preventing haze. In this study, the PM2.5 concentration status in 13 cities from the Beijing-Tianjin-Hebei region was statistically analyzed from January 2016 to November 2016, and the spatial variation of PM2.5 was explored via spatial autocorrelation analysis. The research yielded three overall results. (1) The distribution of PM2.5 concentrations in this area varied greatly during the study period. The concentrations increased from late autumn to early winter, and the spatial range expanded from southeast to northwest. In contrast, the PM2.5 concentration decreased rapidly from late winter to early spring, and the spatial range narrowed from northwest to southeast. (2) The spatial dependence degree, by season from high to low, was in the order winter, autumn, spring, summer. Winter (from December to February of the subsequent year) and summer (from June to August) were, respectively, the highest and lowest seasons with regard to the spatial homogeneity of PM2.5 concentrations. (3) The PM2.5 concentration in the Beijing-Tianjin-Hebei region has significant spatial spillovers. Overall, cities far from Bohai Bay, such as Shijiazhuang and Hengshui, demonstrated a high-high concentration of PM2.5 pollution, while coastal cities, such as Chengde and Qinhuangdao, showed a low-low concentration.

Magnetic resonance imaging of semicircular canals.

PubMed Central

Sbarbati, A; Leclercq, F; Zancanaro, C; Antonakis, K

1992-01-01

The present paper reports the results of the first investigation of the semicircular canals in a living, small animal by means of high spatial resolution magnetic resonance imaging. This procedure is noninvasive and allows identification of the endolymphatic and perilymphatic spaces yielding a morphology quite consistent with direct anatomical examination. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 PMID:1506290

High spectral and spatial resolution hyperspectral imagery for quantifying Russian wheat aphid infestation in wheat using the constrained energy minimization classifier

USDA-ARS?s Scientific Manuscript database

The effects of insect infestation in agricultural crops are of major ecological and economic interest because of reduced yield, increased cost of pest control, and increased risk of environmental contamination from insecticide application. The Russian wheat aphid (RWA, Diuraphis noxia) is an insect...

Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands

Treesearch

Juan Guerra-Hernández; Eduardo González-Ferreiro; Vicente Monleon; Sonia Faias; Margarida Tomé; Ramón Díaz-Varela

2017-01-01

High spatial resolution imagery provided by unmanned aerial vehicles (UAVs) can yield accurate and efficient estimation of tree dimensions and canopy structural variables at the local scale. We flew a low-cost, lightweight UAV over an experimental Pinus pinea L. plantation (290 trees distributed over 16 ha with different fertirrigation treatments)...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Shunmin; Tian, Chengcheng; Zhu, Xiang

Transition-metal-catalyzed cyanation of aryl halides is a common route to benzonitriles, which are integral to many industrial procedures. However, traditional homogeneous catalysts for such processes are expensive and suffer poor recyclability, so a heterogeneous analogue is highly desired. A novel spatial modulation approach has been developed in this paper to fabricate a heterogeneous Pd-metalated nanoporous polymer, which catalyzes the cyanation of aryl halides without need for ligands. Finally, the catalyst displays high activity in the synthesis of benzonitriles, including high product yields, excellent stability and recycling, and broad functional-group tolerance.

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.

2014-10-07

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less

Current nitrogen management status and measures to improve the intensive wheat-maize system in China.

PubMed

Cui, Zhenling; Chen, Xinping; Zhang, Fusuo

2010-01-01

During the first 35 years of the Green Revolution, Chinese grain production doubled, greatly reducing food shortage, but at a high environmental cost. In 2005, China alone accounted for around 38% of the global N fertilizer consumption, but the average on-farm N recovery efficiency for the intensive wheat-maize system was only 16-18%. Current on-farm N use efficiency (NUE) is much lower than in research trials or on-farm in other parts of the world, which is attributed to the overuse of chemical N fertilizer, ignorance of the contribution of N from the environment and the soil, poor synchrony between crop N demand and N supply, failure to bring crop yield potential into full play, and an inability to effectively inhibit N losses. Based on such analyses, some measures to drastically improve NUE in China are suggested, such as managing various N sources to limit the total applied N, spatially and temporally matching rhizospheric N supply with N demand in high-yielding crops, reducing N losses, and simultaneously achieving high-yield and high NUE. Maximizing crop yields using a minimum of N inputs requires an integrated, interdisciplinary cooperation and major scientific and practical breakthroughs involving plant nutrition, soil science, agronomy, and breeding.

Impacts of ozone air pollution and temperature extremes on crop yields: Spatial variability, adaptation and implications for future food security

NASA Astrophysics Data System (ADS)

Tai, Amos P. K.; Val Martin, Maria

2017-11-01

Ozone air pollution and climate change pose major threats to global crop production, with ramifications for future food security. Previous studies of ozone and warming impacts on crops typically do not account for the strong ozone-temperature correlation when interpreting crop-ozone or crop-temperature relationships, or the spatial variability of crop-to-ozone sensitivity arising from varietal and environmental differences, leading to potential biases in their estimated crop losses. Here we develop an empirical model, called the partial derivative-linear regression (PDLR) model, to estimate the spatial variations in the sensitivities of wheat, maize and soybean yields to ozone exposures and temperature extremes in the US and Europe using a composite of multidecadal datasets, fully correcting for ozone-temperature covariation. We find generally larger and more spatially varying sensitivities of all three crops to ozone exposures than are implied by experimentally derived concentration-response functions used in most previous studies. Stronger ozone tolerance is found in regions with high ozone levels and high consumptive crop water use, reflecting the existence of spatial adaptation and effect of water constraints. The spatially varying sensitivities to temperature extremes also indicate stronger heat tolerance in crops grown in warmer regions. The spatial adaptation of crops to ozone and temperature we find can serve as a surrogate for future adaptation. Using the PDLR-derived sensitivities and 2000-2050 ozone and temperature projections by the Community Earth System Model, we estimate that future warming and unmitigated ozone pollution can combine to cause an average decline in US wheat, maize and soybean production by 13%, 43% and 28%, respectively, and a smaller decline for European crops. Aggressive ozone regulation is shown to offset such decline to various extents, especially for wheat. Our findings demonstrate the importance of considering ozone regulation as well as ozone and climate change adaptation (e.g., selecting heat- and ozone-tolerant cultivars, irrigation) as possible strategies to enhance future food security in response to imminent environmental threats.

Using a spatially explicit analysis model to evaluate spatial variation of corn yield

USDA-ARS?s Scientific Manuscript database

Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Beyond the plot: technology extrapolation domains for scaling out agronomic science

NASA Astrophysics Data System (ADS)

Rattalino Edreira, Juan I.; Cassman, Kenneth G.; Hochman, Zvi; van Ittersum, Martin K.; van Bussel, Lenny; Claessens, Lieven; Grassini, Patricio

2018-05-01

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland. Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate ‘technology extrapolation domains’ based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment.

Variability of Precipitation and Evapotranspiration across an Andean Paramo

NASA Astrophysics Data System (ADS)

Jaimes, J. C.; Riveros-Iregui, D.; Avery, W. A.; Gaviria, S.; Peña-Quemba, C.; Herran, G.

2012-12-01

Paramos are alpine grasslands that occur mostly in the Andes Mountains of South America. Typically soils in the paramo have a volcanic origin, which leads to high permeability and high water yield and makes the paramo a reliable drinking water supply for many highland cities. Because hydrological measurements in these humid systems are rare, current understanding of the hydrologic behavior of paramos relies on modeling studies with little validation against ground observations. We present measurements of evapotranspiration (ET) and precipitation (P) across Chingaza Paramo, near Bogotá, Colombia. This paramo supplies water for ~80% of Bogotá's population (a total of 8 million people). Meteorological variables such us air temperature, relative humidity, wind speed, precipitation, and solar radiation were monitored using five weather stations located at various elevations from 3000m to 3600m. Our results show that ET varies from 500 to 700 mm y-1 as a function of elevation, whereas precipitation commonly exceeds ET, ranging between 1500 and 1800 mm y-1. These spatial differences between P and ET make water yield highly variable across this mountainous environment. Our results demonstrate that while paramos play an important role in the hydrologic cycle of tropical environments, understanding their hydrologic behavior requires characterization and monitoring of the pronounced spatial gradients of precipitation and evapotranspiration.

Aligned metal absorbers and the ultraviolet background at the end of reionization

NASA Astrophysics Data System (ADS)

Doughty, Caitlin; Finlator, Kristian; Oppenheimer, Benjamin D.; Davé, Romeel; Zackrisson, Erik

2018-04-01

We use observations of spatially aligned C II, C IV, Si II, Si IV, and O I absorbers to probe the slope and intensity of the ultraviolet background (UVB) at z ˜ 6. We accomplish this by comparing observations with predictions from a cosmological hydrodynamic simulation using three trial UVBs applied in post-processing: a spectrally soft, fluctuating UVB calculated using multifrequency radiative transfer; a soft, spatially uniform UVB; and a hard, spatially uniform `quasars-only' model. When considering our paired high-ionization absorbers (C IV/Si IV), the observed statistics strongly prefer the hard, spatially uniform UVB. This echoes recent findings that cosmological simulations generically underproduce strong C IV absorbers at z > 5. A single low/high ionization pair (Si II/Si IV), by contrast, shows a preference for the HM12 UVB, whereas two more (C II/C IV and O I/C IV) show no preference for any of the three UVBs. Despite this, future observations of specific absorbers, particularly Si IV/C IV, with next-generation telescopes probing to lower column densities should yield tighter constraints on the UVB.

How does spatial and temporal resolution of vegetation index impact crop yield estimation?

USDA-ARS?s Scientific Manuscript database

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing data have long been used in crop yield estimation for decades. The process-based approach uses light use efficiency model to estimate crop yield. Vegetation index (VI) ...

Microchannel plate detector technology potential for LUVOIR and HabEx

NASA Astrophysics Data System (ADS)

Siegmund, O. H. W.; Ertley, C.; Vallerga, J. V.; Schindhelm, E. R.; Harwit, A.; Fleming, B. T.; France, K. C.; Green, J. C.; McCandliss, S. R.; Harris, W. M.

2017-08-01

Microchannel plate (MCP) detectors have been the detector of choice for ultraviolet (UV) instruments onboard many NASA missions. These detectors have many advantages, including high spatial resolution (<20 μm), photon counting, radiation hardness, large formats (up to 20 cm), and ability for curved focal plane matching. Novel borosilicate glass MCPs with atomic layer deposition combine extremely low backgrounds, high strength, and tunable secondary electron yield. GaN and combinations of bialkali/alkali halide photocathodes show promise for broadband, higher quantum efficiency. Cross-strip anodes combined with compact ASIC readout electronics enable high spatial resolution over large formats with high dynamic range. The technology readiness levels of these technologies are each being advanced through research grants for laboratory testing and rocket flights. Combining these capabilities would be ideal for UV instruments onboard the Large UV/Optical/IR Surveyor (LUVOIR) and the Habitable Exoplanet Imaging Mission (HABEX) concepts currently under study for NASA's Astrophysics Decadal Survey.

Complex terrain in the Critical Zone: How topography drives ecohydrological patterns of soil and plant carbon exchange in a semiarid mountainous system

NASA Astrophysics Data System (ADS)

Barron-Gafford, G.; Minor, R. L.; Heard, M. M.; Sutter, L. F.; Yang, J.; Potts, D. L.

2015-12-01

The southwestern U.S. is predicted to experience increasing temperatures and longer periods of inter-storm drought. High temperature and water deficit restrict plant productivity and ecosystem functioning, but the influence of future climate is predicted to be highly heterogeneous because of the complex terrain characteristic of much of the Critical Zone (CZ). Within our Critical Zone Observatory (CZO) in the Southwestern US, we monitor ecosystem-scale carbon and water fluxes using eddy covariance. This whole-ecosystem metric is a powerful integrating measure of ecosystem function over time, but details on spatial heterogeneity resulting from topographic features of the landscape are not captured, nor are interactions among below- and aboveground processes. We supplement eddy covariance monitoring with distributed measures of carbon flux from soil and vegetation across different aspects to quantify the causes and consequences of spatial heterogeneity through time. Given that (i) aspect influences how incoming energy drives evaporative water loss and (ii) seasonality drives temporal patterns of soil moisture recharge, we were able to examine the influence of these processes on CO2 efflux by investigating variation across aspect. We found that aspect was a significant source of spatial heterogeneity in soil CO2 efflux, but the influence varied across seasonal periods. Snow on South-facing aspects melted earlier and yielded higher efflux rates in the spring. However, during summer, North- and South-facing aspects had similar amounts of soil moisture, but soil temperatures were warmer on the North-facing aspect, yielding greater rates of CO2 efflux. Interestingly, aspect did not influence photosynthetic rates. Taken together, we found that physical features of the landscape yielded predictable patterns of levels and phenologies of soil moisture and temperature, but these drivers differentially influenced below- and aboveground sources of carbon exchange. Conducting these spatially distributed measurements are time consuming. Looking forward, we have begun using unmanned aerial vehicles outfitted with thermal and multi-spectral cameras to quantify patterns of water flux, NDVI, needle browning due to moisture stress, and overall phenology in the CZ.

Visualizing deceleration-phase instabilities in inertial confinement fusion implosions using an "enhanced self-emission" technique at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Pickworth, L. A.; Hammel, B. A.; Smalyuk, V. A.; Robey, H. F.; Benedetti, L. R.; Berzak Hopkins, L.; Bradley, D. K.; Field, J. E.; Haan, S. W.; Hatarik, R.; Hartouni, E.; Izumi, N.; Johnson, S.; Khan, S.; Lahmann, B.; Landen, O. L.; Le Pape, S.; MacPhee, A. G.; Meezan, N. B.; Milovich, J.; Nagel, S. R.; Nikroo, A.; Pak, A. E.; Petrasso, R.; Remington, B. A.; Rice, N. G.; Springer, P. T.; Stadermann, M.; Widmann, K.; Hsing, W.

2018-05-01

High-mode perturbations and low-mode asymmetries were measured in the deceleration phase of indirectly driven, deuterium gas filled inertial confinement fusion capsule implosions at convergence ratios of 10 to 15, using a new "enhanced emission" technique at the National Ignition Facility [E. M. Campbell et al., AIP Conf. Proc. 429, 3 (1998)]. In these experiments, a high spatial resolution Kirkpatrick-Baez microscope was used to image the x-ray emission from the inner surface of a high-density-carbon capsule's shell. The use of a high atomic number dopant in the shell enabled time-resolved observations of shell perturbations penetrating into the hot spot. This allowed the effects of the perturbations and asymmetries on degrading neutron yield to be directly measured. In particular, mix induced radiation losses of ˜400 J from the hot spot resulted in a neutron yield reduction of a factor of ˜2. In a subsequent experiment with a significantly increased level of short-mode initial perturbations, shown through the enhanced imaging technique to be highly organized radially, the neutron yield dropped an additional factor of ˜2.

GIS-Based Multi-Criteria Analysis for Arabica Coffee Expansion in Rwanda

PubMed Central

Nzeyimana, Innocent; Hartemink, Alfred E.; Geissen, Violette

2014-01-01

The Government of Rwanda is implementing policies to increase the area of Arabica coffee production. Information on the suitable areas for sustainably growing Arabica coffee is still scarce. This study aimed to analyze suitable areas for Arabica coffee production. We analyzed the spatial distribution of actual and potential production zones for Arabica coffee, their productivity levels and predicted potential yields. We used a geographic information system (GIS) for a weighted overlay analysis to assess the major production zones of Arabica coffee and their qualitative productivity indices. Actual coffee yields were measured in the field and were used to assess potential productivity zones and yields using ordinary kriging with ArcGIS software. The production of coffee covers about 32 000 ha, or 2.3% of all cultivated land in the country. The major zones of production are the Kivu Lake Borders, Central Plateau, Eastern Plateau, and Mayaga agro-ecological zones, where coffee is mainly cultivated on moderate slopes. In the highlands, coffee is grown on steep slopes that can exceed 55%. About 21% percent of the country has a moderate yield potential, ranging between 1.0 and 1.6 t coffee ha−1, and 70% has a low yield potential (<1.0 t coffee ha−1). Only 9% of the country has a high yield potential of 1.6–2.4 t coffee ha−1. Those areas are found near Lake Kivu where the dominant soil Orders are Inceptisols and Ultisols. Moderate yield potential is found in the Birunga (volcano), Congo-Nile watershed Divide, Impala and Imbo zones. Low-yield regions (<1 t ha−1) occur in the eastern semi-dry lowlands, Central Plateau, Eastern Plateau, Buberuka Highlands, and Mayaga zones. The weighted overlay analysis and ordinary kriging indicated a large spatial variability of potential productivity indices. Increasing the area and productivity of coffee in Rwanda thus has considerable potential. PMID:25299459

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

Low altitude remote sensing technologies for crop stress monitoring: a case study on spatial and temporal monitoring of irrigated pinto bean

USDA-ARS?s Scientific Manuscript database

Site-specific crop management is a promising approach to maximize crop yield with optimal use of rapidly depleting natural resources. Availability of high resolution crop data at critical growth stages is a key for real-time data-driven decisions during the production season. The goal of this study ...

Simultaneous multispectral reflectance imaging and laser speckle flowmetry of cerebral blood flow and oxygen metabolism in focal cerebral ischemia

PubMed Central

Jones, Phill B.; Shin, Hwa Kyoung; Boas, David A.; Hyman, Bradley T.; Moskowitz, Michael A.; Ayata, Cenk; Dunn, Andrew K.

2009-01-01

Real-time investigation of cerebral blood flow (CBF), and oxy- and deoxyhemoglobin concentration (HbO, HbR) dynamics has been difficult until recently due to limited spatial and temporal resolution of techniques like laser Doppler flowmetry and magnetic resonance imaging (MRI). The combination of laser speckle flowmetry (LSF) and multispectral reflectance imaging (MSRI) yields high-resolution spatiotemporal maps of hemodynamic and metabolic changes in response to functional cortical activation. During acute focal cerebral ischemia, changes in HbO and HbR are much larger than in functional activation, resulting in the failure of the Beer-Lambert approximation to yield accurate results. We describe the use of simultaneous LSF and MSRI, using a nonlinear Monte Carlo fitting technique, to record rapid changes in CBF, HbO, HbR, and cerebral metabolic rate of oxygen (CMRO2) during acute focal cerebral ischemia induced by distal middle cerebral artery occlusion (dMCAO) and reperfusion. This technique captures CBF and CMRO2 changes during hemodynamic and metabolic events with high temporal and spatial resolution through the intact skull and demonstrates the utility of simultaneous LSF and MSRI in mouse models of cerebrovascular disease. PMID:19021335

GIANT MOLECULAR CLOUDS AND STAR FORMATION IN THE NON-GRAND DESIGN SPIRAL GALAXY NGC 6946

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rebolledo, David; Wong, Tony; Leroy, Adam

We present high spatial resolution observations of giant molecular clouds (GMCs) in the eastern part of the nearby spiral galaxy NGC 6946 obtained with the Combined Array for Research in Millimeter-wave Astronomy (CARMA). We have observed CO(1 {yields} 0), CO(2 {yields} 1) and {sup 13}CO(1 {yields} 0), achieving spatial resolutions of 5.''4 Multiplication-Sign 5.''0, 2.''5 Multiplication-Sign 2.''0, and 5.''6 Multiplication-Sign 5.''4, respectively, over a region of 6 Multiplication-Sign 6 kpc. This region extends from 1.5 kpc to 8 kpc galactocentric radius, thus avoiding the intense star formation in the central kpc. We have recovered short-spacing u-v components by using singlemore » dish observations from the Nobeyama 45 m and IRAM 30 m telescopes. Using the automated CPROPS algorithm, we identified 45 CO cloud complexes in the CO(1 {yields} 0) map and 64 GMCs in the CO(2 {yields} 1) maps. The sizes, line widths, and luminosities of the GMCs are similar to values found in other extragalactic studies. We have classified the clouds into on-arm and inter-arm clouds based on the stellar mass density traced by the 3.6 {mu}m map. Clouds located on-arm present in general higher star formation rates than clouds located in inter-arm regions. Although the star formation efficiency shows no systematic trend with galactocentric radius, some on-arm clouds-which are more luminous and more massive compared to inter-arm GMCs-are also forming stars more efficiently than the rest of the identified GMCs. We find that these structures appear to be located in two specific regions in the spiral arms. One of them shows a strong velocity gradient, suggesting that this region of high star formation efficiency may be the result of gas flow convergence.« less

Investigation of transient dynamics of capillary assisted particle assembly yield

NASA Astrophysics Data System (ADS)

Virganavičius, D.; Juodėnas, M.; Tamulevičius, T.; Schift, H.; Tamulevičius, S.

2017-06-01

In this paper, the transient behavior of the particle assembly yield dynamics when switching from low yield to high yield deposition at different velocity and thermal regimes is investigated. Capillary force assisted particle assembly (CAPA) using colloidal suspension of green fluorescent 270 nm diameter polystyrene beads was performed on patterned poly (dimethyl siloxane) substrates using a custom-built deposition setup. Two types of patterns with different trapping site densities were used to assess CAPA process dynamics and the influence of pattern density and geometry on the deposition yield transitions. Closely packed 300 nm diameter circular pits ordered in hexagonal arrangement with 300 nm pitch, and 2 × 2 mm2 square pits with 2 μm spacing were used. 2-D regular structures of the deposited particles were investigated by means of optical fluorescence and scanning electron microscopy. The fluorescence micrographs were analyzed using a custom algorithm enabling to identify particles and calculate efficiency of the deposition performed at different regimes. Relationship between the spatial distribution of particles in transition zone and ambient conditions was evaluated and quantified by approximation of the yield profile with a logistic function.

Neutron imaging with lithium indium diselenide: Surface properties, spatial resolution, and computed tomography

NASA Astrophysics Data System (ADS)

Lukosi, Eric D.; Herrera, Elan H.; Hamm, Daniel S.; Burger, Arnold; Stowe, Ashley C.

2017-11-01

An array of lithium indium diselenide (LISe) scintillators were investigated for application in neutron imaging. The sensors, varying in thickness and surface roughness, were tested using both reflective and anti-reflective mounting to an aluminum window. The spatial resolution of each LISe scintillator was calculated using the knife-edge test and a modulation transfer function analysis. It was found that the anti-reflective backing case yielded higher spatial resolutions by up to a factor of two over the reflective backing case despite a reduction in measured light yield by an average of 1.97. In most cases, the use of an anti-reflective backing resulted in a higher spatial resolution than the 50 μm-thick ZnS(Cu):6 LiF comparison scintillation screen. The effect of surface roughness was not directly correlated to measured light yield or observed spatial resolution, but weighting the reflective backing case by the random surface roughness revealed that a linear relationship exists between the fractional change (RB/ARB) of the two. Finally, the LISe scintillator array was used in neutron computed tomography to investigate the features of halyomorpha halys with the reflective and anti-reflective backing.

The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

NASA Technical Reports Server (NTRS)

Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

2001-01-01

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Post-fire bedload sediment delivery across spatial scales in the interior western United States

Treesearch

Joseph W. Wagenbrenner; Peter R. Robichaud

2014-01-01

Post-fire sediment yields can be up to three orders of magnitude greater than sediment yields in unburned forests. Much of the research on post-fire erosion rates has been at small scales (100m2 or less), and post-fire sediment delivery rates across spatial scales have not been quantified in detail. We developed relationships for post-fire bedload sediment delivery...

Declining spatial efficiency of global cropland nitrogen allocation

NASA Astrophysics Data System (ADS)

Mueller, Nathaniel D.; Lassaletta, Luis; Runck, Bryan C.; Billen, Gilles; Garnier, Josette; Gerber, James S.

2017-02-01

Efficiently allocating nitrogen (N) across space maximizes crop productivity for a given amount of N input and reduces N losses to the environment. Here we quantify changes in the global spatial efficiency of cropland N use by calculating historical trade-off frontiers relating N inputs to possible N yield assuming efficient allocation. Time series cropland N budgets from 1961 to 2009 characterize the evolution of N input-yield response functions across 12 regions and are the basis for constructing trade-off frontiers. Improvements in agronomic technology have substantially increased cropping system yield potentials and expanded N-driven crop production possibilities. However, we find that these gains are compromised by the declining spatial efficiency of N use across regions. Since the start of the Green Revolution, N inputs and yields have moved farther from the optimal frontier over time; in recent years (1994-2009), global N surplus has grown to a value that is 69% greater than what is possible with efficient N allocation between regions. To reflect regional pollution and agricultural development goals, we construct scenarios that restrict reallocation, finding that these changes only slightly decrease potential gains in nitrogen use efficiency. Our results are inherently conservative due to the regional unit of analysis, meaning a larger potential exists than is quantified here for cross-scale policies to promote spatially efficient N use.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Transparent ceramic scintillators for gamma spectroscopy and MeV imaging

NASA Astrophysics Data System (ADS)

Cherepy, N. J.; Seeley, Z. M.; Payne, S. A.; Swanberg, E. L.; Beck, P. R.; Schneberk, D. J.; Stone, G.; Perry, R.; Wihl, B.; Fisher, S. E.; Hunter, S. L.; Thelin, P. A.; Thompson, R. R.; Harvey, N. M.; Stefanik, T.; Kindem, J.

2015-09-01

We report on the development of two new mechanically rugged, high light yield transparent ceramic scintillators: (1) Ce-doped Gd-garnet for gamma spectroscopy, and (2) Eu-doped Gd-Lu-bixbyite for radiography. GYGAG(Ce) garnet transparent ceramics offer ρ = 5.8g/cm3, Zeff = 48, principal decay of <100 ns, and light yield of 50,000 Ph/MeV. Gdgarnet ceramic scintillators offer the best energy resolution of any oxide scintillator, as good as R(662 keV) = 3% (Si-PD readout) for small sizes and typically R(662 keV) < 5% for cubic inch sizes. For radiography, the bixbyite transparent ceramic scintillator, (Gd,Lu,Eu)2O3, or "GLO," offers excellent x-ray stopping, with ρ = 9.1 g/cm3 and Zeff = 68. Several 10" diameter by 0.1" thickness GLO scintillators have been fabricated. GLO outperforms scintillator glass for high energy radiography, due to higher light yield (55,000 Ph/MeV) and better stopping, while providing spatial resolution of >8 lp/mm.

Perception of differences in naturalistic dynamic scenes, and a V1-based model.

PubMed

To, Michelle P S; Gilchrist, Iain D; Tolhurst, David J

2015-01-16

We investigate whether a computational model of V1 can predict how observers rate perceptual differences between paired movie clips of natural scenes. Observers viewed 198 pairs of movies clips, rating how different the two clips appeared to them on a magnitude scale. Sixty-six of the movie pairs were naturalistic and those remaining were low-pass or high-pass spatially filtered versions of those originals. We examined three ways of comparing a movie pair. The Spatial Model compared corresponding frames between each movie pairwise, combining those differences using Minkowski summation. The Temporal Model compared successive frames within each movie, summed those differences for each movie, and then compared the overall differences between the paired movies. The Ordered-Temporal Model combined elements from both models, and yielded the single strongest predictions of observers' ratings. We modeled naturalistic sustained and transient impulse functions and compared frames directly with no temporal filtering. Overall, modeling naturalistic temporal filtering improved the models' performance; in particular, the predictions of the ratings for low-pass spatially filtered movies were much improved by employing a transient impulse function. The correlations between model predictions and observers' ratings rose from 0.507 without temporal filtering to 0.759 (p = 0.01%) when realistic impulses were included. The sustained impulse function and the Spatial Model carried more weight in ratings for normal and high-pass movies, whereas the transient impulse function with the Ordered-Temporal Model was most important for spatially low-pass movies. This is consistent with models in which high spatial frequency channels with sustained responses primarily code for spatial details in movies, while low spatial frequency channels with transient responses code for dynamic events. © 2015 ARVO.

Spatial Variability of Grapevine Bud Burst Percentage and Its Association with Soil Properties at Field Scale

PubMed Central

Li, Tao; Hao, Xinmei; Kang, Shaozhong

2016-01-01

There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692

A reanalysis dataset of the South China Sea.

PubMed

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992-2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability.

A reanalysis dataset of the South China Sea

PubMed Central

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

A 64-pixel NbTiN superconducting nanowire single-photon detector array for spatially resolved photon detection.

PubMed

Miki, Shigehito; Yamashita, Taro; Wang, Zhen; Terai, Hirotaka

2014-04-07

We present the characterization of two-dimensionally arranged 64-pixel NbTiN superconducting nanowire single-photon detector (SSPD) array for spatially resolved photon detection. NbTiN films deposited on thermally oxidized Si substrates enabled the high-yield production of high-quality SSPD pixels, and all 64 SSPD pixels showed uniform superconducting characteristics within the small range of 7.19-7.23 K of superconducting transition temperature and 15.8-17.8 μA of superconducting switching current. Furthermore, all of the pixels showed single-photon sensitivity, and 60 of the 64 pixels showed a pulse generation probability higher than 90% after photon absorption. As a result of light irradiation from the single-mode optical fiber at different distances between the fiber tip and the active area, the variations of system detection efficiency (SDE) in each pixel showed reasonable Gaussian distribution to represent the spatial distributions of photon flux intensity.

Hyperspectral imagery for mapping crop yield for precision agriculture

USDA-ARS?s Scientific Manuscript database

Crop yield is perhaps the most important piece of information for crop management in precision agriculture. It integrates the effects of various spatial variables such as soil properties, topographic attributes, tillage, plant population, fertilization, irrigation, and pest infestations. A yield map...

Crosslinked polymer nanoparticles containing single conjugated polymer chains

NASA Astrophysics Data System (ADS)

Ponzio, Rodrigo A.; Marcato, Yésica L.; Gómez, María L.; Waiman, Carolina V.; Chesta, Carlos A.; Palacios, Rodrigo E.

2017-06-01

Conjugated polymer nanoparticles are widely used in fluorescent labeling and sensing, as they have mean radii between 5 and 100 nm, narrow size dispersion, high brightness, and are photochemically stable, allowing single particle detection with high spatial and temporal resolution. Highly crosslinked polymers formed by linking individual chains through covalent bonds yield high-strength rigid materials capable of withstanding dissolution by organic solvents. Hence, the combination of crosslinked polymers and conjugated polymers in a nanoparticulated material presents the possibility of interesting applications that require the combined properties of constituent polymers and nanosized dimension. In the present work, F8BT@pEGDMA nanoparticles composed of poly(ethylene glycol dimethacrylate) (pEGDMA; a crosslinked polymer) and containing the commercial conjugated polymer poly(9,9-dioctylfluorene-alt-benzothiadiazole) (F8BT) were synthesized and characterized. Microemulsion polymerization was applied to produce F8BT@pEDGMA particles with nanosized dimensions in a ∼25% yield. Photophysical and size distribution properties of F8BT@pEDGMA nanoparticles were evaluated by various methods, in particular single particle fluorescence microscopy techniques. The results demonstrate that the crosslinking/polymerization process imparts structural rigidity to the F8BT@pEDGMA particles by providing resistance against dissolution/disintegration in organic solvents. The synthesized fluorescent crosslinked nanoparticles contain (for the most part) single F8BT chains and can be detected at the single particle level, using fluorescence microscopy, which bodes well for their potential application as molecularly imprinted polymer fluorescent nanosensors with high spatial and temporal resolution.

Accelerated high-resolution photoacoustic tomography via compressed sensing

NASA Astrophysics Data System (ADS)

Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward

2016-12-01

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.

[Effects of sub-watershed landscape patterns at the upper reaches of Minjiang River on soil erosion].

PubMed

Yang, Meng; Li, Xiu-zhen; Yang, Zhao-ping; Hu, Yuan-man; Wen, Qing-chun

2007-11-01

Based on GIS, the spatial distribution of soil loss and sediment yield in Heishui and Zhenjiangguan sub-watersheds at the upper reaches of Minjiang River was simulated by using sediment delivery-distribution (SEDD) model, and the effects of land use/cover types on soil erosion and sediment yield were discussed, based on the simulated results and related land use maps. A landscape index named location-weighted landscape contrast index (LCI) was calculated to evaluate the effects of landscape components' spatial distribution, weight, and structure of land use/cover on soil erosion. The results showed the soil erosion modulus varied with land use pattern, and decreased in the order of bare rock > urban/village > rangeland > farmland > shrub > forest. There were no significant differences in sediment yield modules among different land use/covers. In the two sub-watersheds, the spatial distribution of land use/covers on slope tended to decrease the final sediment load at watershed outlet, hut as related to relative elevation, relative distance, and flow length, the spatial distribution tended to increase sediment yield. The two sub-watersheds had different advantages as related to landscape components' spatial distribution, but, when the land use/cover weight was considered, the advantages of Zhenjiangguan sub-watershed increased. If the land use/cover structure was considered in addition, the landscape pattern of Zhenjiangguan subwatershed was better. Therefore, only the three elements, i.e., landscape components' spatial distribution, land use/cover weight, and land use/cover structure, were considered comprehensively, can we get an overall evaluation on the effects of landscape pattern on soil erosion. The calculation of LCI related to slope suggested that this index couldn' t accurately reflect the effects of land use/cover weight and structure on soil erosion, and thus, needed to be modified.

Spatial variability in nutrient transport by HUC8, state, and subbasin based on Mississippi/Atchafalaya River Basin SPARROW models

USGS Publications Warehouse

Robertson, Dale M.; Saad, David A.; Schwarz, Gregory E.

2014-01-01

Nitrogen (N) and phosphorus (P) loading from the Mississippi/Atchafalaya River Basin (MARB) has been linked to hypoxia in the Gulf of Mexico. With geospatial datasets for 2002, including inputs from wastewater treatment plants (WWTPs), and monitored loads throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) watershed models were constructed specifically for the MARB, which reduced simulation errors from previous models. Based on these models, N loads/yields were highest from the central part (centered over Iowa and Indiana) of the MARB (Corn Belt), and the highest P yields were scattered throughout the MARB. Spatial differences in yields from previous studies resulted from different descriptions of the dominant sources (N yields are highest with crop-oriented agriculture and P yields are highest with crop and animal agriculture and major WWTPs) and different descriptions of downstream transport. Delivered loads/yields from the MARB SPARROW models are used to rank subbasins, states, and eight-digit Hydrologic Unit Code basins (HUC8s) by N and P contributions and then rankings are compared with those from other studies. Changes in delivered yields result in an average absolute change of 1.3 (N) and 1.9 (P) places in state ranking and 41 (N) and 69 (P) places in HUC8 ranking from those made with previous national-scale SPARROW models. This information may help managers decide where efforts could have the largest effects (highest ranked areas) and thus reduce hypoxia in the Gulf of Mexico.

Studies of multi-ion-fluid yield anomaly in shock-driven implosions

NASA Astrophysics Data System (ADS)

Rinderknecht, H. G.; Rosenberg, M. J.; Li, C. K.; Zylstra, A. B.; Sio, H.; Gatu Johnson, M.; Frenje, J. A.; Séguin, F. H.; Petrasso, R. D.; Amendt, P. A.; Bellei, C.; Wilks, S. C.; Zimmerman, G.; Hoffman, N. M.; Kagan, G.; Molvig, K.; Glebov, V. Yu.; Stoeckl, C.; Marshall, F. J.; Seka, W.; Delettrez, J. A.; Sangster, T. C.; Betti, R.; Goncharov, V. N.; Meyerhofer, D. D.

2014-10-01

A. NIKROO, GA - Anomalously reduced yields relative to hydrodynamically calculated values have been observed for mixtures of D:3He compared to pure D2 gas-filled implosions in a series of shock-driven implosions at OMEGA. An extensive suite of measurements including temporal and spatial measurements of both the DD- and D3He-fusion reactions were obtained to identify the origin and physics behind this anomalous yield reduction. Measured spectral linewidths of fusion products suggest that the D ions are not thermalized to 3He during the burn, contributing to the reduced yield. The hypothesis that ion-species separation due to diffusive processes contributes to the observed yield reduction is explored using hydrodynamic simulations incorporating ion diffusion. Recent observations by Rosenberg et al. of a yield reduction with increased ion-ion mean free path do not explain the observed anomalous yield trend. Future work that will directly probe species separation with high-precision relative fusion reaction rate measurements between DD-neutrons and D3He-protons using the DualPTD instrument is discussed. This work was supported in part by the U.S. DOE, NLUF, LLE, and LLNL.

Towards efficient solar hydrogen production by intercalated carbon nitride photocatalyst.

PubMed

Gao, Honglin; Yan, Shicheng; Wang, Jiajia; Huang, Yu An; Wang, Peng; Li, Zhaosheng; Zou, Zhigang

2013-11-07

The development of efficient photocatalytic material for converting solar energy to hydrogen energy as viable alternatives to fossil-fuel technologies is expected to revolutionize energy shortage and environment issues. However, to date, the low quantum yield for solar hydrogen production over photocatalysts has hindered advances in the practical applications of photocatalysis. Here, we show that a carbon nitride intercalation compound (CNIC) synthesized by a simple molten salt route is an efficient polymer photocatalyst with a high quantum yield. We found that coordinating the alkali metals into the C-N plane of carbon nitride will induce the un-uniform spatial charge distribution. The electrons are confined in the intercalated region while the holes are in the far intercalated region, which promoted efficient separation of photogenerated carriers. The donor-type alkali metal ions coordinating into the nitrogen pots of carbon nitrides increase the free carrier concentration and lead to the formation of novel nonradiative paths. This should favor improved transport of the photogenerated electron and hole and decrease the electron-hole recombination rate. As a result, the CNIC exhibits a quantum yield as high as 21.2% under 420 nm light irradiation for solar hydrogen production. Such high quantum yield opens up new opportunities for using cheap semiconducting polymers as energy transducers.

Simulating and mapping the spatial and seasonal effects of future climate and land -use changes on ecosystem services in the Yanhe watershed, China.

PubMed

Chen, Dengshuai; Li, Jing; Zhou, Zixiang; Liu, Yan; Li, Ting; Liu, Jingya

2018-01-01

Effective information about ecosystem services is essential to help optimize and prioritize activities that support conservation planning in the face of land use and climate changes. This study shows an approach that integrates several dissimilar models for assessing water-related ecosystem services to predict values in 2050 under three land use scenarios in the Yanhe watershed. The simulated output variables pertaining to water yield and sediment yield were used as indicators for two ecosystem-regulating services, i.e., water flow regulation and erosion regulation, which were quantified using the soil and water assessment tool (SWAT) model. The model results were translated into a relative ecosystem service valuation scale, which facilitated the analysis of spatial and seasonal changes and served as the basis for the applied mapping approach. The simulated results indicate that higher water-related regulation services were concentrated in the middle and lower reaches of rivers with high water yield and low sediment erosion. The highest water flow regulation services occurred in summer; nevertheless, this was when erosion regulation services were the lowest compared to other periods in 2050. A comparison of the three land use scenarios showed differences in the water-related regulation services. Scenario 1, with high forest coverage, had the highest erosion regulation services, but the water flow regulation services were the lowest. Scenario 3 showed the reverse pattern. Scenario 2 had intermediate water flow regulation and erosion regulation. Increasing vegetation cover in the watershed is conducive to controlling water and soil erosion but could lead to a decline in available water resources. Spatial mapping is a powerful tool for displaying the spatiotemporal differences in the water-related regulation services delivered by ecosystems and can help decision makers optimize land use in the future, with the goal of maximizing the benefits offered by ecological services in the Yanhe watershed.

Higher sensitivity secondary ion mass spectrometry of biological molecules for high resolution, chemically specific imaging.

PubMed

McDonnell, Liam A; Heeren, Ron M A; de Lange, Robert P J; Fletcher, Ian W

2006-09-01

To expand the role of high spatial resolution secondary ion mass spectrometry (SIMS) in biological studies, numerous developments have been reported in recent years for enhancing the molecular ion yield of high mass molecules. These include both surface modification, including matrix-enhanced SIMS and metal-assisted SIMS, and polyatomic primary ions. Using rat brain tissue sections and a bismuth primary ion gun able to produce atomic and polyatomic primary ions, we report here how the sensitivity enhancements provided by these developments are additive. Combined surface modification and polyatomic primary ions provided approximately 15.8 times more signal than using atomic primary ions on the raw sample, whereas surface modification and polyatomic primary ions yield approximately 3.8 and approximately 8.4 times more signal. This higher sensitivity is used to generate chemically specific images of higher mass biomolecules using a single molecular ion peak.

Generation of Bright, Spatially Coherent Soft X-Ray High Harmonics in a Hollow Waveguide Using Two-Color Synthesized Laser Pulses.

PubMed

Jin, Cheng; Stein, Gregory J; Hong, Kyung-Han; Lin, C D

2015-07-24

We investigate the efficient generation of low-divergence high-order harmonics driven by waveform-optimized laser pulses in a gas-filled hollow waveguide. The drive waveform is obtained by synthesizing two-color laser pulses, optimized such that highest harmonic yields are emitted from each atom. Optimization of the gas pressure and waveguide configuration has enabled us to produce bright and spatially coherent harmonics extending from the extreme ultraviolet to soft x rays. Our study on the interplay among waveguide mode, atomic dispersion, and plasma effect uncovers how dynamic phase matching is accomplished and how an optimized waveform is maintained when optimal waveguide parameters (radius and length) and gas pressure are identified. Our analysis should help laboratory development in the generation of high-flux bright coherent soft x rays as tabletop light sources for applications.

Functional group diversity of bee pollinators increases crop yield

PubMed Central

Hoehn, Patrick; Tscharntke, Teja; Tylianakis, Jason M; Steffan-Dewenter, Ingolf

2008-01-01

Niche complementarity is a commonly invoked mechanism underlying the positive relationship between biodiversity and ecosystem functioning, but little empirical evidence exists for complementarity among pollinator species. This study related differences in three functional traits of pollinating bees (flower height preference, daily time of flower visitation and within-flower behaviour) to the seed set of the obligate cross-pollinated pumpkin Cucurbita moschata Duch. ex Poir. across a land-use intensity gradient from tropical rainforest and agroforests to grassland in Indonesia. Bee richness and abundance changed with habitat variables and we used this natural variation to test whether complementary resource use by the diverse pollinator community enhanced final yield. We found that pollinator diversity, but not abundance, was positively related to seed set of pumpkins. Bees showed species-specific spatial and temporal variation in flower visitation traits and within-flower behaviour, allowing for classification into functional guilds. Diversity of functional groups explained even more of the variance in seed set (r2=45%) than did species richness (r2=32%) highlighting the role of functional complementarity. Even though we do not provide experimental, but rather correlative evidence, we can link spatial and temporal complementarity in highly diverse pollinator communities to pollination success in the field, leading to enhanced crop yield without any managed honeybees. PMID:18595841

Analysis on the application of background parameters on remote sensing classification

NASA Astrophysics Data System (ADS)

Qiao, Y.

Drawing accurate crop cultivation acreage, dynamic monitoring of crops growing and yield forecast are some important applications of remote sensing to agriculture. During the 8th 5-Year Plan period, the task of yield estimation using remote sensing technology for the main crops in major production regions in China once was a subtopic to the national research task titled "Study on Application of Remote sensing Technology". In 21 century in a movement launched by Chinese Ministry of Agriculture to combine high technology to farming production, remote sensing has given full play to farm crops' growth monitoring and yield forecast. And later in 2001 Chinese Ministry of Agriculture entrusted the Northern China Center of Agricultural Remote Sensing to forecast yield of some main crops like wheat, maize and rice in rather short time to supply information for the government decision maker. Present paper is a report for this task. It describes the application of background parameters in image recognition, classification and mapping with focuses on plan of the geo-science's theory, ecological feature and its cartographical objects or scale, the study of phrenology for image optimal time for classification of the ground objects, the analysis of optimal waveband composition and the application of background data base to spatial information recognition ;The research based on the knowledge of background parameters is indispensable for improving the accuracy of image classification and mapping quality and won a secondary reward of tech-science achievement from Chinese Ministry of Agriculture. Keywords: Spatial image; Classification; Background parameter

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Relationship between cotton yield and soil electrical conductivity, topography, and landsat imagery

USDA-ARS?s Scientific Manuscript database

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this stu...

Spatially explicit spectral analysis of point clouds and geospatial data

USGS Publications Warehouse

Buscombe, Daniel D.

2015-01-01

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

NASA Astrophysics Data System (ADS)

Zhang, J.; Yang, J.; Pan, S.; Tian, H.

2016-12-01

China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

NASA Astrophysics Data System (ADS)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

The Red Sea structural architecture assessment based on yield strength spatial variations and Arabian margin preexisting structures

NASA Astrophysics Data System (ADS)

Alotaibi, T.; Furlong, K. P.

2016-12-01

Rift initiation and localization might reflect spatial changes in the lithospheric yield strength. However, this does not appear to be the case in the Red Sea extensional system where fission track analysis shows no significant changes in the geothermal gradient prior to the Red Sea rift onset. In contrast, though the whole Red Sea rift initiated 25 Ma ago, its extensional architecture changes dramatically along strike from narrow localized spreading in the south to asymmetrical diffuse extension north of 21° latitude. This onset of diffuse extension has been recorded in the north-western Arabian margin as old as 33 Ma. Such diversity in the extensional style might reflect along strike yield strength variations as a consequence of the geological setting in the Arabian margin. The north-western Arabian basin, which is part of the Arabian margin, bounded by Qiba high from the east, the Arabian shield from the south and the west and Syrian plateau from the north. The basin accommodates part of the Red Sea diffuse extension and has a preexisting structural architecture represented in the Cenozoic failed rift that called Sarhan graben. Our goal is to analyze the current lithospheric yield strength spatial variations along the Red Sea rift and emphasize their relationship with the Arabian margin structural architecture. We hypothesize that the north-western Arabian margin's lithospheric weakness and structural diversity are playing an important role in producing region of diffuse extension by their interaction with the forces applied by far field stresses represented by the New Tethys slab pull. On the other hand, the south-western Arabian margin interacts with the far field stresses as a single strong block in which led to localize the extension in the southern Red Sea. Our work may improve the scientific community understanding for how rifts initiate and evolve over time.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pacold, J. I.; Altman, A. B.; Donald, S B

Materials of interest for nuclear forensic science are often highly heterogeneous, containing complex mixtures of actinide compounds in a wide variety of matrices. Scanning transmission X-ray microscopy (STXM) is ideally suited to study such materials, as it can be used to chemically image specimens by acquiring X-ray absorption near-edge spectroscopy (XANES) data with 25 nm spatial resolution. In particular, STXM in the soft X-ray synchrotron radiation regime (approximately 120 – 2000 eV) can collect spectroscopic information from the actinides and light elements in a single experiment. Thus, STXM combines the chemical sensitivity of X-ray absorption spectroscopy with high spatial resolutionmore » in a single non-destructive characterization method. This report describes the application of STXM to a broad range of nuclear materials. Where possible, the spectroscopic images obtained by STXM are compared with information derived from other analytical methods, and used to make inferences about the process history of each material. STXM measurements can yield information including the morphology of a sample, “elemental maps” showing the spatial distribution of major chemical constituents, and XANES spectra from localized regions of a sample, which may show spatial variations in chemical composition.« less

Decreasing child mortality, spatial clustering and decreasing disparity in North-Western Burkina Faso.

PubMed

Becher, Heiko; Müller, Olaf; Dambach, Peter; Gabrysch, Sabine; Niamba, Louis; Sankoh, Osman; Simboro, Seraphin; Schoeps, Anja; Stieglbauer, Gabriele; Yé, Yazoume; Sié, Ali

2016-04-01

Within relatively small areas, there exist high spatial variations of mortality between villages. In rural Burkina Faso, with data from 1993 to 1998, clusters of particularly high child mortality were identified in the population of the Nouna Health and Demographic Surveillance System (HDSS), a member of the INDEPTH Network. In this paper, we report child mortality with respect to temporal trends, spatial clustering and disparity in this HDSS from 1993 to 2012. Poisson regression was used to describe village-specific child mortality rates and time trends in mortality. The spatial scan statistic was used to identify villages or village clusters with higher child mortality. Clustering of mortality in the area is still present, but not as strong as before. The disparity of child mortality between villages has decreased. The decrease occurred in the context of an overall halving of child mortality in the rural area of Nouna HDSS between 1993 and 2012. Extrapolated to the Millennium Development Goals target period 1990-2015, this yields an estimated reduction of 54%, which is not too far off the aim of a two-thirds reduction. © 2016 John Wiley & Sons Ltd.

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE PAGES

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ...

2017-12-22

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Quantifying yield gaps in wheat production in Russia

NASA Astrophysics Data System (ADS)

Schierhorn, Florian; Faramarzi, Monireh; Prishchepov, Alexander V.; Koch, Friedrich J.; Müller, Daniel

2014-08-01

Crop yields must increase substantially to meet the increasing demands for agricultural products. Crop yield increases are particularly important for Russia because low crop yields prevail across Russia’s widespread and fertile land resources. However, reliable data are lacking regarding the spatial distribution of potential yields in Russia, which can be used to determine yield gaps. We used a crop growth model to determine the yield potentials and yield gaps of winter and spring wheat at the provincial level across European Russia. We modeled the annual yield potentials from 1995 to 2006 with optimal nitrogen supplies for both rainfed and irrigated conditions. Overall, the results suggest yield gaps of 1.51-2.10 t ha-1, or 44-52% of the yield potential under rainfed conditions. Under irrigated conditions, yield gaps of 3.14-3.30 t ha-1, or 62-63% of the yield potential, were observed. However, recurring droughts cause large fluctuations in yield potentials under rainfed conditions, even when the nitrogen supply is optimal, particularly in the highly fertile black soil areas of southern European Russia. The highest yield gaps (up to 4 t ha-1) under irrigated conditions were detected in the steppe areas in southeastern European Russia along the border of Kazakhstan. Improving the nutrient and water supply and using crop breeds that are adapted to the frequent drought conditions are important for reducing yield gaps in European Russia. Our regional assessment helps inform policy and agricultural investors and prioritize research that aims to increase crop production in this important region for global agricultural markets.

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Impacts of multiple global environmental changes on African crop yield and water use efficiency: Implications to food and water security

NASA Astrophysics Data System (ADS)

Pan, S.; Yang, J.; Zhang, J.; Xu, R.; Dangal, S. R. S.; Zhang, B.; Tian, H.

2016-12-01

Africa is one of the most vulnerable regions in the world to climate change and climate variability. Much concern has been raised about the impacts of climate and other environmental factors on water resource and food security through the climate-water-food nexus. Understanding the responses of crop yield and water use efficiency to environmental changes is particularly important because Africa is well known for widespread poverty, slow economic growth and agricultural systems particularly sensitive to frequent and persistent droughts. However, the lack of integrated understanding has limited our ability to quantify and predict the potential of Africa's agricultural sustainability and freshwater supply, and to better manage the system for meeting an increasing food demand in a way that is socially and environmentally or ecologically sustainable. By using the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed the spatial and temporal patterns of crop yield, evapotranspiration (ET) and water use efficiency across entire Africa in the past 35 years (1980-2015) and the rest of the 21st century (2016-2099). Our preliminary results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion (about 50%), elevated atmospheric CO2 concentration, and nitrogen deposition. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Climate extremes especially droughts and heat wave have largely reduced crop yield in the most vulnerable regions. Our results indicate that N fertilizer could be a major driver to improve food security in Africa. Future climate warming could reduce crop yield and shift cropland distribution. Our study further suggests that improving water use efficiency through land management practices including the increased uses of fertilizers and irrigation will be the key for reducing the loss of crop yield in a warming climate and extreme weather.

The Impact of Land Use and Land Cover Change on Water Yield in the Jing- Jin-Ji Region in China

NASA Astrophysics Data System (ADS)

Li, Suxiao; Yang, Hong

2017-04-01

Water yield is one of the key ecosystem services sustaining both people's life and economic development. However, the water yield function is sensitive to anthropogenic activity especially the land use and land cover change (LUCC). Assessment of historical LUCC and its impact on water yield could benefit designing and implementing appropriate land use strategy that enhance the water yield capacity. Beijing (Jing) and its surrounding areas of Tianjin (Jin) and Hebei (Ji) is the political, cultural and economic center of China. The region is facing increasingly water crisis. Taking the Jing-Jin-Ji region as a study area, this study analyzed the historical LUCC and its impact on water yield by using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to spatially map and quantify the changes of water yield from 1995 to 2010. The results showed there was main decline in area of wetland and forest and increase in area of crop land and built up land. An abrupt decline in water yield was found for year 2000. The water yield was influenced to a great extent by precipitation and evapotranspiration, but the land use played an important role in the water yield capacity (water yield per unit area) through plant cover that affected evapotranspiration, soil water permeability and the capacity of holding the moisture content. By general ranking, the water yield capacity of different land use type was as follows: built-up>bare land>cropland> grassland>forest >wetland, which illustrated that the built-up and bare land had higher run off rate while the vegetation area had higher capacity to control surface run off to increase the groundwater. A good understanding of temporal-spatial allocation of historical LUCC and Water yield of the Jing-Jin-Ji region could help guide land use policy decisions that take into consideration of tradeoffs with respect to spatial distribution of ecosystem services amongst the three administrative entities (Jing-Jin-Ji) and tradeoffs between the economic and ecological development.

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

ERIC Educational Resources Information Center

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2011-01-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the…

Simulating maize yield and bomass with spatial variability of soil field capacity

USGS Publications Warehouse

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Improving yield and performance in ZnO thin-film transistors made using selective area deposition.

PubMed

Nelson, Shelby F; Ellinger, Carolyn R; Levy, David H

2015-02-04

We describe improvements in both yield and performance for thin-film transistors (TFTs) fabricated by spatial atomic layer deposition (SALD). These improvements are shown to be critical in forming high-quality devices using selective area deposition (SAD) as the patterning method. Selective area deposition occurs when the precursors for the deposition are prevented from reacting with some areas of the substrate surface. Controlling individual layer quality and the interfaces between layers is essential for obtaining good-quality thin-film transistors and capacitors. The integrity of the gate insulator layer is particularly critical, and we describe a method for forming a multilayer dielectric using an oxygen plasma treatment between layers that improves crossover yield. We also describe a method to achieve improved mobility at the important interface between the semiconductor and the gate insulator by, conversely, avoiding oxygen plasma treatment. Integration of the best designs results in wide design flexibility, transistors with mobility above 15 cm(2)/(V s), and good yield of circuits.

Simulating maize yield and biomass with spatial variability of soil field capacity

USDA-ARS?s Scientific Manuscript database

Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

PubMed Central

Diago, Maria P.; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψs) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction (RP2) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture. PMID:29441086

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy.

PubMed

Diago, Maria P; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψ s ) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction ([Formula: see text]) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

Towards deep brain monitoring with superficial EEG sensors plus neuromodulatory focused ultrasound

PubMed Central

Darvas, F; Mehić, E; Caler, CJ; Ojemann, JG; Mourad, PD

2017-01-01

Noninvasive recordings of electrophysiological activity have limited anatomical specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalogram (EEG) signal induced by pulsed focused ultrasound (pFU) could overcome those limitations. As a first step towards testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200 microsecond-long pulses applied at 1050 Hz for one second at a spatial peak temporal average intensity of 1.4 W/cm2) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050 Hz electrophysiological signal only when ultrasound was applied to living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pFU as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution. PMID:27181686

Infrared absorption spectroscopy and sensing of protein monolayers using high performance enhancing substrates and a mobile phone (Conference Presentation)

NASA Astrophysics Data System (ADS)

Dana, Aykutlu; Ayas, Sencer; Bakan, Gokhan; Ozgur, Erol; Guner, Hasan; Celebi, Kemal

2016-09-01

Infrared absorption spectroscopy has greatly benefited from the electromagnetic field enhancement offered by plasmonic surfaces. However, because of the localized nature of plasmonic fields, such field enhancements are limited to nm-scale volumes. Here, we demonstrate that a relatively small, but spatially-uniform field enhancement can yield a superior infrared detection performance compared to the plasmonic field enhancement exhibited by optimized infrared nanoantennas. A specifically designed CaF2/Al thin film surface is shown to enable observation of stronger vibrational signals from the probe material, with wider bandwidth and a deeper spatial extent of the field enhancement as compared to optimized plasmonic surfaces. It is demonstrated that the surface structure presented here can enable chemically specific and label-free detection of organic monolayers using surface enhanced infrared spectroscopy. Also, a low cost hand held infrared absorption measurement setup is demonstrated using a miniature bolometric sensor and a mobile phone. A specifically designed grating in combination with an IR light source yields an IR spectrometer covering 7-12 um range, with about 100 cm-1 resolution. Combining the enhancing substrates with the spectroscopy setup, low cost, high sensitivity mobile infrared sensing is enabled. The results have implications in homeland security and environmental monitoring as well as chemical analysis.

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

USGS Publications Warehouse

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Low-redundancy linear arrays in mirrored interferometric aperture synthesis.

PubMed

Zhu, Dong; Hu, Fei; Wu, Liang; Li, Jun; Lang, Liang

2016-01-15

Mirrored interferometric aperture synthesis (MIAS) is a novel interferometry that can improve spatial resolution compared with that of conventional IAS. In one-dimensional (1-D) MIAS, antenna array with low redundancy has the potential to achieve a high spatial resolution. This Letter presents a technique for the direct construction of low-redundancy linear arrays (LRLAs) in MIAS and derives two regular analytical patterns that can yield various LRLAs in short computation time. Moreover, for a better estimation of the observed scene, a bi-measurement method is proposed to handle the rank defect associated with the transmatrix of those LRLAs. The results of imaging simulation demonstrate the effectiveness of the proposed method.

Pathways between primary production and fisheries yields of large marine ecosystems.

PubMed

Friedland, Kevin D; Stock, Charles; Drinkwater, Kenneth F; Link, Jason S; Leaf, Robert T; Shank, Burton V; Rose, Julie M; Pilskaln, Cynthia H; Fogarty, Michael J

2012-01-01

The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems.

Pathways between Primary Production and Fisheries Yields of Large Marine Ecosystems

PubMed Central

Friedland, Kevin D.; Stock, Charles; Drinkwater, Kenneth F.; Link, Jason S.; Leaf, Robert T.; Shank, Burton V.; Rose, Julie M.; Pilskaln, Cynthia H.; Fogarty, Michael J.

2012-01-01

The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems. PMID:22276100

African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Folberth, Christian; Balkovič, Juraj; Ciais, Philippe; Fritz, Steffen; Janssens, Ivan A.; Obersteiner, Michael; See, Linda; Skalský, Rastislav; Xiong, Wei; Peñuealas, Josep

2014-05-01

The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N:P applications under low, medium, and high input scenarios, for past (1975), current, and future N:P mass ratios of respectively, 1:0.29, 1:0.15, and 1:0.05. At low N inputs (10 kg/ha), current yield deficits amount to 10% but will increase up to 27% under the assumed future N:P ratio, while at medium N inputs (50 kg N/ha), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N:P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1:0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Precision Viticulture : is it relevant to manage the vineyard according to the within field spatial variability of the environment ?

NASA Astrophysics Data System (ADS)

Tisseyre, Bruno

2015-04-01

For more than 15 years, research projects are conducted in the precision viticulture (PV) area around the world. These research projects have provided new insights into the within-field variability in viticulture. Indeed, access to high spatial resolution data (remote sensing, embedded sensors, etc.) changes the knowledge we have of the fields in viticulture. In particular, the field which was until now considered as a homogeneous management unit, presents actually a high spatial variability in terms of yield, vigour an quality. This knowledge will lead (and is already causing) changes on how to manage the vineyard and the quality of the harvest at the within field scale. From the experimental results obtained in various countries of the world, the goal of the presentation is to provide figures on: - the spatial variability of the main parameters (yield, vigor, quality), and how this variability is organized spatially, - the temporal stability of the observed spatial variability and the potential link with environmental parameters like soil, topography, soil water availability, etc. - information sources available at a high spatial resolution conventionally used in precision agriculture likely to highlight this spatial variability (multi-spectral images, soil electrical conductivity, etc.) and the limitations that these information sources are likely to present in viticulture. Several strategies are currently being developed to take into account the within field variability in viticulture. They are based on the development of specific equipments, sensors, actuators and site specific strategies with the aim of adapting the vineyard operations at the within-field level. These strategies will be presented briefly in two ways : - Site specific operations (fertilization, pruning, thinning, irrigation, etc.) in order to counteract the effects of the environment and to obtain a final product with a controlled and consistent wine quality, - Differential harvesting with the objective to take advantage of the observed spatial variability to produce different quality of wines. These later approach tends to produce very different quality wines which will be blended to control the final quality and/or marketed differently. These applications show that the environment and its spatial variability can be valued with the goal of controlling the final quality of the wine produced. Technologies to characterize the spatial variability of vine fields are currently in rapid evolution. They will significantly impact production methods and management strategies of the vineyard. In its last part, the presentation will summarize the technologies likely to impact the knowledge and the vineyard management either at the field level, at the vineyard level or at the regional level. A brief overview of the needs in terms of information processing will be also performed. A reflection on the difficulties that might limit the adoption of precision viticulture technologies (PV) will be done. Indeed, although very informative, PV entails high costs of information acquisition and data processing. Cost is one of the major obstacles to the dissemination of these tools and services to the majority of wine producers. In this context, the pooling of investments is a choke point to make the VP accessible to the highest number of growers. Thus, to be adopted, the VP will necessarily satisfy the operational requirements at the field level, but also throughout the whole production area (at the regional level). This working scale raises new scientific questions to be addressed.

The role of precipitation type, intensity, and spatial distribution in source water quality after wildfire

NASA Astrophysics Data System (ADS)

Murphy, Sheila F.; Writer, Jeffrey H.; Blaine McCleskey, R.; Martin, Deborah A.

2015-08-01

Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h-1. These storms, which typically occur several times each year in July-September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10-156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.

The role of precipitation type, intensity, and spatial distribution in source water quality after wildfire

USGS Publications Warehouse

Murphy, Sheila F.; Writer, Jeffrey H.; McCleskey, R. Blaine; Martin, Deborah A.

2015-01-01

Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h−1. These storms, which typically occur several times each year in July–September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10–156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.

Split-probe hybrid femtosecond/picosecond rotational CARS for time-domain measurement of S-branch Raman linewidths within a single laser shot.

PubMed

Patterson, Brian D; Gao, Yi; Seeger, Thomas; Kliewer, Christopher J

2013-11-15

We introduce a multiplex technique for the single-laser-shot determination of S-branch Raman linewidths with high accuracy and precision by implementing hybrid femtosecond (fs)/picosecond (ps) rotational coherent anti-Stokes Raman spectroscopy (CARS) with multiple spatially and temporally separated probe beams derived from a single laser pulse. The probe beams scatter from the rotational coherence driven by the fs pump and Stokes pulses at four different probe pulse delay times spanning 360 ps, thereby mapping collisional coherence dephasing in time for the populated rotational levels. The probe beams scatter at different folded BOXCARS angles, yielding spatially separated CARS signals which are collected simultaneously on the charge coupled device camera. The technique yields a single-shot standard deviation (1σ) of less than 3.5% in the determination of Raman linewidths and the average linewidth values obtained for N(2) are within 1% of those previously reported. The presented technique opens the possibility for correcting CARS spectra for time-varying collisional environments in operando.

Localized surface plasmon resonance nanosensor: a high-resolution distance-dependence study using atomic layer deposition.

PubMed

Whitney, Alyson V; Elam, Jeffrey W; Zou, Shengli; Zinovev, Alex V; Stair, Peter C; Schatz, George C; Van Duyne, Richard P

2005-11-03

Atomic layer deposition (ALD) is used to deposit 1-600 monolayers of Al(2)O(3) on Ag nanotriangles fabricated by nanosphere lithography (NSL). Each monolayer of Al(2)O(3) has a thickness of 1.1 A. It is demonstrated that the localized surface plasmon resonance (LSPR) nanosensor can detect Al(2)O(3) film growth with atomic spatial resolution normal to the nanoparticle surface. This is approximately 10 times greater spatial resolution than that in our previous long-range distance-dependence study using multilayer self-assembled monolayer shells. The use of ALD enables the study of both the long- and short-range distance dependence of the LSPR nanosensor in a single unified experiment. Ag nanoparticles with fixed in-plane widths and decreasing heights yield larger sensing distances. X-ray photoelectron spectroscopy, variable angle spectroscopic ellipsometry, and quartz crystal microbalance measurements are used to study the growth mechanism. It is proposed that the growth of Al(2)O(3) is initiated by the decomposition of trimethylaluminum on Ag. Semiquantitative theoretical calculations were compared with the experimental results and yield excellent agreement.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Visibility graphs of random scalar fields and spatial data

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Iacovacci, Jacopo

2017-07-01

We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.

Study of a high-resolution, 3D positioning cadmium zinc telluride detector for PET.

PubMed

Gu, Y; Matteson, J L; Skelton, R T; Deal, A C; Stephan, E A; Duttweiler, F; Gasaway, T M; Levin, C S

2011-03-21

This paper investigates the performance of 1 mm resolution cadmium zinc telluride (CZT) detectors for positron emission tomography (PET) capable of positioning the 3D coordinates of individual 511 keV photon interactions. The detectors comprise 40 mm × 40 mm × 5 mm monolithic CZT crystals that employ a novel cross-strip readout with interspersed steering electrodes to obtain high spatial and energy resolution. The study found a single anode FWHM energy resolution of 3.06 ± 0.39% at 511 keV throughout most of the detector volume. Improved resolution is expected with properly shielded front-end electronics. Measurements made using a collimated beam established the efficacy of the steering electrodes in facilitating enhanced charge collection across anodes, as well as a spatial resolution of 0.44 ± 0.07 mm in the direction orthogonal to the electrode planes. Finally, measurements based on coincidence electronic collimation yielded a point spread function with 0.78 ± 0.10 mm FWHM, demonstrating 1 mm spatial resolution capability transverse to the anodes-as expected from the 1 mm anode pitch. These findings indicate that the CZT-based detector concept has excellent performance and shows great promise for a high-resolution PET system.

Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron Highlands, Pahang, Malaysia

NASA Astrophysics Data System (ADS)

Ghani, A. H. A.; Lihan, T.; Rahim, S. A.; Musthapha, M. A.; Idris, W. M. R.; Rahman, Z. A.

2013-11-01

Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS) environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation type and density, climate and land use within the drainage basin.

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

In-situ device integration of large-area patterned organic nanowire arrays for high-performance optical sensors

PubMed Central

Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng

2013-01-01

Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887

Effects of front-surface target structures on properties of relativistic laser-plasma electrons.

PubMed

Jiang, S; Krygier, A G; Schumacher, D W; Akli, K U; Freeman, R R

2014-01-01

We report the results of a study of the role of prescribed geometrical structures on the front of a target in determining the energy and spatial distribution of relativistic laser-plasma electrons. Our three-dimensional particle-in-cell simulation studies apply to short-pulse, high-intensity laser pulses, and indicate that a judicious choice of target front-surface geometry provides the realistic possibility of greatly enhancing the yield of high-energy electrons while simultaneously confining the emission to narrow (<5°) angular cones.

Spatially Explicit Estimates of Suspended Sediment and Bedload Transport Rates for Western Oregon and Northwestern California

NASA Astrophysics Data System (ADS)

O'Connor, J. E.; Wise, D. R.; Mangano, J.; Jones, K.

2015-12-01

Empirical analyses of suspended sediment and bedload transport gives estimates of sediment flux for western Oregon and northwestern California. The estimates of both bedload and suspended load are from regression models relating measured annual sediment yield to geologic, physiographic, and climatic properties of contributing basins. The best models include generalized geology and either slope or precipitation. The best-fit suspended-sediment model is based on basin geology, precipitation, and area of recent wildfire. It explains 65% of the variance for 68 suspended sediment measurement sites within the model area. Predicted suspended sediment yields range from no yield from the High Cascades geologic province to 200 tonnes/ km2-yr in the northern Oregon Coast Range and 1000 tonnes/km2-yr in recently burned areas of the northern Klamath terrain. Bed-material yield is similarly estimated from a regression model based on 22 sites of measured bed-material transport, mostly from reservoir accumulation analyses but also from several bedload measurement programs. The resulting best-fit regression is based on basin slope and the presence/absence of the Klamath geologic terrane. For the Klamath terrane, bed-material yield is twice that of the other geologic provinces. This model explains more than 80% of the variance of the better-quality measurements. Predicted bed-material yields range up to 350 tonnes/ km2-yr in steep areas of the Klamath terrane. Applying these regressions to small individual watersheds (mean size; 66 km2 for bed-material; 3 km2 for suspended sediment) and cumulating totals down the hydrologic network (but also decreasing the bed-material flux by experimentally determined attrition rates) gives spatially explicit estimates of both bed-material and suspended sediment flux. This enables assessment of several management issues, including the effects of dams on bedload transport, instream gravel mining, habitat formation processes, and water-quality. The combined fluxes can also be compared to long-term rock uplift and cosmogenically determined landscape erosion rates.

Impacts of forest restoration on water yield: A systematic review

PubMed Central

Filoso, Solange; Bezerra, Maíra Ometto; Weiss, Katherine C. B.; Palmer, Margaret A.

2017-01-01

Background Enhancing water provision services is a common target in forest restoration projects worldwide due to growing concerns over freshwater scarcity. However, whether or not forest cover expansion or restoration can improve water provision services is still unclear and highly disputed. Purpose The goal of this review is to provide a balanced and impartial assessment of the impacts of forest restoration and forest cover expansion on water yields as informed by the scientific literature. Potential sources of bias on the results of papers published are also examined. Data sources English, Spanish and Portuguese peer-review articles in Agricola, CAB Abstracts, ISI Web of Science, JSTOR, Google Scholar, and SciELO. Databases were searched through 2015. Search terms Intervention terms included forest restoration, regeneration/regrowth, forest second-growth, forestation/afforestation, and forestry. Target terms included water yield/quantity, streamflow, discharge, channel runoff, and annual flow. Study selection and eligibility criteria Articles were pre-selected based on key words in the title, abstract or text. Eligible articles addressed relevant interventions and targets and included quantitative information. Results Most studies reported decreases in water yields following the intervention, while other hydrological benefits have been observed. However, relatively few studies focused specifically on forest restoration, especially with native species, and/or on projects done at large spatial or temporal scales. Information is especially limited for the humid tropics and subtropics. Conclusions and implications of key findings While most studies reported a decrease in water yields, meta-analyses from a sub-set of studies suggest the potential influence of temporal and/or spatial scales on the outcomes of forest cover expansion or restoration projects. Given the many other benefits of forest restoration, improving our understanding of when and why forest restoration can lead to recovery of water yields is crucial to help improve positive outcomes and prevent unintended consequences. Our study identifies the critical types of studies and associated measurements needed. PMID:28817639

Relationships between hand laterality and verbal and spatial skills in 436 healthy adults balanced for handedness.

PubMed

Mellet, E; Jobard, G; Zago, L; Crivello, F; Petit, L; Joliot, M; Mazoyer, B; Tzourio-Mazoyer, N

2014-01-01

The relationship between manual laterality and cognitive skills remains highly controversial. Some studies have reported that strongly lateralised participants had higher cognitive performance in verbal and visuo-spatial domains compared to non-lateralised participants; however, others found the opposite. Moreover, some have suggested that familial sinistrality and sex might interact with individual laterality factors to alter cognitive skills. The present study addressed these issues in 237 right-handed and 199 left-handed individuals. Performance tests covered various aspects of verbal and spatial cognition. A principal component analysis yielded two verbal and one spatial factor scores. Participant laterality assessments included handedness, manual preference strength, asymmetry of motor performance, and familial sinistrality. Age, sex, education level, and brain volume were also considered. No effect of handedness was found, but the mean factor scores in verbal and spatial domains increased with right asymmetry in motor performance. Performance was reduced in participants with a familial history of left-handedness combined with a non-maximal preference strength in the dominant hand. These results elucidated some discrepancies among previous findings in laterality factors and cognitive skills. Laterality factors had small effects compared to the adverse effects of age for spatial cognition and verbal memory, the positive effects of education for all three domains, and the effect of sex for spatial cognition.

Automatic enhancement of skin fluorescence localization due to refractive index matching

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2004-07-01

Fluorescence diagnostic techniques are notable amongst many other optical methods, as they offer high sensitivity and non-invasive measurements of tissue properties. However, a combination of multiple scattering and physical heterogeneity of biological tissues hampers the interpretation of the fluorescence measurements. The analyses of the spatial distribution of endogenous and exogenous fluorophores excitations within tissues and their contribution to the detected signal localization are essential for many applications. We have developed a novel Monte Carlo technique that gives a graphical perception of how the excitation and fluorescence detected signal are localized in tissues. Our model takes into account spatial distribution of fluorophores and their quantum yields. We demonstrate that matching of the refractive indices of ambient medium and topical skin layer improves spatial localization of the detected fluorescence signal within the tissue. This result is consistent with the recent conclusion that administering biocompatible agents results in higher image contrast.

Effective intracortical microstimulation parameters applied to primary motor cortex for evoking forelimb movements to stable spatial end points

PubMed Central

Van Acker, Gustaf M.; Amundsen, Sommer L.; Messamore, William G.; Zhang, Hongyu Y.; Luchies, Carl W.; Kovac, Anthony

2013-01-01

High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) applied to motor cortex is recognized as a useful and informative method for corticomotor mapping by evoking natural-appearing movements of the limb to consistent stable end-point positions. An important feature of these movements is that stimulation of a specific site in motor cortex evokes movement to the same spatial end point regardless of the starting position of the limb. The goal of this study was to delineate effective stimulus parameters for evoking forelimb movements to stable spatial end points from HFLD-ICMS applied to primary motor cortex (M1) in awake monkeys. We investigated stimulation of M1 as combinations of frequency (30–400 Hz), amplitude (30–200 μA), and duration (0.5–2 s) while concurrently recording electromyographic (EMG) activity from 24 forelimb muscles and movement kinematics with a motion capture system. Our results suggest a range of parameters (80–140 Hz, 80–140 μA, and 1,000-ms train duration) that are effective and safe for evoking forelimb translocation with subsequent stabilization at a spatial end point. The mean time for stimulation to elicit successful movement of the forelimb to a stable spatial end point was 475.8 ± 170.9 ms. Median successful frequency and amplitude were 110 Hz and 110 μA, respectively. Attenuated parameters resulted in inconsistent, truncated, or undetectable movements, while intensified parameters yielded no change to movement end points and increased potential for large-scale physiological spread and adverse focal motor effects. Establishing cortical stimulation parameters yielding consistent forelimb movements to stable spatial end points forms the basis for a systematic and comprehensive mapping of M1 in terms of evoked movements and associated muscle synergies. Additionally, the results increase our understanding of how the central nervous system may encode movement. PMID:23741044

High resolution phoswich gamma-ray imager utilizing monolithic MPPC arrays with submillimeter pixelized crystals

NASA Astrophysics Data System (ADS)

Kato, T.; Kataoka, J.; Nakamori, T.; Kishimoto, A.; Yamamoto, S.; Sato, K.; Ishikawa, Y.; Yamamura, K.; Kawabata, N.; Ikeda, H.; Kamada, K.

2013-05-01

We report the development of a high spatial resolution tweezers-type coincidence gamma-ray camera for medical imaging. This application consists of large-area monolithic Multi-Pixel Photon Counters (MPPCs) and submillimeter pixelized scintillator matrices. The MPPC array has 4 × 4 channels with a three-side buttable, very compact package. For typical operational gain of 7.5 × 105 at + 20 °C, gain fluctuation over the entire MPPC device is only ± 5.6%, and dark count rates (as measured at the 1 p.e. level) amount to <= 400 kcps per channel. We selected Ce-doped (Lu,Y)2(SiO4)O (Ce:LYSO) and a brand-new scintillator, Ce-doped Gd3Al2Ga3O12 (Ce:GAGG) due to their high light yield and density. To improve the spatial resolution, these scintillators were fabricated into 15 × 15 matrices of 0.5 × 0.5 mm2 pixels. The Ce:LYSO and Ce:GAGG scintillator matrices were assembled into phosphor sandwich (phoswich) detectors, and then coupled to the MPPC array along with an acrylic light guide measuring 1 mm thick, and with summing operational amplifiers that compile the signals into four position-encoded analog outputs being used for signal readout. Spatial resolution of 1.1 mm was achieved with the coincidence imaging system using a 22Na point source. These results suggest that the gamma-ray imagers offer excellent potential for applications in high spatial medical imaging.

A synchrotron radiation microtomography system for the analysis of trabecular bone samples.

PubMed

Salomé, M; Peyrin, F; Cloetens, P; Odet, C; Laval-Jeantet, A M; Baruchel, J; Spanne, P

1999-10-01

X-ray computed microtomography is particularly well suited for studying trabecular bone architecture, which requires three-dimensional (3-D) images with high spatial resolution. For this purpose, we describe a three-dimensional computed microtomography (microCT) system using synchrotron radiation, developed at ESRF. Since synchrotron radiation provides a monochromatic and high photon flux x-ray beam, it allows high resolution and a high signal-to-noise ratio imaging. The principle of the system is based on truly three-dimensional parallel tomographic acquisition. It uses a two-dimensional (2-D) CCD-based detector to record 2-D radiographs of the transmitted beam through the sample under different angles of view. The 3-D tomographic reconstruction, performed by an exact 3-D filtered backprojection algorithm, yields 3-D images with cubic voxels. The spatial resolution of the detector was experimentally measured. For the application to bone investigation, the voxel size was set to 6.65 microm, and the experimental spatial resolution was found to be 11 microm. The reconstructed linear attenuation coefficient was calibrated from hydroxyapatite phantoms. Image processing tools are being developed to extract structural parameters quantifying trabecular bone architecture from the 3-D microCT images. First results on human trabecular bone samples are presented.

Water resources of the Black Sea Basin at high spatial and temporal resolution

NASA Astrophysics Data System (ADS)

Rouholahnejad, Elham; Abbaspour, Karim C.; Srinivasan, Raghvan; Bacu, Victor; Lehmann, Anthony

2014-07-01

The pressure on water resources, deteriorating water quality, and uncertainties associated with the climate change create an environment of conflict in large and complex river system. The Black Sea Basin (BSB), in particular, suffers from ecological unsustainability and inadequate resource management leading to severe environmental, social, and economical problems. To better tackle the future challenges, we used the Soil and Water Assessment Tool (SWAT) to model the hydrology of the BSB coupling water quantity, water quality, and crop yield components. The hydrological model of the BSB was calibrated and validated considering sensitivity and uncertainty analysis. River discharges, nitrate loads, and crop yields were used to calibrate the model. Employing grid technology improved calibration computation time by more than an order of magnitude. We calculated components of water resources such as river discharge, infiltration, aquifer recharge, soil moisture, and actual and potential evapotranspiration. Furthermore, available water resources were calculated at subbasin spatial and monthly temporal levels. Within this framework, a comprehensive database of the BSB was created to fill the existing gaps in water resources data in the region. In this paper, we discuss the challenges of building a large-scale model in fine spatial and temporal detail. This study provides the basis for further research on the impacts of climate and land use change on water resources in the BSB.

Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: Insights into spatial variability using high-resolution satellite data

PubMed Central

Alexeeff, Stacey E.; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A.

2016-01-01

Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1km x 1km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R2 yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with greater than 0.9 out-of-sample R2 yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the standard errors. Land use regression models performed better in chronic effects simulations. These results can help researchers when interpreting health effect estimates in these types of studies. PMID:24896768

Detection of trace nitric oxide concentrations using 1-D laser-induced fluorescence imaging

NASA Astrophysics Data System (ADS)

Yoo, J.; Lee, T.; Jeffries, J. B.; Hanson, R. K.

2008-06-01

Spectrally resolved laser-induced fluorescence (LIF) with one-dimensional spatial imaging was investigated as a technique for detection of trace concentrations of nitric oxide (NO) in high-pressure flames. Experiments were performed in the burnt gases of premixed methane/argon/oxygen flames with seeded NO (15 to 50 ppm), pressures of 10 to 60 bar, and an equivalence ratio of 0.9. LIF signals were dispersed with a spectrometer and recorded on a 2-D intensified CCD array yielding both spectral resolution and 1-D spatial resolution. This method allows isolation of NO-LIF from interference signals due to alternative species (mainly hot O2 and CO2) while providing spatial resolution along the line of the excitation laser. A fast data analysis strategy was developed to enable pulse-by-pulse NO concentration measurements from these images. Statistical analyses as a function of laser energy of these single-shot data were used to determine the detection limits for NO concentration as well as the measurement precision. Extrapolating these results to pulse energies of ˜ 16 mJ/pulse yielded a predicted detection limit of ˜ 10 ppm for pressures up to 60 bar. Quantitative 1-D LIF measurements were performed in CH4/air flames to validate capability for detection of nascent NO in flames at 10-60 bar.

3D Rheological Modeling of NW Intraplate Europe, Deciphering Spatial Integrated strength patterns, Mechanical Strong Layering and EET

NASA Astrophysics Data System (ADS)

Beekman, F.; Hardebol, N.; Cloetingh, S.; Tesauro, M.

2006-12-01

Better understanding of 3D rheological heterogeneity of the European Lithosphere provide the key to tie the recorded intraplate deformation pattern to stress fields transmitted into plate interior from plate boundary forces. The first order strain patterns result from stresses transmitted through the European lithosphere that is marked by a patchwork of high strength variability from inherited structural and compositional heterogeneities and upper mantle thermal perturbations. As the lithospheric rheology depends primarily on its spatial structure, composition and thermal estate, the 3D strength model for the European lithosphere relies on a 3D compositional model that yields the compositional heterogeneities and an iteratively calculated thermal cube using Fouriers law for heat conduction. The accurate appraisal of spatial strength variability results from proper mapping and integration of the geophysical compositional and thermal input parameters. Therefore, much attention has been paid to a proper description of first order structural and tectonic features that facilitate compilation of the compositional and thermal input models. As such, the 3D strength model reflects the thermo-mechanical structure inherited from the Europeans polyphase deformation history. Major 3D spatial mechanical strength variability has been revealed. The East-European and Fennoscandian Craton to the NE exhibit high strength (30-50 1012 N/m) from low mantle temperatures and surface heatflow of 35-60 mW/m2 while central and western Europe reflect a polyphase Phanerozoic thermo- tectonic history. Here, regions with high rigidity are formed primarily by patches of thermally stabilized Variscan Massifs (e.g. Rhenish, Armorican, Bohemian, and Iberian Massif) with low heatflow and lithospheric thickness values (50-65 mW/m2; 110-150 km) yielding strengths of ~15-25 1012 N/m. In contrast, major axis of weakened lithosphere coincides with Cenozoic Rift System (e.g. Upper and Lower Rhine Grabens, Pannonian Basin and Massif Central) attributed to the presence of tomographically imaged plumes. This study has elucidated the memory of the present-days Europeans lithosphere induced by compositional and thermal heterogeneities. The resulting lateral strength variations has a clear signature of the pst lithospheres polyphase deformation and also entails active tectonics, tectonically induced topography and surface processes.

Nitrogen and phosphorus fluxes from watersheds of the northeast U.S. from 1930 to 2000: Role of anthropogenic nutrient inputs, infrastructure, and runoff

NASA Astrophysics Data System (ADS)

Hale, Rebecca L.; Grimm, Nancy B.; Vörösmarty, Charles J.; Fekete, Balazs

2015-03-01

An ongoing challenge for society is to harness the benefits of nutrients, nitrogen (N) and phosphorus (P), while minimizing their negative effects on ecosystems. While there is a good understanding of the mechanisms of nutrient delivery at small scales, it is unknown how nutrient transport and processing scale up to larger watersheds and whole regions over long time periods. We used a model that incorporates nutrient inputs to watersheds, hydrology, and infrastructure (sewers, wastewater treatment plants, and reservoirs) to reconstruct historic nutrient yields for the northeastern U.S. from 1930 to 2002. Over the study period, yields of nutrients increased significantly from some watersheds and decreased in others. As a result, at the regional scale, the total yield of N and P from the region did not change significantly. Temporal variation in regional N and P yields was correlated with runoff coefficient, but not with nutrient inputs. Spatial patterns of N and P yields were best predicted by nutrient inputs, but the correlation between inputs and yields across watersheds decreased over the study period. The effect of infrastructure on yields was minimal relative to the importance of soils and rivers. However, infrastructure appeared to alter the relationships between inputs and yields. The role of infrastructure changed over time and was important in creating spatial and temporal heterogeneity in nutrient input-yield relationships.

High throughput dual-wavelength temperature distribution imaging via compressive imaging

NASA Astrophysics Data System (ADS)

Yao, Xu-Ri; Lan, Ruo-Ming; Liu, Xue-Feng; Zhu, Ge; Zheng, Fu; Yu, Wen-Kai; Zhai, Guang-Jie

2018-03-01

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

The impact exploration of agricultural drought on winter wheat yield in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui

2017-04-01

Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive correlation (p<0.01), which may provide a way to quantitatively evaluate the winter wheat yield losses caused by drought. Key words: drought, winter wheat yield, SPEI, EPIC, the North China Plain

Ultrafast fluorescence imaging in vivo with conjugated polymer fluorophores in the second near-infrared window

NASA Astrophysics Data System (ADS)

Hong, Guosong; Zou, Yingping; Antaris, Alexander L.; Diao, Shuo; Wu, Di; Cheng, Kai; Zhang, Xiaodong; Chen, Changxin; Liu, Bo; He, Yuehui; Wu, Justin Z.; Yuan, Jun; Zhang, Bo; Tao, Zhimin; Fukunaga, Chihiro; Dai, Hongjie

2014-06-01

In vivo fluorescence imaging in the second near-infrared window (1.0-1.7 μm) can afford deep tissue penetration and high spatial resolution, owing to the reduced scattering of long-wavelength photons. Here we synthesize a series of low-bandgap donor/acceptor copolymers with tunable emission wavelengths of 1,050-1,350 nm in this window. Non-covalent functionalization with phospholipid-polyethylene glycol results in water-soluble and biocompatible polymeric nanoparticles, allowing for live cell molecular imaging at >1,000 nm with polymer fluorophores for the first time. Importantly, the high quantum yield of the polymer allows for in vivo, deep-tissue and ultrafast imaging of mouse arterial blood flow with an unprecedented frame rate of >25 frames per second. The high time-resolution results in spatially and time resolved imaging of the blood flow pattern in cardiogram waveform over a single cardiac cycle (~200 ms) of a mouse, which has not been observed with fluorescence imaging in this window before.

High-power diode lasers for optical communications applications

NASA Technical Reports Server (NTRS)

Carlin, D. B.; Goldstein, B.; Channin, D. J.

1985-01-01

High-power, single-mode, double-heterojunction AlGaAs diode lasers are being developed to meet source requirements for both fiber optic local area network and free space communications systems. An individual device, based on the channeled-substrate-planar (CSP) structure, has yielded single spatial and longitudinal mode outputs of up to 90 mW CW, and has maintained a single spatial mode to 150 mW CW. Phase-locked arrays of closely spaced index-guided lasers have been designed and fabricated with the aim of multiplying the outputs of the individual devices to even higher power levels in a stable, single-lobe, anastigmatic beam. The optical modes of the lasers in such arrays can couple together in such a way that they appear to be emanating from a single source, and can therefore be efficiently coupled into optical communications systems. This paper will review the state of high-power laser technology and discuss the communication system implications of these devices.

Application of the Modified Compaction Material Model to the Analysis of Landmine Detonation in Soil with Various Degrees of Water Saturation

DTIC Science & Technology

2007-01-01

Equation of State R2 – Constant in JWL Equation of State σ – Yield Stress T – Temperature...v – Specific volume w – Constant in JWL Equation of State x – Spatial coordinate y – Spatial coordinate Y – Yield stress Subscripts Comp – Value at...Constant in JWL Equation of State α – Porosity B – Compaction Modulus B1 – Strain Hardening Constant B2 – Constant in JWL Equation of State

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

Development of a Compact Neutron Generator to be Used For Associated Particle Imaging Utilizing a RF-Driven Ion Source

NASA Astrophysics Data System (ADS)

Wu, Ying

2009-11-01

The development of a prototype compact neutron generator for the application of associated particle imaging (API) to be used for explosive and contraband detection will be presented. The API technique makes use of the 3.5 MeV alpha particles that are produced simultaneously with the 14 MeV neutrons in the deuterium-tritium (^2D(^3T,n)^4α) fusion reaction to determine the direction of the neutrons and reduce background noise. This method determines the spatial position of each neutron interaction and requires the neutrons to be generated from a small spot in order to achieve high spatial resolution. In this work an axial type neutron generator was designed and built with a predicted neutron yield of 10^8 n/s for a 50 μA D/T ion beam current accelerated to 80 kV. It was shown that the measured yield for a D/D gas filled generator was 2x10^5n/s, which scales to 2x10^7 n/s if a D/T gas fill is used. The generator utilizes an RF planar spiral antenna at 13.56 MHz to create a highly efficient inductively coupled plasma at the ion source. Experimental results show that beams with an atomic ion fraction of > 80% can be obtained with only 100 watts of RF power in the ion source. A single acceleration gap with a secondary electron suppression electrode is used in the acceleration column, to suppress secondary backscattered electrons produced at the target. Initial measurements of the neutron generator performance including the beam spot size and neutron yield under sealed operation will be discussed, along with suggestions for future improvements.

Spatial sensitivity of grassland yields to weather variations in Austria and its implications for the future☆

PubMed Central

Neuwirth, Christian; Hofer, Barbara

2013-01-01

Agricultural production fulfills economic, ecological and structural functions. Despite technological advances, agricultural production remains sensitive to climate variations. In central Europe, climate change is predicted to bring more rainfall in winter, less rainfall in summer, and increased drought risk among other effects. Grassland agriculture, which is the dominant land use in Alpine regions, may be significantly affected by these climatic changes in the future. Motivated by this issue, the susceptibility of grassland yields to weather variations in Austria is empirical evaluated as a case study. The major objective of this study is to derive spatially distributed indications for climate change exposure by assessing the impacts of weather variations on past yield. It is assumed that reduced water supply during summer constitutes a threat to grassland productivity in regions that are warmer and drier already today. On the contrary, increased spring temperatures may improve grassland productivity in cooler regions like Alpine valleys, since the earlier snow melt leads to an extension of the growth period. Regression analyses are used for evaluating the relation between yearly yields and spring temperatures or water supply in summer, respectively. Water supply is thereby expressed by aggregated precipitation sums and the Climatic Water Balance (CWB). Input data are a meteorological time series as well as yearly yields available for 25 years between 1970 and 2010 and 99 districts in Austria. Yearly yields show a significant (P < 0.05) and positive dependency on water supply in summer for the eastern Austrian lowlands. The combination of temperature in spring and CWB in summer is only significant for six districts in the east of Austria. The positive impact of higher spring temperatures could not be verified. Generally, the regression coefficients are not very high, which indicates that temperature and water supply do not fully describe grassland productivity. Projected climate change may increasingly constitute a risk to yield reliability in the east of the country. That in turn, requires consideration in agricultural development plans and a quantification of these impacts from a social-economic perspective. PMID:25843990

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

[Spatial-temporal variations of spring maize potential yields in a changing climate in Northeast China.

PubMed

Liu, Zhi Juan; Yang, Xiao Guang; Lyu, Shuo; Wang, Jing; Lin, Xiao Mao

2018-01-01

Based on meteorological data, agro-meteorological observations, and agricultural statistical data in Northeast China (NEC), by using the validated Agricultural Production System sIMulator (APSIM-maize), the potential, attainable, potential farmers' and actual farmers' yields of spring maize during the period 1961 to 2015 were analyzed, and the effects of climate variation on maize potential yield in NEC were quantified. Results indicated that the potential yield of spring maize was 12.2 t·hm -2 during the period 1961 to 2015, with those in northeast being lower than southwest within the study region. The attainable yield of spring maize was 11.3 t·hm -2 , and showed a similar spatial distribution with potential yield. Under the current farmers' management practices, mean simulated potential and actual farmers' yields were 6.5 and 4.5 t·hm -2 , respectively. Assuming there were no changes in cultivars and management practices in NEC, the mean potential, attainable, and potential farmers' yields of spring maize would decrease by 0.34, 0.25 and 0.10 t·hm -2 per decade in NEC. However, the actual farmers' yields increased with the value of 1.27 t·hm -2 per decade averaged over NEC. Due to climate variation, year-to-year variations of spring maize potential, attainable, and potential farmers' yields were significant, ranging from 10.0 to 14.4, 9.8 to 13.3, 4.4 to 8.5 t·hm -2 , respectively.

Conceptual model of sediment processes in the upper Yuba River watershed, Sierra Nevada, CA

USGS Publications Warehouse

Curtis, J.A.; Flint, L.E.; Alpers, Charles N.; Yarnell, S.M.

2005-01-01

This study examines the development of a conceptual model of sediment processes in the upper Yuba River watershed; and we hypothesize how components of the conceptual model may be spatially distributed using a geographical information system (GIS). The conceptual model illustrates key processes controlling sediment dynamics in the upper Yuba River watershed and was tested and revised using field measurements, aerial photography, and low elevation videography. Field reconnaissance included mass wasting and channel storage inventories, assessment of annual channel change in upland tributaries, and evaluation of the relative importance of sediment sources and transport processes. Hillslope erosion rates throughout the study area are relatively low when compared to more rapidly eroding landscapes such as the Pacific Northwest and notable hillslope sediment sources include highly erodible andesitic mudflows, serpentinized ultramafics, and unvegetated hydraulic mine pits. Mass wasting dominates surface erosion on the hillslopes; however, erosion of stored channel sediment is the primary contributor to annual sediment yield. We used GIS to spatially distribute the components of the conceptual model and created hillslope erosion potential and channel storage models. The GIS models exemplify the conceptual model in that landscapes with low potential evapotranspiration, sparse vegetation, steep slopes, erodible geology and soils, and high road densities display the greatest hillslope erosion potential and channel storage increases with increasing stream order. In-channel storage in upland tributaries impacted by hydraulic mining is an exception. Reworking of stored hydraulic mining sediment in low-order tributaries continues to elevate upper Yuba River sediment yields. Finally, we propose that spatially distributing the components of a conceptual model in a GIS framework provides a guide for developing more detailed sediment budgets or numerical models making it an inexpensive way to develop a roadmap for understanding sediment dynamics at a watershed scale.

Influence of Scale Effect and Model Performance in Downscaling ASTER Land Surface Temperatures to a Very High Spatial Resolution in an Agricultural Area

NASA Astrophysics Data System (ADS)

Zhou, J.; Li, G.; Liu, S.; Zhan, W.; Zhang, X.

2015-12-01

At present land surface temperatures (LSTs) can be generated from thermal infrared remote sensing with spatial resolutions from ~100 m to tens of kilometers. However, LSTs with high spatial resolution, e.g. tens of meters, are still lack. The purpose of LST downscaling is to generate LSTs with finer spatial resolutions than their native spatial resolutions. The statistical linear or nonlinear regression models are most frequently used for LST downscaling. The basic assumption of these models is the scale-invariant relationships between LST and its descriptors, which is questioned but rare researches have been reported. In addition, few researches can be found for downscaling satellite LST or TIR data to a high spatial resolution, i.e. better than 100 m or even finer. The lack of LST with high spatial resolution cannot satisfy the requirements of applications such as evapotranspiration mapping at the field scale. By selecting a dynamically developing agricultural oasis as the study area, the aim of this study is to downscale the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSTs to 15 m, to satisfy the requirement of evapotranspiration mapping at the field scale. Twelve ASTER images from May to September in 2012, covering the entire growth stage of maize, were selected. Four statistical models were evaluated, including one global model, one piecewise model, and two local models. The influence from scale effect in downscaling LST was quantified. The downscaled LSTs are evaluated from accuracy and image quality. Results demonstrate that the influence from scale effect varies according to models and the maize growth stage. Significant influence about -4 K to 6 K existed at the early stage and weaker influence existed in the middle stage. When compared with the ground measured LSTs, the downscaled LSTs resulted from the global and local models yielded higher accuracies and better image qualities than the local models. In addition to the vegetation indices, the surface albedo is an important descriptor for downscaling LST through explaining its spatial variation induced by soil moisture.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

PubMed

Liu, Wenfeng; Yang, Hong; Liu, Junguo; Azevedo, Ligia B; Wang, Xiuying; Xu, Zongxue; Abbaspour, Karim C; Schulin, Rainer

2016-12-01

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr -1 . Two thirds of these, or 29TgNyr -1 , are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

Treesearch

Assefa S. Desta

2006-01-01

A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

Very high resolution UV and X-ray spectroscopy and imagery of solar active regions

NASA Technical Reports Server (NTRS)

Bruner, M.; Brown, W. A.; Haisch, B. M.

1987-01-01

A scientific investigation of the physics of the solar atmosphere, which uses the techniques of high resolution soft X-ray spectroscopy and high resolution UV imagery, is described. The experiments were conducted during a series of three sounding rocket flights. All three flights yielded excellent images in the UV range, showing unprecedented spatial resolution. The second flight recorded the X-ray spectrum of a solar flare, and the third that of an active region. A normal incidence multi-layer mirror was used during the third flight to make the first astronomical X-ray observations using this new technique.

Rice yield in response to climate trends and drought index in the Mun River Basin, Thailand.

PubMed

Prabnakorn, Saowanit; Maskey, Shreedhar; Suryadi, F X; de Fraiture, Charlotte

2018-04-15

Rice yields in Thailand are among the lowest in Asia. In northeast Thailand where about 90% of rice cultivation is rain-fed, climate variability and change affect rice yields. Understanding climate characteristics and their impacts on the rice yield is important for establishing proper adaptation and mitigation measures to enhance productivity. In this paper, we investigate climatic conditions of the past 30years (1984-2013) and assess the impacts of the recent climate trends on rice yields in the Mun River Basin in northeast Thailand. We also analyze the relationship between rice yield and a drought indicator (Standardized Precipitation and Evapotranspiration Index, SPEI), and the impact of SPEI trends on the yield. Our results indicate that the total yield losses due to past climate trends are rather low, in the range of <50kg/ha per decade (3% of actual average yields). In general, increasing trends in minimum and maximum temperatures lead to modest yield losses. In contrast, precipitation and SPEI-1, i.e. SPEI based on one monthly data, show positive correlations with yields in all months, except in the wettest month (September). If increasing trends of temperatures during the growing season persist, a likely climate change scenario, there is high possibility that the yield losses will become more serious in future. In this paper, we show that the drought index SPEI-1 detects soil moisture deficiency and crop stress in rice better than precipitation or precipitation based indicators. Further, our results emphasize the importance of spatial and temporal resolutions in detecting climate trends and impacts on yields. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparing two tools for ecosystem service assessments regarding water resources decisions.

PubMed

Dennedy-Frank, P James; Muenich, Rebecca Logsdon; Chaubey, Indrajeet; Ziv, Guy

2016-07-15

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fourier removal of stripe artifacts in IRAS images

NASA Technical Reports Server (NTRS)

Van Buren, Dave

1987-01-01

By working in the Fourier plane, approximate removal of stripe artifacts in IRAS images can be effected. The image of interest is smoothed and subtracted from the original, giving the high-spatial-frequency part. This 'filtered' image is then clipped to remove point sources and then Fourier transformed. Subtracting the Fourier components contributing to the stripes in this image from the Fourier transform of the original and transforming back to the image plane yields substantial removal of the stripes.

Computational Modeling of the Spatial Distribution and Temporal Decay of Geomagnetically Trapped Debris of a High Altitude Nuclear Detonation

DTIC Science & Technology

2007-06-01

effects of the magnetic bubble on the dispersion and trapping efficiency of the particles is studied and reported. 15. NUMBER OF PAGES 263 14...efficiency of the particles is studied and reported. vi THIS PAGE INTENTIONALLY LEFT BLANK vii TABLE OF CONTENTS I. INTRODUCTION...single and much lower yield nuclear weapons at many different altitudes. The conclusion of our study and research at USSTRATCOM was that a modeling

Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

NASA Astrophysics Data System (ADS)

Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

2017-12-01

Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

Soil erosion and sediment delivery in a mountain catchment under scenarios of land use change using a spatially distributed numerical model

NASA Astrophysics Data System (ADS)

Alatorre, L. C.; Beguería, S.; Lana-Renault, N.; Navas, A.; García-Ruiz, J. M.

2012-05-01

Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are of great interest to assess the expected effect of LULC changes on soil erosion and sediment yield. However, they can only be applied if spatially distributed data is available for their calibration. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small (2.84 km2) experimental catchment in the Central Spanish Pyrenees. Model calibration was performed based on a dataset of soil redistribution rates derived from point 137Cs inventories, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space, which was not possible to attain if only external (not spatially distributed) sediment yield data were available. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios were then modeled to reproduce land use at the beginning of the twentieth century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr-1) and sediment delivery (11.2 to 1.2 Mg yr-1 ha-1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation recolonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

NASA Astrophysics Data System (ADS)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar application rate.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

NASA Technical Reports Server (NTRS)

Hammerling, Dorit M.; Michalak, Anna M.; Kawa, S. Randolph

2012-01-01

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

Skiff-based Sonar/LiDAR Survey to Calibrate Reservoir Volumes for Watershed Sediment Yield Studies: Carmel River Example

NASA Astrophysics Data System (ADS)

Smith, D. P.; Kvitek, R.; Quan, S.; Iampietro, P.; Paddock, E.; Richmond, S. F.; Gomez, K.; Aiello, I. W.; Consulo, P.

2009-12-01

Models of watershed sediment yield are complicated by spatial and temporal variability of geologic substrate, land cover, and precipitation parameters. Episodic events such as ENSO cycles and severe wildfire are frequent enough to matter in the long-term average yield, and they can produce short-lived, extreme geomorphic responses. The sediment yield from extreme events is difficult to accurately capture because of the obvious dangers associated with field measurements during flood conditions, but it is critical to include extreme values for developing realistic models of rainfall-sediment yield relations, and for calculating long term average denudation rates. Dammed rivers provide a time-honored natural laboratory for quantifying average annual sediment yield and extreme-event sediment yield. While lead-line surveys of the past provided crude estimates of reservoir sediment trapping, recent advances in geospatial technology now provide unprecedented opportunities to improve volume change measurements. High-precision digital elevation models surveyed on an annual basis, or before-and-after specific rainfall-runoff events can be used to quantify relations between rainfall and sediment yield as a function of landscape parameters, including spatially explicit fire intensity. The Basin-Complex Fire of June and July 2008 resulted in moderate to severe burns in the 114 km^2 portion of the Carmel River watershed above Los Padres Dam. The US Geological Survey produced a debris flow probability/volume model for the region indicating that the reservoir could lose considerable capacity if intense enough precipitation occurred in the 2009-10 winter. Loss of Los Padres reservoir capacity has implications for endangered steelhead and red-legged frogs, and groundwater on municipal water supply. In anticipation of potentially catastrophic erosion, we produced an accurate volume calculation of the Los Padres reservoir in fall 2009, and locally monitored hillslope and fluvial processes during winter months. The pre-runoff reservoir volume was developed by collecting and merging sonar and LiDAR data from a small research skiff equipped with a high-precision positioning and attitude-correcting system. The terrestrial LiDAR data were augmented with shore-based total station positioning. Watershed monitoring included benchmarked serial stream surveys and semi-quantitative assessment of a variety of near-channel colluvial processes. Rainfall in the 2009-10 water year was not intense enough to trigger widespread debris flows of slope failure in the burned watershed, but dry ravel was apparently accelerated. The geomorphic analysis showed that sediment yield was not significantly higher during this low-rainfall year, despite the wide-spread presence of very steep, fire-impacted slopes. Because there was little to no increase in sediment yield this year, we have postponed our second reservoir survey. A predicted ENSO event that might bring very intense rains to the watershed is currently predicted for winter 2009-10.

Highly charged ion secondary ion mass spectroscopy

DOEpatents

Hamza, Alex V.; Schenkel, Thomas; Barnes, Alan V.; Schneider, Dieter H.

2001-01-01

A secondary ion mass spectrometer using slow, highly charged ions produced in an electron beam ion trap permits ultra-sensitive surface analysis and high spatial resolution simultaneously. The spectrometer comprises an ion source producing a primary ion beam of highly charged ions that are directed at a target surface, a mass analyzer, and a microchannel plate detector of secondary ions that are sputtered from the target surface after interaction with the primary beam. The unusually high secondary ion yield permits the use of coincidence counting, in which the secondary ion stops are detected in coincidence with a particular secondary ion. The association of specific molecular species can be correlated. The unique multiple secondary nature of the highly charged ion interaction enables this new analytical technique.

Light-Weight Multispectral Uav Sensors and Their Capabilities for Predicting Grain Yield and Detecting Plant Diseases

NASA Astrophysics Data System (ADS)

Nebiker, S.; Lack, N.; Abächerli, M.; Läderach, S.

2016-06-01

In this paper we investigate the performance of new light-weight multispectral sensors for micro UAV and their application to selected tasks in agronomical research and agricultural practice. The investigations are based on a series of flight campaigns in 2014 and 2015 covering a number of agronomical test sites with experiments on rape, barley, onion, potato and other crops. In our sensor comparison we included a high-end multispectral multiSPEC 4C camera with bandpass colour filters and reference channel in zenith direction and a low-cost, consumer-grade Canon S110 NIR camera with Bayer pattern colour filters. Ground-based reference measurements were obtained using a terrestrial hyperspectral field spectrometer. The investigations show that measurements with the high-end system consistently match very well with ground-based field spectrometer measurements with a mean deviation of just 0.01-0.04 NDVI values. The low-cost system, while delivering better spatial resolutions, expressed significant biases. The sensors were subsequently used to address selected agronomical questions. These included crop yield estimation in rape and barley and plant disease detection in potato and onion cultivations. High levels of correlation between different vegetation indices and reference yield measurements were obtained for rape and barley. In case of barley, the NDRE index shows an average correlation of 87% with reference yield, when species are taken into account. With high geometric resolutions and respective GSDs of down to 2.5 cm the effects of a thrips infestation in onion could be analysed and potato blight was successfully detected at an early stage of infestation.

Comparison of holographic lens and filter systems for lateral spectrum splitting

NASA Astrophysics Data System (ADS)

Vorndran, Shelby; Chrysler, Benjamin; Kostuk, Raymond K.

2016-09-01

Spectrum splitting is an approach to increasing the conversion efficiency of a photovoltaic (PV) system. Several methods can be used to perform this function which requires efficient spatial separation of different spectral bands of the incident solar radiation. In this paper several of holographic methods for implementing spectrum splitting are reviewed along with the benefits and disadvantages associated with each approach. The review indicates that a volume holographic lens has many advantages for spectrum splitting in terms of both power conversion efficiency and energy yield. A specific design for a volume holographic spectrum splitting lens is discussed for use with high bandgap InGaP and low bandgap silicon PV cells. The holographic lenses are modeled using rigorous coupled wave analysis, and the optical efficiency is evaluated using non-sequential raytracing. A proof-of-concept off-axis holographic lens is also recorded in dichromated gelatin film and the spectral diffraction efficiency of the hologram is measured with multiple laser sources across the diffracted spectral band. The experimental volume holographic lens (VHL) characteristics are compared to an ideal spectrum splitting filter in terms of power conversion efficiency and energy yield in environments with high direct normal incidence (DNI) illumination and high levels of diffuse illumination. The results show that the experimental VHL can achieve 62.5% of the ideal filter power conversion efficiency, 64.8% of the ideal filter DNI environment energy yield, and 57.7% of the ideal diffuse environment energy yield performance.

Spatial analysis of ecosystem service relationships to improve targeting of payments for hydrological services

PubMed Central

Manson, Robert H.; Ricketts, Taylor H.; Geissert, Daniel

2018-01-01

Payment for hydrological services (PHS) are popular tools for conserving ecosystems and their water-related services. However, improving the spatial targeting and impacts of PHS, as well as their ability to foster synergies with other ecosystem services (ES), remain challenging. We aimed at using spatial analyses to evaluate the targeting performance of México’s National PHS program in central Veracruz. We quantified the effectiveness of areas targeted for PHS in actually covering areas of high HS provision and social priority during 2003–2013. First, we quantified provisioning and spatial distributions of two target (water yield and soil retention), and one non-target ES (carbon storage) using InVEST. Subsequently, pairwise relationships among ES were quantified by using spatial correlation and overlap analyses. Finally, we evaluated targeting by: (i) prioritizing areas of individual and overlapping ES; (ii) quantifying spatial co-occurrences of these priority areas with those targeted by PHS; (iii) evaluating the extent to which PHS directly contribute to HS delivery; and (iv), testing if PHS targeted areas disproportionately covered areas with high ecological and social priority. We found that modelled priority areas exhibited non-random distributions and distinct spatial patterns. Our results show significant pairwise correlations between all ES suggesting synergistic relationships. However, our analysis showed a significantly lower overlap than expected and thus significant mismatches between PHS targeted areas and all types of priority areas. These findings suggest that the targeting of areas with high HS provisioning and social priority by Mexico’s PHS program could be improved significantly. This study underscores: (1) the importance of using maps of HS provisioning as main targeting criteria in PHS design to channel payments towards areas that require future conservation, and (2) the need for future research that helps balance ecological and socioeconomic targeting criteria. PMID:29462205

Harvester-based sensing system for cotton fiber-quality mapping

USDA-ARS?s Scientific Manuscript database

Precision agriculture in cotton production attempts to maximize profitability by exploiting information on field spatial variability to optimize the fiber yield and quality. For precision agriculture to be economically viable, collection of spatial variability data within a field must be automated a...

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Y.; Xiao, J.

2017-12-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of vegetation greening particularly afforestation on the hydrologic cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China's land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation greening and browning on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield or weakened the increase in water yield; vegetation browning reduced ET and increased water yield or weakened the decrease in water yield. At the large river basin and national scales, the greening trends had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the greenness changes on ET and water yield varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrologic cycle are needed to account for the feedbacks to the climate.

The Multi-Spectral Imaging Diagnostic on Alcator C-MOD and TCV

NASA Astrophysics Data System (ADS)

Linehan, B. L.; Mumgaard, R. T.; Duval, B. P.; Theiler, C. G.; TCV Team

2017-10-01

The Multi-Spectral Imaging (MSI) diagnostic is a new instrument that captures simultaneous spectrally filtered images from a common sight view while maintaining a large tendue and high spatial resolution. The system uses a polychromator layout where each image is sequentially filtered. This procedure yields a high transmission for each spectral channel with minimal vignetting and aberrations. A four-wavelength system was installed on Alcator C-Mod and then moved to TCV. The system uses industrial cameras to simultaneously image the divertor region at 95 frames per second at f/# 2.8 via a coherent fiber bundle (C-Mod) or a lens-based relay optic (TCV). The images are absolutely calibrated and spatially registered enabling accurate measurement of atomic line ratios and absolute line intensities. The images will be used to study divertor detachment by imaging impurities and Balmer series emissions. Furthermore, the large field of view and an ability to support many types of detectors opens the door for other novel approaches to optically measuring plasma with high temporal, spatial, and spectral resolution. Such measurements will allow for the study of Stark broadening and divertor turbulence. Here, we present the first measurements taken with this cavity imaging system. USDoE awards DE-FC02-99ER54512 and award DE-AC05-06OR23100, ORISE, administered by ORAU.

Health risks from large-scale water pollution: trends in Central Asia.

PubMed

Törnqvist, Rebecka; Jarsjö, Jerker; Karimov, Bakhtiyor

2011-02-01

Limited data on the pollution status of spatially extensive water systems constrain health-risk assessments at basin-scales. Using a recipient measurement approach in a terminal water body, we show that agricultural and industrial pollutants in groundwater-surface water systems of the Aral Sea Drainage Basin (covering the main part of Central Asia) yield cumulative health hazards above guideline values in downstream surface waters, due to high concentrations of copper, arsenic, nitrite, and to certain extent dichlorodiphenyltrichloroethane (DDT). Considering these high-impact contaminants, we furthermore perform trend analyses of their upstream spatial-temporal distribution, investigating dominant large-scale spreading mechanisms. The ratio between parent DDT and its degradation products showed that discharges into or depositions onto surface waters are likely to be recent or ongoing. In river water, copper concentrations peak during the spring season, after thawing and snow melt. High spatial variability of arsenic concentrations in river water could reflect its local presence in the top soil of nearby agricultural fields. Overall, groundwaters were associated with much higher health risks than surface waters. Health risks can therefore increase considerably, if the downstream population must switch to groundwater-based drinking water supplies during surface water shortage. Arid regions are generally vulnerable to this problem due to ongoing irrigation expansion and climate changes. Copyright © 2010 Elsevier Ltd. All rights reserved.

The vibro-acoustic response and analysis of a full-scale aircraft fuselage section for interior noise reduction.

PubMed

Herdic, Peter C; Houston, Brian H; Marcus, Martin H; Williams, Earl G; Baz, Amr M

2005-06-01

The surface and interior response of a Cessna Citation fuselage section under three different forcing functions (10-1000 Hz) is evaluated through spatially dense scanning measurements. Spatial Fourier analysis reveals that a point force applied to the stiffener grid provides a rich wavenumber response over a broad frequency range. The surface motion data show global structural modes (approximately < 150 Hz), superposition of global and local intrapanel responses (approximately 150-450 Hz), and intrapanel motion alone (approximately > 450 Hz). Some evidence of Bloch wave motion is observed, revealing classical stop/pass bands associated with stiffener periodicity. The interior response (approximately < 150 Hz) is dominated by global structural modes that force the interior cavity. Local intrapanel responses (approximately > 150 Hz) of the fuselage provide a broadband volume velocity source that strongly excites a high density of interior modes. Mode coupling between the structural response and the interior modes appears to be negligible due to a lack of frequency proximity and mismatches in the spatial distribution. A high degree-of-freedom finite element model of the fuselage section was developed as a predictive tool. The calculated response is in good agreement with the experimental result, yielding a general model development methodology for accurate prediction of structures with moderate to high complexity.

Study of a high-resolution, 3-D positioning cadmium zinc telluride detector for PET

PubMed Central

Gu, Y; Matteson, J L; Skelton, R T; Deal, A C; Stephan, E A; Duttweiler, F; Gasaway, T M; Levin, C S

2011-01-01

This paper investigates the performance of 1 mm resolution Cadmium Zinc Telluride (CZT) detectors for positron emission tomography (PET) capable of positioning the 3-D coordinates of individual 511 keV photon interactions. The detectors comprise 40 mm × 40 mm × 5 mm monolithic CZT crystals that employ a novel cross-strip readout with interspersed steering electrodes to obtain high spatial and energy resolution. The study found a single anode FWHM energy resolution of 3.06±0.39% at 511 keV throughout most the detector volume. Improved resolution is expected with properly shielded front-end electronics. Measurements made using a collimated beam established the efficacy of the steering electrodes in facilitating enhanced charge collection across anodes, as well as a spatial resolution of 0.44±0.07 mm in the direction orthogonal to the electrode planes. Finally, measurements based on coincidence electronic collimation yielded a point spread function with 0.78±0.10 mm FWHM, demonstrating 1 mm spatial resolution capability transverse to the anodes – as expected from the 1 mm anode pitch. These findings indicate that the CZT-based detector concept has excellent performance and shows great promise for a high-resolution PET system. PMID:21335649

Io’s volcanoes at high spatial, spectral, and temporal resolution from ground-based observations

NASA Astrophysics Data System (ADS)

de Kleer, Katherine R.; de Pater, Imke

2017-10-01

Io’s dynamic volcanic eruptions provide a laboratory for studying large-scale volcanism on a body vastly different from Earth, and for unraveling the connections between tidal heating and the geological activity it powers. Ground-based near-infrared observatories allow for high-cadence, long-time-baseline observing programs using diverse instrumentation, and yield new information into the nature and variability of this activity. I will summarize results from four years of ground-based observations of Io’s volcanism, including: (1) A multi-year cadence observing campaign using adaptive optics on 8-10 meter telescopes, which places constraints on tidal heating models through sampling the spatial distribution of Io’s volcanic heat flow, and provides estimates of the occurrence rate of Io’s most energetic eruptions; (2) High-spectral-resolution (R~25,000) studies of Io’s volcanic SO gas emission at 1.7 microns, which resolves this rovibronic line into its different branches, and thus contains detailed information on the temperature and thermal state of the gas; and (3) The highest-spatial-resolution map ever produced of the entire Loki Patera, a 20,000 km2 volcanic feature on Io, derived from adaptive-optics observations of an occultation of Io by Europa. The map achieves a spatial resolution of ~10 km and indicates compositional differences across the patera. These datasets both reveal specific characteristics of Io’s individual eruptions, and provide clues into the sub-surface systems connecting Io’s tidally-heated interior to its surface expressions of volcanism.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

Calculations Supporting Management Zones

USDA-ARS?s Scientific Manuscript database

Since the early 1990’s the tools of precision farming (GPS, yield monitors, soil sensors, etc.) have documented how spatial and temporal variability are important factors impacting crop yield response. For precision farming, variability can be measured then used to divide up a field so that manageme...

Definition of management zones for enhancing cultivated land conservation using combined spatial data.

PubMed

Li, Yan; Shi, Zhou; Wu, Hao-Xiang; Li, Feng; Li, Hong-Yi

2013-10-01

The loss of cultivated land has increasingly become an issue of regional and national concern in China. Definition of management zones is an important measure to protect limited cultivated land resource. In this study, combined spatial data were applied to define management zones in Fuyang city, China. The yield of cultivated land was first calculated and evaluated and the spatial distribution pattern mapped; the limiting factors affecting the yield were then explored; and their maps of the spatial variability were presented using geostatistics analysis. Data were jointly analyzed for management zone definition using a combination of principal component analysis with a fuzzy clustering method, two cluster validity functions were used to determine the optimal number of cluster. Finally one-way variance analysis was performed on 3,620 soil sampling points to assess how well the defined management zones reflected the soil properties and productivity level. It was shown that there existed great potential for increasing grain production, and the amount of cultivated land played a key role in maintaining security in grain production. Organic matter, total nitrogen, available phosphorus, elevation, thickness of the plow layer, and probability of irrigation guarantee were the main limiting factors affecting the yield. The optimal number of management zones was three, and there existed significantly statistical differences between the crop yield and field parameters in each defined management zone. Management zone I presented the highest potential crop yield, fertility level, and best agricultural production condition, whereas management zone III lowest. The study showed that the procedures used may be effective in automatically defining management zones; by the development of different management zones, different strategies of cultivated land management and practice in each zone could be determined, which is of great importance to enhance cultivated land conservation, stabilize agricultural production, promote sustainable use of cultivated land and guarantee food security.

Influence of excited state spatial distributions on plasma diagnostics: Atmospheric pressure laser-induced He-H2 plasma

NASA Astrophysics Data System (ADS)

Monfared, Shabnam K.; Hüwel, Lutz

2012-10-01

Atmospheric pressure plasmas in helium-hydrogen mixtures with H2 molar concentrations ranging from 0.13% to 19.7% were investigated at times from 1 to 25 μs after formation by a Q-switched Nd:YAG laser. Spatially integrated electron density values are obtained using time resolved optical emission spectroscopic techniques. Depending on mixture concentration and delay time, electron densities vary from almost 1017 cm-3 to about 1014 cm-3. Helium based results agree reasonably well with each other, as do values extracted from the Hα and Hβ emission lines. However, in particular for delays up to about 7 μs and in mixtures with less than 1% hydrogen, large discrepancies are observed between results obtained from the two species. Differences decrease with increasing hydrogen partial pressure and/or increasing delay time. In mixtures with molecular hydrogen fraction of 7% or more, all methods yield electron densities that are in good agreement. These findings seemingly contradict the well-established idea that addition of small amounts of hydrogen for diagnostic purposes does not perturb the plasma. Using Abel inversion analysis of the experimental data and a semi-empirical numerical model, we demonstrate that the major part of the detected discrepancies can be traced to differences in the spatial distributions of excited helium and hydrogen neutrals. The model yields spatially resolved emission intensities and electron density profiles that are in qualitative agreement with experiment. For the test case of a 1% H2 mixture at 5 μs delay, our model suggests that high electron temperatures cause an elevated degree of ionization and thus a reduction of excited hydrogen concentration relative to that of helium near the plasma center. As a result, spatially integrated analysis of hydrogen emission lines leads to oversampling of the plasma perimeter and thus to lower electron density values compared to those obtained from helium lines.

Real-time optical image processing techniques

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1988-01-01

Nonlinear real-time optical processing on spatial pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-channel spatial light modulators (MSLMs). Micro-channel spatial light modulators are modified via the Fabry-Perot method to achieve the high gamma operation required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness of the thresholding and also showed the needs of higher SBP for image processing. The Hughes LCLV has been characterized and found to yield high gamma (about 1.7) when operated in low frequency and low bias mode. Cascading of two LCLVs should also provide enough gamma for nonlinear processing. In this case, the SBP of the LCLV is sufficient but the uniformity of the LCLV needs improvement. These include image correlation, computer generation of holograms, pseudo-color image encoding for image enhancement, and associative-retrieval in neural processing. The discovery of the only known optical method for dynamic range compression of an input image in real-time by using GaAs photorefractive crystals is reported. Finally, a new architecture for non-linear multiple sensory, neural processing has been suggested.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

Miniature integrated-optical wavelength analyzer chip

NASA Astrophysics Data System (ADS)

Kunz, R. E.; Dübendorfer, J.

1995-11-01

A novel integrated-optical chip suitable for realizing compact miniature wavelength analyzers with high linear dispersion is presented. The chip performs the complete task of converting the spectrum of an input beam into a corresponding spatial irradiance distribution without the need for an imaging function. We demonstrate the feasibility of this approach experimentally by monitoring the changes in the mode spectrum of a laser diode on varying its case temperature. Comparing the results with simultaneous measurements by a commercial spectrometer yielded a rms wavelength deviation of 0.01 nm.

Strengths and Limitations of Operational Use of 1 Km EO Biophysical Products for Regional Prediction of Grain Yelds in Europe (wheat, barley and maize)

NASA Astrophysics Data System (ADS)

Meroni, M.; LEO, O.; Lopez-Lozano, R.; Baruth, B.; Duveiller, G.; Garcia-Condado, S.; Hooker, J.; Seguini, L.

2014-12-01

The site-specific relationship between EO indicators and actual crop yields has been explored in many different studies, describing semi-empirical regression models between spatially aggregated biophysical parameters or vegetation indices and observed yields (from field measurements or official statistics). However, when considering larger extensions -from countries to continents- agro-climatic conditions and crop management may differ substantially among regions, and these differences may greatly influence the relationship between biophysical indicators and the observed yields, which may be also driven by limiting factors other than green biomass formation. The present study aims to better assess the contribution of EO indicators within an operational crop yield forecasting system in Europe and neighbouring countries, by evaluating how these above mentioned geographic differences influence the relationship between biophysical indicators and crop yield. We therefore explore, as a first step, the correspondence between fAPAR time-series (1999-2013) and the inter-annual yield variability of wheat, barley and grain maize, at sub-national level across Europe (270-450 Administrative Units, depending on crop). In a second step, we map the agro-climatic contexts in which EO indicators better explain the observed yield inter-annual variability, identify the influence of some meteorological events on the fAPAR -yield relationship and provide some recommendations for further investigation. The results indicate that in water-limited environments (e.g. Mediterranean and Black Sea areas), fAPAR is highly correlated with yields whereas in northern Europe, crop yield appears much less limited by leaf area expansion along the season, and the relationship between yield and EO products becomes more difficult to interpret.

Scanning ion imaging - a potent tool in SIMS U -Pb zircon geochronology

NASA Astrophysics Data System (ADS)

Whitehouse, M. J.; Fedo, C.; Kusiak, M.; Nemchin, A.

2012-12-01

The application of high spatial resolution (< 15-20 μm lateral) U-Pb data obtained by sec-ondary ion mass spectrometers (SIMS) coupled with textural information from scanning electron microscope (SEM) based cathodoluminescence (CL) and/or back-scattered elec-tron (BSE) characterisation, has revolutionised geochronology over the past 25 years, re-vealing complexities of crustal evolution from zoned zircons. In addition to ge-ochronology, such studies now commonly form the basis of broader investigations using O- and Hf- isotopes and trace elements obtained from the same growth zone as age, circumventing ambiguities commonly present in bulk-rock isotope studies. The choice of analytical beam diameter is often made to maximise the precision of data obtained from a given area of analysis within an identifiable growth zone. In cases where zircons yield poorly constrained internal structures in SEM, high spatial resolution spot analyses may yield uninterpretable and/or meaningless mixed ages by inadvertent sampling across regions with real age differences. Scanning ion imaging (SII) has the potential to generate accurate and precise geochrono-logical data with a spatial resolution down to ca. 2 μm, much higher than that of a normal spot analysis. SII acquisition utilises a rastered primary beam to image an area of the sample with a spatial resolution dependent on the selected primary beam diameter. On the Cameca ims1270/80 instruments, the primary beam scanning is coupled with the dynamic transfer optical system (DTOS) which deflects the secondary ions back on to the ion optical axis of the instrument regardless of where in the raster illuminated area the ions originated. This feature allows retention of a high field magnification (= high transmission) mode and the ability to operate the mass spectrometer at high mass resolution without any compromise in the quality of the peak shape. Secondary ions may be detected either in a sequential (peak hopping) mono-collection mode or simultaneous multicollection mode using low-noise pulse counting electron multipliers. Regardless of the detection mode, data are acquired over sufficient cycles to generate usable counting statistics from selected sub-areas of the image. In two case studies from southern west Greenland and Antarctica, Pb-isotope maps gen-erated using SII reveal considerable complexities of internal structure, age and isotope systematics that were not predictable from CL imaging of the grains (Fig. 1). Fig. 1. Scanning ion images of the 207Pb/206Pb ratio in zircons from (a) W. Greenland and (b) Antarctica (inset shows rastered area of grain corresponding to the image).

Precise Placement of Metallic Nanowires on a Substrate by Localized Electric Fields and Inter-Nanowire Electrostatic Interaction

PubMed Central

2017-01-01

Placing nanowires at the predetermined locations on a substrate represents one of the significant hurdles to be tackled for realization of heterogeneous nanowire systems. Here, we demonstrate spatially-controlled assembly of a single nanowire at the photolithographically recessed region at the electrode gap with high integration yield (~90%). Two popular routes, such as protruding electrode tips and recessed wells, for spatially-controlled nanowire alignment, are compared to investigate long-range dielectrophoretic nanowire attraction and short-range nanowire-nanowire electrostatic interaction for determining the final alignment of attracted nanowires. Furthermore, the post-assembly process has been developed and tested to make a robust electrical contact to the assembled nanowires, which removes any misaligned ones and connects the nanowires to the underlying electrodes of circuit. PMID:29048363

Optical network scaling: roles of spectral and spatial aggregation.

PubMed

Arık, Sercan Ö; Ho, Keang-Po; Kahn, Joseph M

2014-12-01

As the bit rates of routed data streams exceed the throughput of single wavelength-division multiplexing channels, spectral and spatial traffic aggregation become essential for optical network scaling. These aggregation techniques reduce network routing complexity by increasing spectral efficiency to decrease the number of fibers, and by increasing switching granularity to decrease the number of switching components. Spectral aggregation yields a modest decrease in the number of fibers but a substantial decrease in the number of switching components. Spatial aggregation yields a substantial decrease in both the number of fibers and the number of switching components. To quantify routing complexity reduction, we analyze the number of multi-cast and wavelength-selective switches required in a colorless, directionless and contentionless reconfigurable optical add-drop multiplexer architecture. Traffic aggregation has two potential drawbacks: reduced routing power and increased switching component size.

Mesoscale Science with High Energy X-ray Diffraction Microscopy at the Advanced Photon Source

NASA Astrophysics Data System (ADS)

Suter, Robert

2014-03-01

Spatially resolved diffraction of monochromatic high energy (> 50 keV) x-rays is used to map microstructural quantities inside of bulk polycrystalline materials. The non-destructive nature of High Energy Diffraction Microscopy (HEDM) measurements allows tracking of responses as samples undergo thermo-mechanical or other treatments. Volumes of the order of a cubic millimeter are probed with micron scale spatial resolution. Data sets allow direct comparisons to computational models of responses that frequently involve long-ranged, multi-grain interactions; such direct comparisons have only become possible with the development of HEDM and other high energy x-ray methods. Near-field measurements map the crystallographic orientation field within and between grains using a computational reconstruction method that simulates the experimental geometry and matches orientations in micron sized volume elements to experimental data containing projected grain images in large numbers of Bragg peaks. Far-field measurements yield elastic strain tensors through indexing schemes that sort observed diffraction peaks into sets associated with individual crystals and detect small radial motions in large numbers of such peaks. Combined measurements, facilitated by a new end station hutch at Advanced Photon Source beamline 1-ID, are mutually beneficial and result in accelerated data reduction. Further, absorption tomography yields density contrast that locates secondary phases, void clusters, and cracks, and tracks sample shape during deformation. A collaboration led by the Air Force Research Laboratory and including the Advanced Photon Source, Lawrence Livermore National Laboratory, Carnegie Mellon University, Petra-III, and Cornell University and CHESS is developing software and hardware for combined measurements. Examples of these capabilities include tracking of grain boundary migrations during thermal annealing, tensile deformation of zirconium, and combined measurements of nickel superalloys and a titanium alloy under tensile forces. Work supported by NSF grant DMR-1105173

Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

NASA Astrophysics Data System (ADS)

Mann, M.; Warner, J.

2015-12-01

Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

Spatial averaging of a dissipative particle dynamics model for active suspensions

NASA Astrophysics Data System (ADS)

Panchenko, Alexander; Hinz, Denis F.; Fried, Eliot

2018-03-01

Starting from a fine-scale dissipative particle dynamics (DPD) model of self-motile point particles, we derive meso-scale continuum equations by applying a spatial averaging version of the Irving-Kirkwood-Noll procedure. Since the method does not rely on kinetic theory, the derivation is valid for highly concentrated particle systems. Spatial averaging yields stochastic continuum equations similar to those of Toner and Tu. However, our theory also involves a constitutive equation for the average fluctuation force. According to this equation, both the strength and the probability distribution vary with time and position through the effective mass density. The statistics of the fluctuation force also depend on the fine scale dissipative force equation, the physical temperature, and two additional parameters which characterize fluctuation strengths. Although the self-propulsion force entering our DPD model contains no explicit mechanism for aligning the velocities of neighboring particles, our averaged coarse-scale equations include the commonly encountered cubically nonlinear (internal) body force density.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS.

PubMed

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H] + ). Identifying and distinguishing the molecular ions of lipids (m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS. Graphical Abstract ᅟ.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS

NASA Astrophysics Data System (ADS)

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H]+). Identifying and distinguishing the molecular ions of lipids ( m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

The low-temperature scintillation properties of bismuth germanate and its application to high-energy gamma radiation imaging devices.

PubMed

Piltingsrud, H V

1979-12-01

Bismuth germanate is a scintillation material with very high z, and high density (7.13 g/cm3). It is a rugged, nonhygroscopic, crystalline material with room-temperature scintillation properties described by previous investigators as having a light yield approximately 8% of that of NaI(Tl), emission peak at approximately 480 nm, decay constant of 0.3 microsec, and energy resolution congruent to 15% (FWHM) for Cs-137 gamma radiations. These properties make it an excellent candidate for applications involving the detection of high-energy gamma photons and positron annihilation radiation, particularly when good spatial resolution is desired. At room temperature, however, the application of this material is somewhat limited by low light output and poor energy resolution. This paper presents new data on the scintillation properties of bismuth germanate as a function of temperature from -- 196 degrees C to j0 degrees C. Low-temperature use of the material is shown to greatly improve its light yield and energy resolution. The implications of this work to the design of imaging devices for high-energy radiation in health physics and nuclear medicine are discussed.

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

NASA Astrophysics Data System (ADS)

Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Printable semiconductor structures and related methods of making and assembling

DOEpatents

Nuzzo, Ralph G.; Rogers, John A.; Menard, Etienne; Lee, Keon Jae; Khang; , Dahl-Young; Sun, Yugang; Meitl, Matthew; Zhu, Zhengtao; Ko, Heung Cho; Mack, Shawn

2013-03-12

The present invention provides a high yield pathway for the fabrication, transfer and assembly of high quality printable semiconductor elements having selected physical dimensions, shapes, compositions and spatial orientations. The compositions and methods of the present invention provide high precision registered transfer and integration of arrays of microsized and/or nanosized semiconductor structures onto substrates, including large area substrates and/or flexible substrates. In addition, the present invention provides methods of making printable semiconductor elements from low cost bulk materials, such as bulk silicon wafers, and smart-materials processing strategies that enable a versatile and commercially attractive printing-based fabrication platform for making a broad range of functional semiconductor devices.

Printable semiconductor structures and related methods of making and assembling

DOEpatents

Nuzzo, Ralph G [Champaign, IL; Rogers, John A [Champaign, IL; Menard, Etienne [Durham, NC; Lee, Keon Jae [Tokyo, JP; Khang, Dahl-Young [Urbana, IL; Sun, Yugang [Westmont, IL; Meitl, Matthew [Raleigh, NC; Zhu, Zhengtao [Rapid City, SD; Ko, Heung Cho [Urbana, IL; Mack, Shawn [Goleta, CA

2011-10-18

The present invention provides a high yield pathway for the fabrication, transfer and assembly of high quality printable semiconductor elements having selected physical dimensions, shapes, compositions and spatial orientations. The compositions and methods of the present invention provide high precision registered transfer and integration of arrays of microsized and/or nanosized semiconductor structures onto substrates, including large area substrates and/or flexible substrates. In addition, the present invention provides methods of making printable semiconductor elements from low cost bulk materials, such as bulk silicon wafers, and smart-materials processing strategies that enable a versatile and commercially attractive printing-based fabrication platform for making a broad range of functional semiconductor devices.

Printable semiconductor structures and related methods of making and assembling

DOEpatents

Nuzzo, Ralph G.; Rogers, John A.; Menard, Etienne; Lee, Keon Jae; Khang, Dahl-Young; Sun, Yugang; Meitl, Matthew; Zhu, Zhengtao; Ko, Heung Cho; Mack, Shawn

2010-09-21

The present invention provides a high yield pathway for the fabrication, transfer and assembly of high quality printable semiconductor elements having selected physical dimensions, shapes, compositions and spatial orientations. The compositions and methods of the present invention provide high precision registered transfer and integration of arrays of microsized and/or nanosized semiconductor structures onto substrates, including large area substrates and/or flexible substrates. In addition, the present invention provides methods of making printable semiconductor elements from low cost bulk materials, such as bulk silicon wafers, and smart-materials processing strategies that enable a versatile and commercially attractive printing-based fabrication platform for making a broad range of functional semiconductor devices.

Winners and losers of national and global efforts to reconcile agricultural intensification and biodiversity conservation.

PubMed

Egli, Lukas; Meyer, Carsten; Scherber, Christoph; Kreft, Holger; Tscharntke, Teja

2018-05-01

Closing yield gaps within existing croplands, and thereby avoiding further habitat conversions, is a prominently and controversially discussed strategy to meet the rising demand for agricultural products, while minimizing biodiversity impacts. The agricultural intensification associated with such a strategy poses additional threats to biodiversity within agricultural landscapes. The uneven spatial distribution of both yield gaps and biodiversity provides opportunities for reconciling agricultural intensification and biodiversity conservation through spatially optimized intensification. Here, we integrate distribution and habitat information for almost 20,000 vertebrate species with land-cover and land-use datasets. We estimate that projected agricultural intensification between 2000 and 2040 would reduce the global biodiversity value of agricultural lands by 11%, relative to 2000. Contrasting these projections with spatial land-use optimization scenarios reveals that 88% of projected biodiversity loss could be avoided through globally coordinated land-use planning, implying huge efficiency gains through international cooperation. However, global-scale optimization also implies a highly uneven distribution of costs and benefits, resulting in distinct "winners and losers" in terms of national economic development, food security, food sovereignty or conservation. Given conflicting national interests and lacking effective governance mechanisms to guarantee equitable compensation of losers, multinational land-use optimization seems politically unlikely. In turn, 61% of projected biodiversity loss could be avoided through nationally focused optimization, and 33% through optimization within just 10 countries. Targeted efforts to improve the capacity for integrated land-use planning for sustainable intensification especially in these countries, including the strengthening of institutions that can arbitrate subnational land-use conflicts, may offer an effective, yet politically feasible, avenue to better reconcile future trade-offs between agriculture and conservation. The efficiency gains of optimization remained robust when assuming that yields could only be increased to 80% of their potential. Our results highlight the need to better integrate real-world governance, political and economic challenges into sustainable development and global change mitigation research. © 2018 John Wiley & Sons Ltd.

Recent changes in county-level corn yield variability in the United States from observations and crop models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

USDA-ARS?s Scientific Manuscript database

There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Yield response to landscape position under variable N for irrigated corn

USDA-ARS?s Scientific Manuscript database

Variable nutrient and water supply can result in spatial and temporal variation in crop yield within a given agricultural field. For the western Corn Belt, irrigated corn accounts for 58% of total annual corn production with the majority grown in Nebraska. Although irrigation decreases temporal yi...

Maize yield response to nitrogen as influenced by spatio-temporal variations of soil-water-topography dynamics

USDA-ARS?s Scientific Manuscript database

Reducing N loss from agricultural lands and applying N fertilizer at rates that satisfy both economic and environmental objectives is critical for sustainable agricultural management. This study investigated spatial variability in maize yield response to N and its controlling factors along a typical...

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled futuremore » climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.« less

Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?

USDA-ARS?s Scientific Manuscript database

Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...

Topographic controls on soil nutrient variations in a Silvopasture system

USDA-ARS?s Scientific Manuscript database

Topography plays a crucial role in the spatial distribution of nutrients in soils because of its influence on the flow and (re)distribution of water and energy in a landscape. Information on the spatial pattern of soil nutrient distribution would benefit management decisions to maximize crop yield a...

Big assumptions for small samples in crop insurance

Treesearch

Ashley Elaine Hungerford; Barry Goodwin

2014-01-01

The purpose of this paper is to investigate the effects of crop insurance premiums being determined by small samples of yields that are spatially correlated. If spatial autocorrelation and small sample size are not properly accounted for in premium ratings, the premium rates may inaccurately reflect the risk of a loss.

Sources of nitrate yields in the Mississippi River Basin.

PubMed

David, Mark B; Drinkwater, Laurie E; McIsaac, Gregory F

2010-01-01

Riverine nitrate N in the Mississippi River leads to hypoxia in the Gulf of Mexico. Several recent modeling studies estimated major N inputs and suggested source areas that could be targeted for conservation programs. We conducted a similar analysis with more recent and extensive data that demonstrates the importance of hydrology in controlling the percentage of net N inputs (NNI) exported by rivers. The average fraction of annual riverine nitrate N export/NNI ranged from 0.05 for the lower Mississippi subbasin to 0.3 for the upper Mississippi River basin and as high as 1.4 (4.2 in a wet year) for the Embarras River watershed, a mostly tile-drained basin. Intensive corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] watersheds on Mollisols had low NNI values and when combined with riverine N losses suggest a net depletion of soil organic N. We used county-level data to develop a nonlinear model ofN inputs and landscape factors that were related to winter-spring riverine nitrate yields for 153 watersheds within the basin. We found that river runoff times fertilizer N input was the major predictive term, explaining 76% of the variation in the model. Fertilizer inputs were highly correlated with fraction of land area in row crops. Tile drainage explained 17% of the spatial variation in winter-spring nitrate yield, whereas human consumption of N (i.e., sewage effluent) accounted for 7%. Net N inputs were not a good predictor of riverine nitrate N yields, nor were other N balances. We used this model to predict the expected nitrate N yield from each county in the Mississippi River basin; the greatest nitrate N yields corresponded to the highly productive, tile-drained cornbelt from southwest Minnesota across Iowa, Illinois, Indiana, and Ohio. This analysis can be used to guide decisions about where efforts to reduce nitrate N losses can be most effectively targeted to improve local water quality and reduce export to the Gulf of Mexico.

Multiyear high-resolution carbon exchange over European croplands from the integration of observed crop yields into CarbonTracker Europe

NASA Astrophysics Data System (ADS)

Combe, Marie; Vilà-Guerau de Arellano, Jordi; de Wit, Allard; Peters, Wouter

2016-04-01

Carbon exchange over croplands plays an important role in the European carbon cycle over daily-to-seasonal time scales. Not only do crops occupy one fourth of the European land area, but their photosynthesis and respiration are large and affect CO2 mole fractions at nearly every atmospheric CO2 monitoring site. A better description of this crop carbon exchange in our CarbonTracker Europe data assimilation system - which currently treats crops as unmanaged grasslands - could strongly improve its ability to constrain terrestrial carbon fluxes. Available long-term observations of crop yield, harvest, and cultivated area allow such improvements, when combined with the new crop-modeling framework we present. This framework can model the carbon fluxes of 10 major European crops at high spatial and temporal resolution, on a 12x12 km grid and 3-hourly time-step. The development of this framework is threefold: firstly, we optimize crop growth using the process-based WOrld FOod STudies (WOFOST) agricultural crop growth model. Simulated yields are downscaled to match regional crop yield observations from the Statistical Office of the European Union (EUROSTAT) by estimating a yearly regional parameter for each crop species: the yield gap factor. This step allows us to better represent crop phenology, to reproduce the observed multiannual European crop yields, and to construct realistic time series of the crop carbon fluxes (gross primary production, GPP, and autotrophic respiration, Raut) on a fine spatial and temporal resolution. Secondly, we combine these GPP and Raut fluxes with a simple soil respiration model to obtain the total ecosystem respiration (TER) and net ecosystem exchange (NEE). And thirdly, we represent the horizontal transport of carbon that follows crop harvest and its back-respiration into the atmosphere during harvest consumption. We distribute this carbon using observations of the density of human and ruminant populations from EUROSTAT. We assess the model's ability to represent the seasonal GPP, TER and NEE fluxes using observations at 6 European FluxNet winter wheat and grain maize sites and compare it with the fluxes of the current terrestrial carbon cycle model of CarbonTracker Europe: the Simple Biosphere - Carnegie-Ames-Stanford Approach (SiBCASA) model. We find that the new model framework provides a detailed, realistic, and strongly observation-driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal, and serve as a new cropland component in CarbonTracker Europe flux estimates.

Growth of Nanosized Single Crystals for Efficient Perovskite Light-Emitting Diodes.

PubMed

Lee, Seungjin; Park, Jong Hyun; Nam, Yun Seok; Lee, Bo Ram; Zhao, Baodan; Di Nuzzo, Daniele; Jung, Eui Dae; Jeon, Hansol; Kim, Ju-Young; Jeong, Hu Young; Friend, Richard H; Song, Myoung Hoon

2018-04-24

Organic-inorganic hybrid perovskites are emerging as promising emitting materials due to their narrow full-width at half-maximum emissions, color tunability, and high photoluminescence quantum yields (PLQYs). However, the thermal generation of free charges at room temperature results in a low radiative recombination rate and an excitation-intensity-dependent PLQY, which is associated with the trap density. Here, we report perovskite films composed of uniform nanosized single crystals (average diameter = 31.7 nm) produced by introducing bulky amine ligands and performing the growth at a lower temperature. By effectively controlling the crystal growth, we maximized the radiative bimolecular recombination yield by reducing the trap density and spatially confining the charges. Finally, highly bright and efficient green emissive perovskite light-emitting diodes that do not suffer from electroluminescence blinking were achieved with a luminance of up to 55 400 cd m -2 , current efficiency of 55.2 cd A -1 , and external quantum efficiency of 12.1%.

Role of Excessive Autophagy Induced by Mechanical Overload in Vein Graft Neointima Formation: Prediction and Prevention

NASA Astrophysics Data System (ADS)

Chang, Ya-Ju; Huang, Hui-Chun; Hsueh, Yuan-Yu; Wang, Shao-Wei; Su, Fong-Chin; Chang, Chih-Han; Tang, Ming-Jer; Li, Yi-Shuan; Wang, Shyh-Hau; Shung, Kirk K.; Chien, Shu; Wu, Chia-Ching

2016-02-01

Little is known regarding the interplays between the mechanical and molecular bases for vein graft restenosis. We elucidated the stenosis initiation using a high-frequency ultrasonic (HFU) echogenicity platform and estimated the endothelium yield stress from von-Mises stress computation to predict the damage locations in living rats over time. The venous-arterial transition induced the molecular cascades for autophagy and apoptosis in venous endothelial cells (ECs) to cause neointimal hyperplasia, which correlated with the high echogenicity in HFU images and the large mechanical stress that exceeded the yield strength. The ex vivo perfusion of arterial laminar shear stress to isolated veins further confirmed the correlation. EC damage can be rescued by inhibiting autophagy formation using 3-methyladenine (3-MA). Pretreatment of veins with 3-MA prior to grafting reduced the pathological increases of echogenicity and neointima formation in rats. Therefore, this platform provides non-invasive temporal spatial measurement and prediction of restenosis after venous-arterial transition as well as monitoring the progression of the treatments.

Modeling the impacts of hunting on the population dynamics of red howler monkeys (Alouatta seniculus)

USGS Publications Warehouse

Wiederholt, Ruscena; Fernandez-Duque, Eduardo; Diefenbach, Duane R.; Rudran, Rasanayagam

2010-01-01

Overexploitation of wildlife populations occurs across the humid tropics and is a significant threat to the long-term survival of large-bodied primates. To investigate the impacts of hunting on primates and ways to mitigate them, we developed a spatially explicit, individual-based model for a landscape that included hunted and un-hunted areas. We used the large-bodied neotropical red howler monkey (Alouatta seniculus) as our case study species because its life history characteristics make it vulnerable to hunting. We modeled the influence of different rates of harvest and proportions of landscape dedicated to un-hunted reserves on population persistence, population size, social dynamics, and hunting yields of red howler monkeys. In most scenarios, the un-hunted populations maintained a constant density regardless of hunting pressure elsewhere, and allowed the overall population to persist. Therefore, the overall population was quite resilient to extinction; only in scenarios without any un-hunted areas did the population go extinct. However, the total and hunted populations did experience large declines over 100 years under moderate and high hunting pressure. In addition, when reserve area decreased, population losses and losses per unit area increased disproportionately. Furthermore, hunting disrupted the social structure of troops. The number of male turnovers and infanticides increased in hunted populations, while birth rates decreased and exacerbated population losses due to hunting. Finally, our results indicated that when more than 55% of the landscape was harvested at high (30%) rates, hunting yields, as measured by kilograms of biomass, were less than those obtained from moderate harvest rates. Additionally, hunting yields, expressed as the number of individuals hunted/year/km2, increased in proximity to un-hunted areas, and suggested that dispersal from un-hunted areas may have contributed to hunting sustainability. These results indicate that un-hunted areas serve to enhance hunting yields, population size, and population persistence in hunted landscapes. Therefore, spatial regulation of hunting via a reserve system may be an effective management strategy for sustainable hunting, and we recommend it because it may also be more feasible to implement than harvest quotas or restrictions on season length.

Towards a Solid Foundation of Using Remotely Sensed Solar-Induced Chlorophyll Fluorescence for Crop Monitoring and Yield Forecast

NASA Astrophysics Data System (ADS)

Chen, Y.; Sun, Y.; You, L.; Liu, Y.

2017-12-01

The growing demand for food production due to population increase coupled with high vulnerability to volatile environmental changes poses a paramount challenge for mankind in the coming century. Real-time crop monitoring and yield forecasting must be a key part of any solution to this challenge as these activities provide vital information needed for effective and efficient crop management and for decision making. However, traditional methods of crop growth monitoring (e.g., remotely sensed vegetation indices) do not directly relate to the most important function of plants - photosynthesis and therefore crop yield. The recent advance in the satellite remote sensing of Solar-Induced chlorophyll Fluorescence (SIF), an integrative photosynthetic signal from molecular origin and a direct measure of plant functions holds great promise for real-time monitoring of crop growth conditions and forecasting yields. In this study, we use satellite measurements of SIF from both the Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A and the Orbiting Carbon Observatory-2 (OCO-2) satellites to estimate crop yield using both process-based and statistical models. We find that SIF-based crop yield well correlates with the global yield product Spatial Production Allocation Model (SPAM) derived from ground surveys for all major crops including maize, soybean, wheat, sorghum, and rice. The potential and challenges of using upcoming SIF satellite missions for crop monitoring and prediction will also be discussed.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Rainfall disaggregation for urban hydrology: Effects of spatial consistence

NASA Astrophysics Data System (ADS)

Müller, Hannes; Haberlandt, Uwe

2015-04-01

For urban hydrology rainfall time series with a high temporal resolution are crucial. Observed time series of this kind are very short in most cases, so they cannot be used. On the contrary, time series with lower temporal resolution (daily measurements) exist for much longer periods. The objective is to derive time series with a long duration and a high resolution by disaggregating time series of the non-recording stations with information of time series of the recording stations. The multiplicative random cascade model is a well-known disaggregation model for daily time series. For urban hydrology it is often assumed, that a day consists of only 1280 minutes in total as starting point for the disaggregation process. We introduce a new variant for the cascade model, which is functional without this assumption and also outperforms the existing approach regarding time series characteristics like wet and dry spell duration, average intensity, fraction of dry intervals and extreme value representation. However, in both approaches rainfall time series of different stations are disaggregated without consideration of surrounding stations. This yields in unrealistic spatial patterns of rainfall. We apply a simulated annealing algorithm that has been used successfully for hourly values before. Relative diurnal cycles of the disaggregated time series are resampled to reproduce the spatial dependence of rainfall. To describe spatial dependence we use bivariate characteristics like probability of occurrence, continuity ratio and coefficient of correlation. Investigation area is a sewage system in Northern Germany. We show that the algorithm has the capability to improve spatial dependence. The influence of the chosen disaggregation routine and the spatial dependence on overflow occurrences and volumes of the sewage system will be analyzed.

Constraints on Circumstellar Dust Grain Sizes from High Spatial Resolution Observations in the Thermal Infrared

NASA Technical Reports Server (NTRS)

Bloemhof, E. E.; Danen, R. M.; Gwinn, C. R.

1996-01-01

We describe how high spatial resolution imaging of circumstellar dust at a wavelength of about 10 micron, combined with knowledge of the source spectral energy distribution, can yield useful information about the sizes of the individual dust grains responsible for the infrared emission. Much can be learned even when only upper limits to source size are available. In parallel with high-resolution single-telescope imaging that may resolve the more extended mid-infrared sources, we plan to apply these less direct techniques to interpretation of future observations from two-element optical interferometers, where quite general arguments may be made despite only crude imaging capability. Results to date indicate a tendency for circumstellar grain sizes to be rather large compared to the Mathis-Rumpl-Nordsieck size distribution traditionally thought to characterize dust in the general interstellar medium. This may mean that processing of grains after their initial formation and ejection from circumstellar atmospheres adjusts their size distribution to the ISM curve; further mid-infrared observations of grains in various environments would help to confirm this conjecture.

Mechanisms of value-learning in the guidance of spatial attention.

PubMed

Anderson, Brian A; Kim, Haena

2018-05-11

The role of associative reward learning in the guidance of feature-based attention is well established. The extent to which reward learning can modulate spatial attention has been much more controversial. At least one demonstration of a persistent spatial attention bias following space-based associative reward learning has been reported. At the same time, multiple other experiments have been published failing to demonstrate enduring attentional biases towards locations at which a target, if found, yields high reward. This is in spite of evidence that participants use reward structures to inform their decisions where to search, leading some to suggest that, unlike feature-based attention, spatial attention may be impervious to the influence of learning from reward structures. Here, we demonstrate a robust bias towards regions of a scene that participants were previously rewarded for selecting. This spatial bias relies on representations that are anchored to the configuration of objects within a scene. The observed bias appears to be driven specifically by reinforcement learning, and can be observed with equal strength following non-reward corrective feedback. The time course of the bias is consistent with a transient shift of attention, rather than a strategic search pattern, and is evident in eye movement patterns during free viewing. Taken together, our findings reconcile previously conflicting reports and offer an integrative account of how learning from feedback shapes the spatial attention system. Copyright © 2018 Elsevier B.V. All rights reserved.

Surrogate taxa and fossils as reliable proxies of spatial biodiversity patterns in marine benthic communities.

PubMed

Tyler, Carrie L; Kowalewski, Michał

2017-03-15

Rigorous documentation of spatial heterogeneity (β-diversity) in present-day and preindustrial ecosystems is required to assess how marine communities respond to environmental and anthropogenic drivers. However, the overwhelming majority of contemporary and palaeontological assessments have centred on single higher taxa. To evaluate the validity of single taxa as community surrogates and palaeontological proxies, we compared macrobenthic communities and sympatric death assemblages at 52 localities in Onslow Bay (NC, USA). Compositional heterogeneity did not differ significantly across datasets based on live molluscs, live non-molluscs, and all live organisms. Death assemblages were less heterogeneous spatially, likely reflecting homogenization by time-averaging. Nevertheless, live and dead datasets were greater than 80% congruent in pairwise comparisons to the literature estimates of β-diversity in other marine ecosystems, yielded concordant bathymetric gradients, and produced nearly identical ordinations consistently delineating habitats. Congruent estimates from molluscs and non-molluscs suggest that single groups can serve as reliable community proxies. High spatial fidelity of death assemblages supports the emerging paradigm of Conservation Palaeobiology. Integrated analyses of ecological and palaeontological data based on surrogate taxa can quantify anthropogenic changes in marine ecosystems and advance our understanding of spatial and temporal aspects of biodiversity. © 2017 The Author(s).

Atmospheric circulation patterns and spatial climatic variations in Beringia

NASA Astrophysics Data System (ADS)

Mock, Cary J.; Bartlein, Patrick J.; Anderson, Patricia M.

1998-08-01

Analyses of more than 40 years of climatic data reveal intriguing spatial variations in climatic patterns for Beringia (North-eastern Siberia and Alaska), aiding the understanding of the hierarchy of climatic controls that operate at different spatial scales within the Arctic. A synoptic climatology, using a subjective classification methodology on January and July sea level pressure, and July 500 hPa height anomaly patterns, identified 13 major atmospheric circulation patterns (26 pairs consisting of 13 synoptic/temperature and 13 synoptic/precipitation comparisons) that occur over Beringia. Composite anomaly maps of circulation, temperature, and precipitation described the spatial variability of surface climatic responses to circulation. Results indicate that nine synoptic pairs yield homogeneous surface climatic anomaly patterns throughout most of Beringia. However, many of the surface climatic responses illustrate heterogeneous anomaly patterns as a result of variations in circulation controls, such as troughing over East Asia and the Pacific subtropical high superimposed over topography, with small shifts in atmospheric circulation dramatically altering spatial variations of anomaly patterns. Distinctive contrasts in climatic responses, as suggested from ten synoptic pairs, are clearly evident for Western Beringia versus Eastern Beringia. These results offer important implications for scholars interested in assessing late Quaternary climatic change in the region from interannual to millennial timescales.

The Structure of Working Memory Abilities across the Adult Life Span

PubMed Central

Hale, Sandra; Rose, Nathan S.; Myerson, Joel; Strube, Michael J; Sommers, Mitchell; Tye-Murray, Nancy; Spehar, Brent

2010-01-01

The present study addresses three questions regarding age differences in working memory: (1) whether performance on complex span tasks decreases as a function of age at a faster rate than performance on simple span tasks; (2) whether spatial working memory decreases at a faster rate than verbal working memory; and (3) whether the structure of working memory abilities is different for different age groups. Adults, ages 20–89 (n=388), performed three simple and three complex verbal span tasks and three simple and three complex spatial memory tasks. Performance on the spatial tasks decreased at faster rates as a function of age than performance on the verbal tasks, but within each domain, performance on complex and simple span tasks decreased at the same rates. Confirmatory factor analyses revealed that domain-differentiated models yielded better fits than models involving domain-general constructs, providing further evidence of the need to distinguish verbal and spatial working memory abilities. Regardless of which domain-differentiated model was examined, and despite the faster rates of decrease in the spatial domain, age group comparisons revealed that the factor structure of working memory abilities was highly similar in younger and older adults and showed no evidence of age-related dedifferentiation. PMID:21299306

Adaptive electron beam shaping using a photoemission gun and spatial light modulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maxson, Jared; Lee, Hyeri; Bartnik, Adam C.

The need for precisely defined beam shapes in photoelectron sources has been well established. In this paper, we use a spatial light modulator and simple shaping algorithm to create arbitrary, detailed transverse laser shapes with high fidelity. We transmit this shaped laser to the photocathode of a high voltage dc gun. Using beam currents where space charge is negligible, and using an imaging solenoid and fluorescent viewscreen, we show that the resultant beam shape preserves these detailed features with similar fidelity. Next, instead of transmitting a shaped laser profile, we use an active feedback on the unshaped electron beam imagemore » to create equally accurate and detailed shapes. We demonstrate that this electron beam feedback has the added advantage of correcting for electron optical aberrations, yielding shapes without skew. The method may serve to provide precisely defined electron beams for low current target experiments, space-charge dominated beam commissioning, as well as for online adaptive correction of photocathode quantum efficiency degradation.« less

Adaptive electron beam shaping using a photoemission gun and spatial light modulator

NASA Astrophysics Data System (ADS)

Maxson, Jared; Lee, Hyeri; Bartnik, Adam C.; Kiefer, Jacob; Bazarov, Ivan

2015-02-01

The need for precisely defined beam shapes in photoelectron sources has been well established. In this paper, we use a spatial light modulator and simple shaping algorithm to create arbitrary, detailed transverse laser shapes with high fidelity. We transmit this shaped laser to the photocathode of a high voltage dc gun. Using beam currents where space charge is negligible, and using an imaging solenoid and fluorescent viewscreen, we show that the resultant beam shape preserves these detailed features with similar fidelity. Next, instead of transmitting a shaped laser profile, we use an active feedback on the unshaped electron beam image to create equally accurate and detailed shapes. We demonstrate that this electron beam feedback has the added advantage of correcting for electron optical aberrations, yielding shapes without skew. The method may serve to provide precisely defined electron beams for low current target experiments, space-charge dominated beam commissioning, as well as for online adaptive correction of photocathode quantum efficiency degradation.

A quantitative and spatially resolved analysis of the performance-bottleneck in high efficiency, planar hybrid perovskite solar cells

DOE PAGES

Draguta, Sergiu; Christians, Jeffrey A.; Morozov, Yurii V.; ...

2018-01-01

Hybrid perovskites represent a potential paradigm shift for the creation of low-cost solar cells. Current power conversion efficiencies (PCEs) exceed 22%. However, despite this, record PCEs are still far from their theoretical Shockley–Queisser limit of 31%. To increase these PCE values, there is a pressing need to understand, quantify and microscopically model charge recombination processes in full working devices. Here, we present a complete microscopic account of charge recombination processes in high efficiency (18–19% PCE) hybrid perovskite (mixed cation and methylammonium lead iodide) solar cells. We employ diffraction-limited optical measurements along with relevant kinetic modeling to establish, for the firstmore » time, local photoluminescence quantum yields, trap densities, trapping efficiencies, charge extraction efficiencies, quasi-Fermi-level splitting, and effective PCE estimates. Correlations between these spatially resolved parameters, in turn, allow us to conclude that intrinsic electron traps in the perovskite active layers limit the performance of these state-of-the-art hybrid perovskite solar cells.« less

Climate and southern Africa's water-energy-food nexus

NASA Astrophysics Data System (ADS)

Conway, Declan; van Garderen, Emma Archer; Deryng, Delphine; Dorling, Steve; Krueger, Tobias; Landman, Willem; Lankford, Bruce; Lebek, Karen; Osborn, Tim; Ringler, Claudia; Thurlow, James; Zhu, Tingju; Dalin, Carole

2015-09-01

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven, for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and gross domestic product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose: the Southern African Development Community, the Southern African Power Pool and trade of agricultural products amounting to significant transfers of embedded water.

Adaptive electron beam shaping using a photoemission gun and spatial light modulator

DOE PAGES

Maxson, Jared; Lee, Hyeri; Bartnik, Adam C.; ...

2015-02-01

The need for precisely defined beam shapes in photoelectron sources has been well established. In this paper, we use a spatial light modulator and simple shaping algorithm to create arbitrary, detailed transverse laser shapes with high fidelity. We transmit this shaped laser to the photocathode of a high voltage dc gun. Using beam currents where space charge is negligible, and using an imaging solenoid and fluorescent viewscreen, we show that the resultant beam shape preserves these detailed features with similar fidelity. Next, instead of transmitting a shaped laser profile, we use an active feedback on the unshaped electron beam imagemore » to create equally accurate and detailed shapes. We demonstrate that this electron beam feedback has the added advantage of correcting for electron optical aberrations, yielding shapes without skew. The method may serve to provide precisely defined electron beams for low current target experiments, space-charge dominated beam commissioning, as well as for online adaptive correction of photocathode quantum efficiency degradation.« less

A quantitative and spatially resolved analysis of the performance-bottleneck in high efficiency, planar hybrid perovskite solar cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Draguta, Sergiu; Christians, Jeffrey A.; Morozov, Yurii V.

Hybrid perovskites represent a potential paradigm shift for the creation of low-cost solar cells. Current power conversion efficiencies (PCEs) exceed 22%. However, despite this, record PCEs are still far from their theoretical Shockley–Queisser limit of 31%. To increase these PCE values, there is a pressing need to understand, quantify and microscopically model charge recombination processes in full working devices. Here, we present a complete microscopic account of charge recombination processes in high efficiency (18–19% PCE) hybrid perovskite (mixed cation and methylammonium lead iodide) solar cells. We employ diffraction-limited optical measurements along with relevant kinetic modeling to establish, for the firstmore » time, local photoluminescence quantum yields, trap densities, trapping efficiencies, charge extraction efficiencies, quasi-Fermi-level splitting, and effective PCE estimates. Correlations between these spatially resolved parameters, in turn, allow us to conclude that intrinsic electron traps in the perovskite active layers limit the performance of these state-of-the-art hybrid perovskite solar cells.« less

Use of remote sensing, geographic information systems, and spatial statistics to assess spatio-temporal population dynamics of Heterodera glycines and soybean yield quantity and quality

NASA Astrophysics Data System (ADS)

Moreira, Antonio Jose De Araujo

Soybean, Glycine max (L.) Merr., is an important source of oil and protein worldwide, and soybean cyst nematode (SCN), Heterodera glycines, is among the most important yield-limiting factors in soybean production worldwide. Early detection of SCN is difficult because soybean plants infected by SCN often do not exhibit visible symptoms. It was hypothesized, however, that reflectance data obtained by remote sensing from soybean canopies may be used to detect plant stress caused by SCN infection. Moreover, reflectance measurements may be related to soybean growth and yield. Two field experiments were conducted from 2000 to 2002 to study the relationships among reflectance data, quantity and quality of soybean yield, and SCN population densities. The best relationships between reflectance and the quantity of soybean grain yield occurred when reflectance data were obtained late August to early September. Similarly, reflectance was best related to seed oil and seed protein content and seed size when measured during late August/early September. Grain quality-reflectance relationships varied spatially and temporally. Reflectance measured early or late in the season had the best relationships with SCN population densities measured at planting. Soil properties likely affected reflectance measurements obtained at the beginning of the season and somehow may have been related to SCN population densities at planting. Reflectance data obtained at the end of the growing season likely was affected by early senescence of SCN-infected soybeans. Spatio-temporal aspects of SCN population densities in both experiments were assessed using spatial statistics and regression analyses. In the 2000 and 2001 growing seasons, spring-to-fall changes in SCN population densities were best related to SCN population densities at planting for both experiments. However, within-season changes in SCN population densities were best related to SCN population densities at harvest for both experiments in 2002. Variograms were fitted to the data to describe the spatial characteristics of SCN population densities in both fields at planting and at harvest from 2000 to 2003 and these parameters varied within seasons and during overwinter periods in both experiments. Distinct relationships between temporal and spatial changes in SCN population densities were not detected.

Biofilms promote altruism.

PubMed

Kreft, Jan-Ulrich

2004-08-01

The origin of altruism is a fundamental problem in evolution, and the maintenance of biodiversity is a fundamental problem in ecology. These two problems combine with the fundamental microbiological question of whether it is always advantageous for a unicellular organism to grow as fast as possible. The common basis for these three themes is a trade-off between growth rate and growth yield, which in turn is based on irreversible thermodynamics. The trade-off creates an evolutionary alternative between two strategies: high growth yield at low growth rate versus high growth rate at low growth yield. High growth yield at low growth rate is a case of an altruistic strategy because it increases the fitness of the group by using resources economically at the cost of decreased fitness, or growth rate, of the individual. The group-beneficial behaviour is advantageous in the long term, whereas the high growth rate strategy is advantageous in the short term. Coexistence of species requires differences between their niches, and niche space is typically divided into four 'axes' (time, space, resources, predators). This neglects survival strategies based on cooperation, which extend the possibilities of coexistence, arguing for the inclusion of cooperation as the fifth 'axis'. Here, individual-based model simulations show that spatial structure, as in, for example, biofilms, is necessary for the origin and maintenance of this 'primitive' altruistic strategy and that the common belief that growth rate but not yield decides the outcome of competition is based on chemostat models and experiments. This evolutionary perspective on life in biofilms can explain long-known biofilm characteristics, such as the structural organization into microcolonies, the often-observed lack of mixing among microcolonies, and the shedding of single cells, as promoting the origin and maintenance of the altruistic strategy. Whereas biofilms enrich altruists, enrichment cultures, microbiology's paradigm for isolating bacteria into pure culture, select for highest growth rate.

Geoelectrical characterisation of basement aquifers: the case of Iberekodo, southwestern Nigeria

NASA Astrophysics Data System (ADS)

Aizebeokhai, Ahzegbobor P.; Oyeyemi, Kehinde D.

2018-03-01

Basement aquifers, which occur within the weathered and fractured zones of crystalline bedrocks, are important groundwater resources in tropical and subtropical regions. The development of basement aquifers is complex owing to their high spatial variability. Geophysical techniques are used to obtain information about the hydrologic characteristics of the weathered and fractured zones of the crystalline basement rocks, which relates to the occurrence of groundwater in the zones. The spatial distributions of these hydrologic characteristics are then used to map the spatial variability of the basement aquifers. Thus, knowledge of the spatial variability of basement aquifers is useful in siting wells and boreholes for optimal and perennial yield. Geoelectrical resistivity is one of the most widely used geophysical methods for assessing the spatial variability of the weathered and fractured zones in groundwater exploration efforts in basement complex terrains. The presented study focuses on combining vertical electrical sounding with two-dimensional (2D) geoelectrical resistivity imaging to characterise the weathered and fractured zones in a crystalline basement complex terrain in southwestern Nigeria. The basement aquifer was delineated, and the nature, extent and spatial variability of the delineated basement aquifer were assessed based on the spatial variability of the weathered and fractured zones. The study shows that a multiple-gradient array for 2D resistivity imaging is sensitive to vertical and near-surface stratigraphic features, which have hydrological implications. The integration of resistivity sounding with 2D geoelectrical resistivity imaging is efficient and enhances near-surface characterisation in basement complex terrain.

Development of heat and drought related extreme weather events and their effect on winter wheat yields in Germany

NASA Astrophysics Data System (ADS)

Lüttger, Andrea B.; Feike, Til

2018-04-01

Climate change constitutes a major challenge for high productivity in wheat, the most widely grown crop in Germany. Extreme weather events including dry spells and heat waves, which negatively affect wheat yields, are expected to aggravate in the future. It is crucial to improve the understanding of the spatiotemporal development of such extreme weather events and the respective crop-climate relationships in Germany. Thus, the present study is a first attempt to evaluate the historic development of relevant drought and heat-related extreme weather events from 1901 to 2010 on county level (NUTS-3) in Germany. Three simple drought indices and two simple heat stress indices were used in the analysis. A continuous increase in dry spells over time was observed over the investigated periods from 1901-1930, 1931-1960, 1961-1990 to 2001-2010. Short and medium dry spells, i.e., precipitation-free periods longer than 5 and 8 days, respectively, increased more strongly compared to longer dry spells (longer than 11 days). The heat-related stress indices with maximum temperatures above 25 and 28 °C during critical wheat growth phases showed no significant increase over the first three periods but an especially sharp increase in the final 1991-2010 period with the increases being particularly pronounced in parts of Southwestern Germany. Trend analysis over the entire 110-year period using Mann-Kendall test revealed a significant positive trend for all investigated indices except for heat stress above 25 °C during flowering period. The analysis of county-level yield data from 1981 to 2010 revealed declining spatial yield variability and rather constant temporal yield variability over the three investigated (1981-1990, 1991-2000, and 2001-2010) decades. A clear spatial gradient manifested over time with variability in the West being much smaller than in the east of Germany. Correlating yield variability with the previously analyzed extreme weather indices revealed strong spatiotemporal fluctuations in explanatory power of the different indices over all German counties and the three time periods. Over the 30 years, yield deviations were increasingly well correlated with heat and drought-related indices, with the number of days with maximum temperature above 25 °C during anthesis showing a sharp increase in explanatory power over entire Germany in the final 2001-2010 period.

Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data

NASA Astrophysics Data System (ADS)

Kouadio, Louis; Duveiller, Grégory; Djaby, Bakary; El Jarroudi, Moussa; Defourny, Pierre; Tychon, Bernard

2012-08-01

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence rate and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha-1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.

Experimental study on secondary electron emission characteristics of Cu

NASA Astrophysics Data System (ADS)

Liu, Shenghua; Liu, Yudong; Wang, Pengcheng; Liu, Weibin; Pei, Guoxi; Zeng, Lei; Sun, Xiaoyang

2018-02-01

Secondary electron emission (SEE) of a surface is the origin of the multipacting effect which could seriously deteriorate beam quality and even perturb the normal operation of particle accelerators. Experimental measurements on secondary electron yield (SEY) for different materials and coatings have been developed in many accelerator laboratories. In fact, the SEY is just one parameter of secondary electron emission characteristics which include spatial and energy distribution of emitted electrons. A novel experimental apparatus was set up in China Spallation Neutron Source, and an innovative method was applied to obtain the whole characteristics of SEE. Taking Cu as the sample, secondary electron yield, its dependence on beam injection angle, and the spatial and energy distribution of secondary electrons were achieved with this measurement device. The method for spatial distribution measurement was first proposed and verified experimentally. This contribution also tries to give all the experimental results a reasonable theoretical analysis and explanation.

Near-threshold harmonics from a femtosecond enhancement cavity-based EUV source: effects of multiple quantum pathways on spatial profile and yield.

PubMed

Hammond, T J; Mills, Arthur K; Jones, David J

2011-12-05

We investigate the photon flux and far-field spatial profiles for near-threshold harmonics produced with a 66 MHz femtosecond enhancement cavity-based EUV source operating in the tight-focus regime. The effects of multiple quantum pathways in the far-field spatial profile and harmonic yield show a strong dependence on gas jet dynamics, particularly nozzle diameter and position. This simple system, consisting of only a 700 mW Ti:Sapphire oscillator and an enhancement cavity produces harmonics up to 20 eV with an estimated 30-100 μW of power (intracavity) and > 1μW (measured) of power spectrally-resolved and out-coupled from the cavity. While this power is already suitable for applications, a quantum mechanical model of the system indicates substantial improvements should be possible with technical upgrades.

Identifying areas at risk of low birth weight using spatial epidemiology: A small area surveillance study.

PubMed

Insaf, Tabassum Z; Talbot, Thomas

2016-07-01

To assess the geographic distribution of Low Birth Weight (LBW) in New York State among singleton births using a spatial regression approach in order to identify priority areas for public health actions. LBW was defined as birth weight less than 2500g. Geocoded data from 562,586 birth certificates in New York State (years 2008-2012) were merged with 2010 census data at the tract level. To provide stable estimates and maintain confidentiality, data were aggregated to yield 1268 areas of analysis. LBW prevalence among singleton births was related with area-level behavioral, socioeconomic and demographic characteristics using a Poisson mixed effects spatial error regression model. Observed low birth weight showed statistically significant auto-correlation in our study area (Moran's I 0.16 p value 0.0005). After over-dispersion correction and accounting for fixed effects for selected social determinants, spatial autocorrelation was fully accounted for (Moran's I-0.007 p value 0.241). The proportion of LBW was higher in areas with larger Hispanic or Black populations and high smoking prevalence. Smoothed maps with predicted prevalence were developed to identify areas at high risk of LBW. Spatial patterns of residual variation were analyzed to identify unique risk factors. Neighborhood racial composition contributes to disparities in LBW prevalence beyond differences in behavioral and socioeconomic factors. Small-area analyses of LBW can identify areas for targeted interventions and display unique local patterns that should be accounted for in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Visual attention and the apprehension of spatial relations: the case of depth.

PubMed

Moore, C M; Elsinger, C L; Lleras, A

2001-05-01

Several studies have shown that targets defined on the basis of the spatial relations between objects yield highly inefficient visual search performance (e.g., Logan, 1994; Palmer, 1994), suggesting that the apprehension of spatial relations may require the selective allocation of attention within the scene. In the present study, we tested the hypothesis that depth relations might be different in this regard and might support efficient visual search. This hypothesis was based, in part, on the fact that many perceptual organization processes that are believed to occur early and in parallel, such as figure-ground segregation and perceptual completion, seem to depend on the assignment of depth relations. Despite this, however, using increasingly salient cues to depth (Experiments 2-4) and including a separate test of the sufficiency of the most salient depth cue used (Experiment 5), no evidence was found to indicate that search for a target defined by depth relations is any different than search for a target defined by other types of spatial relations, with regard to efficiency of search. These findings are discussed within the context of the larger literature on early processing of three-dimensional characteristics of visual scenes.

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Maize (Zea mays L.) yield response to nitrogen as influenced by spatio-temporal variations of soil-water-topography dynamics

USDA-ARS?s Scientific Manuscript database

Reducing nitrogen (N) loss from agricultural lands and applying N fertilizer at rates that satisfy both economic and environmental objectives is critical for sustainable agricultural management. This study investigated spatial variability in maize yield response to N and its controlling factors alon...

The Effect of Correlated Energetic Disorder on Charge Transport in Organic Semiconductors

NASA Astrophysics Data System (ADS)

Allen, Jonathan; Röding, Sebastian; Cherqui, Charles; Dunlap, David

2012-10-01

In their 1995 paper describing a Monte Carlo simulation for dissociation of an electron-hole pair in the presence of Gaussian energetic disorder, Albrect and Bäassler reported a surprising result. They found that increasing the width σ of the energetic disorder increases the quantum yield φ. They attributed this behavior to the tendency for energy fluctuations to compete against the Coulombic pair attraction, driving the electron-hole pair apart at short distances where, without disorder, recombination would be almost certain. We have expanded upon this notion, and introduced spatial correlation into the energetic disorder. By correlating the energetic disorder, we have demonstrated even larger quantum yields in simulation, attributable to the tendency of correlation to drive the charges further apart spatially than merely random disorder. Our results generally support the findings of Greenham et al. in that a larger correlation radius gives a larger quantum yield. In addition to larger quantum yield, we believe that correlated disorder could be used to create pathways for charge transport within a material, allowing the charge carrier behavior to be tuned.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

Identification and delineation of areas flood hazard using high accuracy of DEM data

NASA Astrophysics Data System (ADS)

Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

2018-05-01

Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

Mediterranean Land Use and Land Cover Classification Assessment Using High Spatial Resolution Data

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2016-10-01

Landscape fragmentation is noticeably practiced in Mediterranean regions and imposes substantial complications in several satellite image classification methods. To some extent, high spatial resolution data were able to overcome such complications. For better classification performances in Land Use Land Cover (LULC) mapping, the current research adopts different classification methods comparison for LULC mapping using Sentinel-2 satellite as a source of high spatial resolution. Both of pixel-based and an object-based classification algorithms were assessed; the pixel-based approach employs Maximum Likelihood (ML), Artificial Neural Network (ANN) algorithms, Support Vector Machine (SVM), and, the object-based classification uses the Nearest Neighbour (NN) classifier. Stratified Masking Process (SMP) that integrates a ranking process within the classes based on spectral fluctuation of the sum of the training and testing sites was implemented. An analysis of the overall and individual accuracy of the classification results of all four methods reveals that the SVM classifier was the most efficient overall by distinguishing most of the classes with the highest accuracy. NN succeeded to deal with artificial surface classes in general while agriculture area classes, and forest and semi-natural area classes were segregated successfully with SVM. Furthermore, a comparative analysis indicates that the conventional classification method yielded better accuracy results than the SMP method overall with both classifiers used, ML and SVM.

A highly distributed Bragg stack with unique geometry provides effective camouflage for Loliginid squid eyes

PubMed Central

Holt, Amanda L.; Sweeney, Alison M.; Johnsen, Sönke; Morse, Daniel E.

2011-01-01

Cephalopods possess a sophisticated array of mechanisms to achieve camouflage in dynamic underwater environments. While active mechanisms such as chromatophore patterning and body posturing are well known, passive mechanisms such as manipulating light with highly evolved reflectors may also play an important role. To explore the contribution of passive mechanisms to cephalopod camouflage, we investigated the optical and biochemical properties of the silver layer covering the eye of the California fishery squid, Loligo opalescens. We discovered a novel nested-spindle geometry whose correlated structure effectively emulates a randomly distributed Bragg reflector (DBR), with a range of spatial frequencies resulting in broadband visible reflectance, making it a nearly ideal passive camouflage material for the depth at which these animals live. We used the transfer-matrix method of optical modelling to investigate specular reflection from the spindle structures, demonstrating that a DBR with widely distributed thickness variations of high refractive index elements is sufficient to yield broadband reflectance over visible wavelengths, and that unlike DBRs with one or a few spatial frequencies, this broadband reflectance occurs from a wide range of viewing angles. The spindle shape of the cells may facilitate self-assembly of a random DBR to achieve smooth spatial distributions in refractive indices. This design lends itself to technological imitation to achieve a DBR with wide range of smoothly varying layer thicknesses in a facile, inexpensive manner. PMID:21325315

A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff; Skalka, Christian

2012-01-01

This invention is designed to ascertain the snow water equivalence (SWE) of snowpacks with better spatial and temporal resolutions than present techniques. The approach is ground-based, as opposed to some techniques that are air-based. In addition, the approach is compact, non-destructive, and can be communicated with remotely, and thus can be deployed in areas not possible with current methods. Presently there are two principal ground-based techniques for obtaining SWE measurements. The first is manual snow core measurements of the snowpack. This approach is labor-intensive, destructive, and has poor temporal resolution. The second approach is to deploy a large (e.g., 3x3 m) snowpillow, which requires significant infrastructure, is potentially hazardous [uses a approximately equal to 200-gallon (approximately equal to 760-L) antifreeze-filled bladder], and requires deployment in a large, flat area. High deployment costs necessitate few installations, thus yielding poor spatial resolution of data. Both approaches have limited usefulness in complex and/or avalanche-prone terrains. This approach is compact, non-destructive to the snowpack, provides high temporal resolution data, and due to potential low cost, can be deployed with high spatial resolution. The invention consists of three primary components: a robust wireless network and computing platform designed for harsh climates, new SWE sensing strategies, and algorithms for smart sampling, data logging, and SWE computation.

Spatial Language Processing in the Blind: Evidence for a Supramodal Representation and Cortical Reorganization

PubMed Central

Struiksma, Marijn E.; Noordzij, Matthijs L.; Neggers, Sebastiaan F. W.; Bosker, Wendy M.; Postma, Albert

2011-01-01

Neuropsychological and imaging studies have shown that the left supramarginal gyrus (SMG) is specifically involved in processing spatial terms (e.g. above, left of), which locate places and objects in the world. The current fMRI study focused on the nature and specificity of representing spatial language in the left SMG by combining behavioral and neuronal activation data in blind and sighted individuals. Data from the blind provide an elegant way to test the supramodal representation hypothesis, i.e. abstract codes representing spatial relations yielding no activation differences between blind and sighted. Indeed, the left SMG was activated during spatial language processing in both blind and sighted individuals implying a supramodal representation of spatial and other dimensional relations which does not require visual experience to develop. However, in the absence of vision functional reorganization of the visual cortex is known to take place. An important consideration with respect to our finding is the amount of functional reorganization during language processing in our blind participants. Therefore, the participants also performed a verb generation task. We observed that only in the blind occipital areas were activated during covert language generation. Additionally, in the first task there was functional reorganization observed for processing language with a high linguistic load. As the visual cortex was not specifically active for spatial contents in the first task, and no reorganization was observed in the SMG, the latter finding further supports the notion that the left SMG is the main node for a supramodal representation of verbal spatial relations. PMID:21935391

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Space based observations: A state of the art solution for spatial monitoring tropical forested watershed productivity at regional scale in developing countries

NASA Astrophysics Data System (ADS)

Mahmud, M. R.

2014-02-01

This paper presents the simplified and operational approach of mapping the water yield in tropical watershed using space-based multi sensor remote sensing data. Two main critical hydrological rainfall variables namely rainfall and evapotranspiration are being estimated by satellite measurement and reinforce the famous Thornthwaite & Mather water balance model. The satellite rainfall and ET estimates were able to represent the actual value on the ground with accuracy under considerable conditions. The satellite derived water yield had good agreement and relation with actual streamflow. A high bias measurement may result due to; i) influence of satellite rainfall estimates during heavy storm, and ii) large uncertainties and standard deviation of MODIS temperature data product. The output of this study managed to improve the regional scale of hydrology assessment in Peninsular Malaysia.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

Ecosystem services of human-dominated watersheds and land use influences: a case study from the Dianchi Lake watershed in China.

PubMed

Hou, Ying; Li, Bo; Müller, Felix; Chen, Weiping

2016-11-01

Watersheds provide multiple ecosystem services. Ecosystem service assessment is a promising approach to investigate human-environment interaction at the watershed scale. The spatial characteristics of ecosystem services are closely related to land use statuses in human-dominated watersheds. This study aims to investigate the effects of land use on the spatial variations of ecosystem services at the Dianchi Lake watershed in Southwest China. We investigated the spatial variations of six ecosystem services-food supply, net primary productivity (NPP), habitat quality, evapotranspiration, water yield, and nitrogen retention. These services were selected based on their significance at the Dianchi Lake watershed and the availability of their data. The quantification of these services was based on modeling, value transference, and spatial analysis in combination with biophysical and socioeconomic data. Furthermore, we calculated the values of ecosystem services provided by different land use types and quantified the correlations between ecosystem service values and land use area proportions. The results show considerable spatial variations in the six ecosystem services associated with land use influences in the Dianchi Lake watershed. The cropland and forest land use types had predominantly positive influences on food productivity and NPP, respectively. The rural residential area and forest land use types reduced and enhanced habitat quality, respectively; these influences were identical to those of evapotranspiration. Urban area and rural residential area exerted significantly positive influences on water yield. In contrast, water yield was negatively correlated with forest area proportion. Finally, cropland and forest had significantly positive and negative influences, respectively, on nitrogen retention. Our study emphasizes the importance of consideration of the influences from land use composition and distribution on ecosystem services for managing the ecosystems of human-dominated watersheds.

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).

PubMed

Gavaret, M; Maillard, L; Jung, J

2015-03-01

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG) allow the recording of spontaneous or evoked electromagnetic brain activity with excellent temporal resolution. Data must be recorded with high temporal resolution (sampling rate) and high spatial resolution (number of channels). Data analyses are based on several steps with selection of electromagnetic signals, elaboration of a head model and use of algorithms in order to solve the inverse problem. Due to considerable technical advances in spatial resolution, these tools now represent real methods of ElectroMagnetic Source Imaging. HR-EEG and MEG constitute non-invasive and complementary examinations, characterized by distinct sensitivities according to the location and orientation of intracerebral generators. In the presurgical assessment of drug-resistant partial epilepsies, HR-EEG and MEG can characterize and localize interictal activities and thus the irritative zone. HR-EEG and MEG often yield significant additional data that are complementary to other presurgical investigations and particularly relevant in MRI-negative cases. Currently, the determination of the epileptogenic zone and functional brain mapping remain rather less well-validated indications. In France, in 2014, HR-EEG is now part of standard clinical investigation of epilepsy, while MEG remains a research technique. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Spatial Characteristics of the Unsteady Differential Pressures on 16 percent F/A-18 Vertical Tails

NASA Technical Reports Server (NTRS)

Moses, Robert W.; Ashley, Holt

1998-01-01

Buffeting is an aeroelastic phenomenon which plagues high performance aircraft at high angles of attack. For the F/A-18 at high angles of attack, vortices emanating from wing/fuselage leading edge extensions burst, immersing the vertical tails in their turbulent wake. The resulting buffeting of the vertical tails is a concern from fatigue and inspection points of view. Previous flight and wind-tunnel investigations to determine the buffet loads on the tail did not provide a complete description of the spatial characteristics of the unsteady differential pressures. Consequently, the unsteady differential pressures were considered to be fully correlated in the analyses of buffet and buffeting. The use of fully correlated pressures in estimating the generalized aerodynamic forces for the analysis of buffeting yielded responses that exceeded those measured in flight and in the wind tunnel. To learn more about the spatial characteristics of the unsteady differential pressures, an available 16%, sting-mounted, F-18 wind-tunnel model was modified and tested in the Transonic Dynamics Tunnel (TDT) at the NASA Langley Research Center as part of the ACROBAT (Actively Controlled Response Of Buffet-Affected Tails) program. Surface pressures were measured at high angles of attack on flexible and rigid tails. Cross-correlation and cross-spectral analyses of the pressure time histories indicate that the unsteady differential pressures are not fully correlated. In fact, the unsteady differential pressure resemble a wave that travels along the tail. At constant angle of attack, the pressure correlation varies with flight speed.

Spatial Aspects of Interspecific Competition

NASA Technical Reports Server (NTRS)

Durrett, Rick; Levin, Simon

1998-01-01

Using several variants of a stochastic spatial model introduced by Silvertown et al., we investigate the effect of spatial distribution of individuals on the outcome of competition. First, we prove rigorously that if one species has a competitive advantage over each of the others, then eventually it takes over all the sites in the system. Second, we examine tradeoffs between competition and dispersal distance in a two-species system. Third, we consider a cyclic competitive relationship between three types. In this case, a nonspatial treatment leads to densities that follow neutrally stable cycles or even unstable spiral solutions, while a spatial model yields a stationary distribution with an interesting spatial structure.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Midwest agriculture and ENSO: A comparison of AVHRR NDVI3g data and crop yields in the United States Corn Belt from 1982 to 2014

NASA Astrophysics Data System (ADS)

Glennie, Erin; Anyamba, Assaf

2018-06-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) data were compared to National Agricultural Statistics Service (NASS) corn yield data in the United States Corn Belt from 1982 to 2014. The main objectives of the comparison were to assess 1) the consistency of regional Corn Belt responses to El Niño/Southern Oscillation (ENSO) teleconnection signals, and 2) the reliability of using NDVI as an indicator of crop yield. Regional NDVI values were used to model a seasonal curve and to define the growing season - May to October. Seasonal conditions in each county were represented by NDVI and land surface temperature (LST) composites, and corn yield was represented by average annual bushels produced per acre. Correlation analysis between the NDVI, LST, corn yield, and equatorial Pacific sea surface temperature anomalies revealed patterns in land surface dynamics and corn yield, as well as typical impacts of ENSO episodes. It was observed from the study that growing seasons coincident with La Niña events were consistently warmer, but El Niño events did not consistently impact NDVI, temperature, or corn yield data. Moreover, the El Niño and La Niña composite images suggest that impacts vary spatially across the Corn Belt. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be attributed to soy crops and other background interference. The overall correlation between the total growing season NDVI anomaly and detrended corn yield was 0.61(p = 0.00013), though the strength of the relationship varies across the Corn Belt.

Science highlights from MAVEN/IUVS after two years in Mars Orbit

NASA Astrophysics Data System (ADS)

Schneider, N. M.; Deighan, J.; Stiepen, A.; Jain, S.; Lefèvre, F.; Stevens, M. H.; Gröller, H.; Yelle, R. V.; Lo, D.; Evans, J. S.; Stewart, I. F.; Chaffin, M.; Crismani, M. M. J.; Mayyasi, M.; McClintock, W. E.; Holsclaw, G.; Clarke, J. T.; Montmessin, F.; Jakosky, B. M.

2016-12-01

The broad capabilities of the Imaging UltraViolet Spectrograph on the MAVEN mission are enabling new science ranging from Mars' lower atmosphere up though the escaping corona. After two years in Mars orbit, the instrument has yielded insights on present-day processes at Mars including dayglow, nightglow, aurora, meteor showers, clouds, and solar-planetary interactions. In this presentation we will highlight several new discoveries in the mesosphere and below. First, spatial mapping of nitric oxide nightglow reveals regions of atmospheric downwelling necessitating substantial changes to global atmospheric circulation models. Second, a new high-spatial-resolution UV imaging mode allows detection of clouds from nadir to limb and their local time evolution, as well as unprecedented determinations of Mars' low-altitude ozone. Finally, IUVS has obtained hundreds of stellar occultation profiles probing atmospheric structure, composition, waves and tides.

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence.

PubMed

Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S

2003-12-21

Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS4), Photofrin meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelength (mu(a,x,f)) was recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining mu(a,x,f) independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS4 and TPPS4 were calculated to be 0.59 +/- 0.03 and 0.121 +/- 0.001 respectively using the point source model, and 0.63 +/- 0.03 and 0.129 +/- 0.002 using the pencil beam excitation model. These results are consistent with published values.

Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain

NASA Astrophysics Data System (ADS)

Chen, Chao; Baethgen, Walter E.; Wang, Enli; Yu, Qiang

2011-12-01

Grain yields of wheat and maize were obtained from national statistics and simulated with an agricultural system model to investigate the effects of historical climate variability and irrigation on crop yield in the North China Plain (NCP). Both observed and simulated yields showed large temporal and spatial variability due to variations in climate and irrigation supply. Wheat yield under full irrigation (FI) was 8 t ha-1 or higher in 80% of seasons in the north, it ranged from 7 to 10 t ha-1 in 90% of seasons in central NCP, and less than 9 t ha-1 in 85% of seasons in the south. Reduced irrigation resulted in increased crop yield variability. Wheat yield under supplemental irrigation, i.e., to meet only 50% of irrigation water requirement [supplemental irrigation (SI)] ranged from 2.7 to 8.8 t ha-1 with the maximum frequency of seasons having the range of 4-6 t ha-1 in the north, 4-7 t ha-1 in central NCP, and 5-8 t ha-1 in the south. Wheat yield under no irrigation (NI) was lower than 1 t ha-1 in about 50% of seasons. Considering the NCP as a whole, simulated maize yield under FI ranged from 3.9 to 11.8 t ha-1 with similar frequency distribution in the range of 6-11.8 t ha-1 with the interval of 2 t ha-1. It ranged from 0 to 11.8 t ha-1, uniformly distributed into the range of 4-10 t ha-1 under SI, and NI. The results give an insight into the levels of regional crop production affected by climate and water management strategies.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Modeling suspended sediment sources and transport in the Ishikari River basin, Japan, using SPARROW

NASA Astrophysics Data System (ADS)

Duan, W. L.; He, B.; Takara, K.; Luo, P. P.; Nover, D.; Hu, M. C.

2015-03-01

It is important to understand the mechanisms that control the fate and transport of suspended sediment (SS) in rivers, because high suspended sediment loads have significant impacts on riverine hydroecology. In this study, the SPARROW (SPAtially Referenced Regression on Watershed Attributes) watershed model was applied to estimate the sources and transport of SS in surface waters of the Ishikari River basin (14 330 km2), the largest watershed in Hokkaido, Japan. The final developed SPARROW model has four source variables (developing lands, forest lands, agricultural lands, and stream channels), three landscape delivery variables (slope, soil permeability, and precipitation), two in-stream loss coefficients, including small streams (streams with drainage area < 200 km2) and large streams, and reservoir attenuation. The model was calibrated using measurements of SS from 31 monitoring sites of mixed spatial data on topography, soils and stream hydrography. Calibration results explain approximately 96% (R2) of the spatial variability in the natural logarithm mean annual SS flux (kg yr-1) and display relatively small prediction errors at the 31 monitoring stations. Results show that developing land is associated with the largest sediment yield at around 1006 kg km-2 yr-1, followed by agricultural land (234 kg km-2 yr-1). Estimation of incremental yields shows that 35% comes from agricultural lands, 23% from forested lands, 23% from developing lands, and 19% from stream channels. The results of this study improve our understanding of sediment production and transportation in the Ishikari River basin in general, which will benefit both the scientific and management communities in safeguarding water resources.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Spatial Interpolation of Aerosol Optical Depth Pollution: Comparison of Methods for the Development of Aerosol Distribution

NASA Astrophysics Data System (ADS)

Safarpour, S.; Abdullah, K.; Lim, H. S.; Dadras, M.

2017-09-01

Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellites, for the 10 years period of 2000 - 2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer and winter and ordinary kriging yielded the best results for fall.

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

USGS Publications Warehouse

Morin, Dana J.; Fuller, Angela K.; Royle, J. Andrew; Sutherland, Chris

2017-01-01

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Assessment of the Spatial and Temporal Variations of Water Quality for Agricultural Lands with Crop Rotation in China by Using a HYPE Model

PubMed Central

Yin, Yunxing; Jiang, Sanyuan; Pers, Charlotta; Yang, Xiaoying; Liu, Qun; Yuan, Jin; Yao, Mingxing; He, Yi; Luo, Xingzhang; Zheng, Zheng

2016-01-01

Many water quality models have been successfully used worldwide to predict nutrient losses from anthropogenically impacted catchments, but hydrological and nutrient simulations with limited data are difficult considering the transfer of model parameters and complication of model calibration and validation. This study aims: (i) to assess the performance capabilities of a new and relatively more advantageous model, namely, Hydrological Predictions for the Environment (HYPE), that simulates stream flow and nutrient load in agricultural areas by using a multi-site and multi-objective parameter calibration method and (ii) to investigate the temporal and spatial variations of total nitrogen (TN) and total phosphorous (TP) concentrations and loads with crop rotation by using the model for the first time. A parameter estimation tool (PEST) was used to calibrate parameters. Results show that the parameters related to the effective soil porosity were highly sensitive to hydrological modeling. N balance was largely controlled by soil denitrification processes. P balance was influenced by the sedimentation rate and production/decay of P in rivers and lakes. The model reproduced the temporal and spatial variations of discharge and TN/TP relatively well in both calibration (2006–2008) and validation (2009–2010) periods. Among the obtained data, the lowest Nash-Suttclife efficiency of discharge, daily TN load, and daily TP load were 0.74, 0.51, and 0.54, respectively. The seasonal variations of daily TN concentrations in the entire simulation period were insufficient, indicated that crop rotation changed the timing and amount of N output. Monthly TN and TP simulation yields revealed that nutrient outputs were abundant in summer in terms of the corresponding discharge. The area-weighted TN and TP load annual yields in five years showed that nutrient loads were extremely high along Hong and Ru rivers, especially in agricultural lands. PMID:26999184

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Adaptive hyperspectral imager: design, modeling, and control

NASA Astrophysics Data System (ADS)

McGregor, Scot; Lacroix, Simon; Monmayrant, Antoine

2015-08-01

An adaptive, hyperspectral imager is presented. We propose a system with easily adaptable spectral resolution, adjustable acquisition time, and high spatial resolution which is independent of spectral resolution. The system yields the possibility to define a variety of acquisition schemes, and in particular near snapshot acquisitions that may be used to measure the spectral content of given or automatically detected regions of interest. The proposed system is modelled and simulated, and tests on a first prototype validate the approach to achieve near snapshot spectral acquisitions without resorting to any computationally heavy post-processing, nor cumbersome calibration

The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; De La Beaujardiere, J.-F.; Fan, Yuhong; Leka, K. D.; Mcclymont, A. N.; Metcalf, Thomas R.; Mickey, Donald L.; Wuelser, Jean-Pierre; Lites, Bruce W.

1993-01-01

Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.

Spatial Statistical Data Fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Nguyen, Hai

2010-01-01

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).

Optical design and development of a snapshot light-field laryngoscope

NASA Astrophysics Data System (ADS)

Zhu, Shuaishuai; Jin, Peng; Liang, Rongguang; Gao, Liang

2018-02-01

The convergence of recent advances in optical fabrication and digital processing yields a generation of imaging technology-light-field (LF) cameras which bridge the realms of applied mathematics, optics, and high-performance computing. Herein for the first time, we introduce the paradigm of LF imaging into laryngoscopy. The resultant probe can image the three-dimensional shape of vocal folds within a single camera exposure. Furthermore, to improve the spatial resolution, we developed an image fusion algorithm, providing a simple solution to a long-standing problem in LF imaging.

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

Essential climatic variables estimation with satellite imagery

NASA Astrophysics Data System (ADS)

Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

2016-12-01

According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

Resolution Enhancement in PET Reconstruction Using Collimation

NASA Astrophysics Data System (ADS)

Metzler, Scott D.; Matej, Samuel; Karp, Joel S.

2013-02-01

Collimation can improve both the spatial resolution and sampling properties compared to the same scanner without collimation. Spatial resolution improves because each original crystal can be conceptually split into two (i.e., doubling the number of in-plane crystals) by masking half the crystal with a high-density attenuator (e.g., tungsten); this reduces coincidence efficiency by 4× since both crystals comprising the line of response (LOR) are masked, but yields 4× as many resolution-enhanced (RE) LORs. All the new RE LORs can be measured by scanning with the collimator in different configurations.In this simulation study, the collimator was assumed to be ideal, neither allowing gamma penetration nor truncating the field of view. Comparisons were made in 2D between an uncollimated small-animal system with 2-mm crystals that were assumed to be perfectly absorbing and the same system with collimation that narrowed the effective crystal size to 1 mm. Digital phantoms included a hot-rod and a single-hot-spot, both in a uniform background with activity ratio of 4:1. In addition to the collimated and uncollimated configurations, angular and spatial wobbling acquisitions of the 2-mm case were also simulated. Similarly, configurations with different combinations of the RE LORs were considered including (i) all LORs, (ii) only those parallel to the 2-mm LORs; and (iii) only cross pairs that are not parallel to the 2-mm LORs. Lastly, quantitative studies were conducted for collimated and uncollimated data using contrast recovery coefficient and mean-squared error (MSE) as metrics. The reconstructions show that for most noise levels there is a substantial improvement in image quality (i.e., visual quality, resolution, and a reduction in artifacts) by using collimation even when there are 4 fewer counts or-in some cases-comparing with the noiseless uncollimated reconstruction. By comparing various configurations of sampling, the results show that it is the matched combination of both improved spatial resolution of each LOR and the increase in the number of LORs that yields improved reconstructions. Further, the quantitative studies show that for low-count scans, the collimated data give better MSE for small lesions and the uncollimated data give better MSE for larger lesions; for highcount studies, the collimated data yield better quantitative values for the entire range of lesion sizes that were evaluated.

Daily monitoring of 30 m crop condition over complex agricultural landscapes

NASA Astrophysics Data System (ADS)

Sun, L.; Gao, F.; Xie, D.; Anderson, M. C.; Yang, Y.

2017-12-01

Crop progress provides information necessary for efficient irrigation, scheduling fertilization and harvesting operations at optimal times for achieving higher yields. In the United States, crop progress reports are released online weekly by US Department of Agriculture (USDA) - National Agricultural Statistics Service (NASS). However, the ground data collection is time consuming and subjective, and these reports are provided at either district (multiple counties) or state level. Remote sensing technologies have been widely used to map crop conditions, to extract crop phenology, and to predict crop yield. However, for current satellite-based sensors, it is difficult to acquire both high spatial resolution and frequent coverage. For example, Landsat satellites are capable to capture 30 m resolution images, while the long revisit cycles, cloud contamination further limited their use in detecting rapid surface changes. On the other hand, MODIS can provide daily observations, but with coarse spatial resolutions range from 250 to 1000 m. In recent years, multi-satellite data fusion technology such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used to combine the spatial resolution of Landsat with the temporal frequency of MODIS. It has been found that this synthetic dataset could provide more valuable information compared to the images acquired from only one single sensor. However, accuracy of STARFM depends on heterogeneity of landscape and available clear image pairs of MODIS and Landsat. In this study, a new fusion method was developed using the crop vegetation index (VI) timeseries extracted from "pure" MODIS pixels and Landsat overpass images to generate daily 30 m VI for crops. The fusion accuracy was validated by comparing to the original Landsat images. Results show that the relative error in non-rapid growing period is around 3-5% and in rapid growing period is around 6-8% . The accuracy is much better than that of STARFM which is 4-9% in non-rapid growing period and 10-16% in rapid growing period based on 13 image pairs. The predicted VI from this approach looks consistent and smooth in the SLC-off gap stripes of Landsat 7 ETM+ image. The new fusion results will be used to map crop phenology and to predict crop yield at field scale in the complex agricultural landscapes.

Quantitative analysis of L-edge white line intensities: the influence of saturation and transverse coherence.

PubMed

Hahlin, A; Karis, O; Brena, B; Dunn, J H; Arvantis, D

2001-03-01

We have performed x-ray absorption spectroscopy at the Fe, Ni, and Co L2,3 edges of in situ grown thin magnetic films. We compare electron yield measurements performed at SSRL and BESSY-I. Differences in the L2,3 white line intensities are found for all three elements, comparing data from the two facilities. We propose a correlation between spectral intensities and the degree of spatial coherence of the exciting radiation. The electron yield saturation effects are stronger for light with a higher degree of spatial coherence. Therefore the observed, coherence related, intensity variations are due to an increase in the absorption coefficient, and not to secondary channel related effects.

Very high spatial resolution two-dimensional solar spectroscopy with video CCDs

NASA Technical Reports Server (NTRS)

Johanneson, A.; Bida, T.; Lites, B.; Scharmer, G. B.

1992-01-01

We have developed techniques for recording and reducing spectra of solar fine structure with complete coverage of two-dimensional areas at very high spatial resolution and with a minimum of seeing-induced distortions. These new techniques permit one, for the first time, to place the quantitative measures of atmospheric structure that are afforded only by detailed spectral measurements into their proper context. The techniques comprise the simultaneous acquisition of digital spectra and slit-jaw images at video rates as the solar scene sweeps rapidly by the spectrograph slit. During data processing the slit-jaw images are used to monitor rigid and differential image motion during the scan, allowing measured spectrum properties to be remapped spatially. The resulting quality of maps of measured properties from the spectra is close to that of the best filtergrams. We present the techniques and show maps from scans over pores and small sunspots obtained at a resolution approaching 1/3 arcsec in the spectral region of the magnetically sensitive Fe I lines at 630.15 and 630.25 nm. The maps shown are of continuum intensity and calibrated Doppler velocity. More extensive spectral inversion of these spectra to yield the strength of the magnetic field and other parameters is now underway, and the results of that analysis will be presented in a following paper.

Escherichia coli sampling reliability at a frequently closed Chicago beach: monitoring and management implications

USGS Publications Warehouse

Whitman, Richard L.; Nevers, Meredith B.

2004-01-01

Monitoring beaches for recreational water quality is becoming more common, but few sampling designs or policy approaches have evaluated the efficacy of monitoring programs. The authors intensively sampled water for E. coli (N=1770) at 63rd Street Beach, Chicago for 6 months in 2000 in order to (1) characterize spatial-temporal trends, (2) determine between and within transect variation, and (3) estimate sample size requirements and determine sampling reliability.E. coli counts were highly variable within and between sampling sites but spatially and diurnally autocorrelated. Variation in counts decreased with water depth and time of day. Required number of samples was high for 70% precision around the critical closure level (i.e., 6 within or 24 between transect replicates). Since spatial replication may be cost prohibitive, composite sampling is an alternative once sources of error have been well defined. The results suggest that beach monitoring programs may be requiring too few samples to fulfill management objectives desired. As the recreational water quality national database is developed, it is important that sampling strategies are empirically derived from a thorough understanding of the sources of variation and the reliability of collected data. Greater monitoring efficacy will yield better policy decisions, risk assessments, programmatic goals, and future usefulness of the information.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

Global motion compensated visual attention-based video watermarking

NASA Astrophysics Data System (ADS)

Oakes, Matthew; Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking.

A wide field-of-view imaging DOAS instrument for continuous trace gas mapping from aircraft

NASA Astrophysics Data System (ADS)

Schönhardt, A.; Altube, P.; Gerilowski, K.; Krautwurst, S.; Hartmann, J.; Meier, A. C.; Richter, A.; Burrows, J. P.

2014-04-01

For the purpose of trace gas measurements and pollution mapping, the Airborne imaging DOAS instrument for Measurements of Atmospheric Pollution (AirMAP) has been developed, characterised and successfully operated from aircraft. From the observations with the AirMAP instrument nitrogen dioxide (NO2) columns were retrieved. A major benefit of the pushbroom imaging instrument is the spatially continuous, gap-free measurement sequence independent of flight altitude, a valuable characteristic for mapping purposes. This is made possible by the use of a frame-transfer detector. With a wide-angle entrance objective, a broad field-of-view across track of around 48° is achieved, leading to a swath width of about the same size as the flight altitude. The use of fibre coupled light intake optics with sorted light fibres allows flexible positioning within the aircraft and retains the very good imaging capabilities. The measurements yield ground spatial resolutions below 100 m. From a maximum of 35 individual viewing directions (lines of sight, LOS) represented by 35 single fibres, the number of viewing directions is adapted to each situation by averaging according to signal-to-noise or spatial resolution requirements. Exploitation of all the viewing directions yields observations at 30 m spatial resolution, making the instrument a suitable tool for mapping trace gas point sources and small scale variability. For accurate spatial mapping the position and aircraft attitude are taken into account using the Attitude and Heading Reference System of the aircraft. A first demonstration mission using AirMAP was undertaken. In June 2011, AirMAP has been operated on the AWI Polar-5 aircraft in the framework of the AIRMETH2011 campaign. During a flight above a medium sized coal-fired power plant in North-West Germany, AirMAP clearly detects the emission plume downwind from the exhaust stack, with NO2 vertical columns around 2 × 1016 molecules cm-2 in the plume center. The emission estimates are consistent with reports in the pollutant transfer register. Strong spatial gradients and variability in NO2 amounts across and along flight direction are observed, and small-scale enhancements of NO2 above a motorway are detected. The present study reports on the experimental setup and characteristics of AirMAP, and the first measurements at high spatial resolution and wide spatial coverage are presented which meet the requirements for NO2 mapping to observe and account for the intrinsic variability of tropospheric NO2.

Switching to switchgrass: Pathways and consequences of bioenergy switchgrass entering the Midwestern landscape

NASA Astrophysics Data System (ADS)

Krohn, Brian

The US has the ambitious goal of producing 60 billion liters of cellulosic biofuel by 2022. Researchers and US Federal Agencies have identified switchgrass (Panicum virgatum L.) as a potential feedstock for next generation biofuels to help meet this goal because of its excellent agronomic and environmental characteristics. With national policy supporting the development of a switchgrass to bioenergy industry two key questions arise: 1) Under what economic and political conditions will switchgrass enter the landscape? 2) Where on the landscape will switchgrass be cultivated given varying economic and political conditions? The goal of this dissertation is to answer these questions by analyzing the adoption of switchgrass across the upper Midwestern US at a high spatial resolution (30m) under varying economic conditions. In the first chapter, I model switchgrass yields at a high resolution and find considerable variability in switchgrass yields across space, scale, time, and nitrogen management. Then in the second chapter, I use the spatial results from chapter one to challenge the assumption that low-input (unmanaged) switchgrass systems cannot compete economically with high-input (managed) switchgrass systems. Finally, in the third chapter, I evaluate the economic and land quality conditions required for switchgrass to be competitive with a corn/soy rotation. I find that switchgrass can displace low-yielding corn/soy on environmentally sensitive land but, to be competitive, it requires economic support through payments for ecosystem services equal to 360 ha-1. With a total expenditure of 4.3 billion annually for ecosystem services, switchgrass could displace corn/soy on 12.2 million hectares of environmentally sensitive land and increase ethanol production above that from the existing corn by 20 billion liters. Thus, ecosystem services can be an effective means of meeting both bioenergy and environmental goals. Taking the three chapters in aggregate it is apparent that switchgrass faces many challenges before it will be adopted on the landscape and it is unlikely it will be adopted under traditional market pricing. However, switchgrass does have considerable potential to help meet the US's bioenergy and environmental goals through new mechanisms, such as payments for ecosystem services potentially coupled with low-input management systems.

Volumetric 3D display using a DLP projection engine

NASA Astrophysics Data System (ADS)

Geng, Jason

2012-03-01

In this article, we describe a volumetric 3D display system based on the high speed DLPTM (Digital Light Processing) projection engine. Existing two-dimensional (2D) flat screen displays often lead to ambiguity and confusion in high-dimensional data/graphics presentation due to lack of true depth cues. Even with the help of powerful 3D rendering software, three-dimensional (3D) objects displayed on a 2D flat screen may still fail to provide spatial relationship or depth information correctly and effectively. Essentially, 2D displays have to rely upon capability of human brain to piece together a 3D representation from 2D images. Despite the impressive mental capability of human visual system, its visual perception is not reliable if certain depth cues are missing. In contrast, volumetric 3D display technologies to be discussed in this article are capable of displaying 3D volumetric images in true 3D space. Each "voxel" on a 3D image (analogous to a pixel in 2D image) locates physically at the spatial position where it is supposed to be, and emits light from that position toward omni-directions to form a real 3D image in 3D space. Such a volumetric 3D display provides both physiological depth cues and psychological depth cues to human visual system to truthfully perceive 3D objects. It yields a realistic spatial representation of 3D objects and simplifies our understanding to the complexity of 3D objects and spatial relationship among them.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

A Critical Test of Temporal and Spatial Accuracy of the Tobii T60XL Eye Tracker

ERIC Educational Resources Information Center

Morgante, James D.; Zolfaghari, Rahman; Johnson, Scott P.

2012-01-01

Infant eye tracking is becoming increasingly popular for its presumed precision relative to traditional looking time paradigms and potential to yield new insights into developmental processes. However, there is strong reason to suspect that the temporal and spatial resolution of popular eye tracking systems is not entirely accurate, potentially…

Integrating geospatial data and cropping system simulation within a geographic information system to analyze spatial seed cotton yield, water use, and irrigation requirements

USDA-ARS?s Scientific Manuscript database

The development of sensors that provide geospatial information on crop and soil conditions has been a primary success for precision agriculture. However, further developments are needed to integrate geospatial data into computer algorithms that spatially optimize crop production while considering po...

Spatial-spectral characterization of focused spatially chirped broadband laser beams.

PubMed

Greco, Michael J; Block, Erica; Meier, Amanda K; Beaman, Alex; Cooper, Samuel; Iliev, Marin; Squier, Jeff A; Durfee, Charles G

2015-11-20

Proper alignment is critical to obtain the desired performance from focused spatially chirped beams, for example in simultaneous spatial and temporal focusing (SSTF). We present a simple technique for inspecting the beam paths and focusing conditions for the spectral components of a broadband beam. We spectrally resolve the light transmitted past a knife edge as it was scanned across the beam at several axial positions. The measurement yields information about spot size, M2, and the propagation paths of different frequency components. We also present calculations to illustrate the effects of defocus aberration on SSTF beams.

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Yibo; Xiao, Jingfeng; Ju, Weimin; Xu, Ke; Zhou, Yanlian; Zhao, Yuntai

2016-09-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China’s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation ‘greening’ and ‘browning’ on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate.

Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

NASA Astrophysics Data System (ADS)

Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

2018-04-01

Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

Integrating High Resolution Water Footprint and GIS for Promoting Water Efficiency in the Agricultural Sector: A Case Study of Plantation Crops in the Jordan Valley

PubMed Central

Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit

2016-01-01

Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000–2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts. PMID:28018408

Integrating High Resolution Water Footprint and GIS for Promoting Water Efficiency in the Agricultural Sector: A Case Study of Plantation Crops in the Jordan Valley.

PubMed

Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit

2016-01-01

Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000-2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts.

Vine vigor components and its variability - relationship to wine composition

NASA Astrophysics Data System (ADS)

Lafontaine, Magali; Tittmann, Susanne; Stoll, Manfred

2015-04-01

It was pointed out that a high spatial variability for canopy size and yield would exist within a vineyard but a high temporal stability over the years was observed. Furthermore, a greater variability in grape phenolics than in sugars and pH was detected within a vineyard. But the link between remote sensing indices and quality parameters of grapes is still unclear. Indeed, though in red grape varieties anthocyanins content was spatially negatively correlated to vigor parameters, it seemed that yield, Normalized Difference Vegetation Index (NDVI) and Plant Cell Density (PCD) indices were poorly correlated. Moreover, the link to quality parameters of wines remains uncertain. It was shown that more vigorous vines would lead to wines with less tannins while anthocyanins in wines would be highest when the vines were balanced but the question is if vine size or architecture, yield or nitrogen assimilation would play major contribution to those differences. The general scope of our project was to provide further knowledge on the relationship between vigor parameters and wine composition and relate these to the information gained by remote sensing. Variability in a 0.15 ha vineyard of Pinot noir planted in 2003 and grafted on SO4 rootstock at Geisenheim (Germany) was followed. Vine vigor was assessed manually for each of the 400 vines (cane number, pruning weight, trunk diameter) together with yield parameters (number of bunches per vine, crop yield). Leaf composition was assessed with a hand-held optical sensor (Multiplex3® [Mx3] (Force-A, Orsay, France) based on chlorophyll fluorescence screening providing information on leaf chlorophyll (SFR_G) and nitrogen (NBI_G) content. A micro-scale winemaking of single vines with a 3 factorial design on yield (L low, M middle, H high), SFRG (L, M, H) and canopy size (pruning weight, trunk diameter) (L, M, H) was performed for 2013 and 2014 to completely reflect variability. Wine tannin concentration represented the highest variability with a 11 fold concentration range (50-550 mg CE L-1) while variability of anthocyanins was lower with a 3 fold concentration range (90-250 mg M3OG L-1). The results showed that differences in leaf chlorophyll (SFR_G) would represent the most important factor influencing wine phenolic composition. Measurements of soil resistivity based on ARP technique (Geocarta, Paris, France), leaf composition with a mounted Multiplex providing information on porosity (NFI), biomass (BIOMASS) and chlorophyll (BISFR) together with NDVI assessed by geo-X8000 (geo-konzept-Gesellschaft für Umweltplanungssysteme mbH, Adelschlag, Germany) were performed. Grapes and berry composition was also assessed with Mx3 providing information on anthocyanins (ANTH, FERARI) and sugar (SFR_R) variability. In a second step, vines similar in size (trunk diameter and cane number) and similar yield (number of bunches per vines) were divided in 3 groups differing in leaf SFR_G. A larger scale winemaking (150kg) showed that with increasing SFR_G, Pinot noir wine typicity decreased together with anthocyanin concentration while tannin concentration increased. A better understanding of vineyard variability for targeted management or harvest would allow better understanding to produce and select fruit to a favored wine style.

Q-plates as higher order polarization controllers for orbital angular momentum modes of fiber.

PubMed

Gregg, P; Mirhosseini, M; Rubano, A; Marrucci, L; Karimi, E; Boyd, R W; Ramachandran, S

2015-04-15

We demonstrate that a |q|=1/2 plate, in conjunction with appropriate polarization optics, can selectively and switchably excite all linear combinations of the first radial mode order |l|=1 orbital angular momentum (OAM) fiber modes. This enables full mapping of free-space polarization states onto fiber vector modes, including the radially (TM) and azimuthally polarized (TE) modes. The setup requires few optical components and can yield mode purities as high as ∼30  dB. Additionally, just as a conventional fiber polarization controller creates arbitrary elliptical polarization states to counteract fiber birefringence and yield desired polarizations at the output of a single-mode fiber, q-plates disentangle degenerate state mixing effects between fiber OAM states to yield pure states, even after long-length fiber propagation. We thus demonstrate the ability to switch dynamically, potentially at ∼GHz rates, between OAM modes, or create desired linear combinations of them. We envision applications in fiber-based lasers employing vector or OAM mode outputs, as well as communications networking schemes exploiting spatial modes for higher dimensional encoding.

Measurement of the secondary electron emission from CVD diamond films using phosphor screen detectors

NASA Astrophysics Data System (ADS)

Vaz, R.; May, P. W.; Fox, N. A.; Harwood, C. J.; Chatterjee, V.; Smith, J. A.; Horsfield, C. J.; Lapington, J. S.; Osbourne, S.

2015-03-01

Diamond-based photomultipliers have the potential to provide a significant improvement over existing devices due to diamond's high secondary electron yield and narrow energy distribution of secondary electrons which improves energy resolution creating extremely fast response times. In this paper we describe an experimental apparatus designed to study secondary electron emission from diamond membranes only 400 nm thick, observed in reflection and transmission configurations. The setup consists of a system of calibrated P22 green phosphor screens acting as radiation converters which are used in combination with photomultiplier tubes to acquire secondary emission yield data from the diamond samples. The superior signal voltage sampling of the phosphor screen setup compared with traditional Faraday Cup detection allows the variation in the secondary electron yield across the sample to be visualised, allowing spatial distributions to be obtained. Preliminary reflection and transmission yield data are presented as a function of primary electron energy for selected CVD diamond films and membranes. Reflection data were also obtained from the same sample set using a Faraday Cup detector setup. In general, the curves for secondary electron yield versus primary energy for both measurement setups were comparable. On average a 15-20% lower signal was recorded on our setup compared to the Faraday Cup, which was attributed to the lower photoluminescent efficiency of the P22 phosphor screens when operated at sub-kilovolt bias voltages.

A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

NASA Astrophysics Data System (ADS)

Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

2015-12-01

Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

Edge technique lidar for high accuracy, high spatial resolution wind measurement in the Planetary Boundary Layer

NASA Technical Reports Server (NTRS)

Korb, C. L.; Gentry, Bruce M.

1995-01-01

The goal of the Army Research Office (ARO) Geosciences Program is to measure the three dimensional wind field in the planetary boundary layer (PBL) over a measurement volume with a 50 meter spatial resolution and with measurement accuracies of the order of 20 cm/sec. The objective of this work is to develop and evaluate a high vertical resolution lidar experiment using the edge technique for high accuracy measurement of the atmospheric wind field to meet the ARO requirements. This experiment allows the powerful capabilities of the edge technique to be quantitatively evaluated. In the edge technique, a laser is located on the steep slope of a high resolution spectral filter. This produces large changes in measured signal for small Doppler shifts. A differential frequency technique renders the Doppler shift measurement insensitive to both laser and filter frequency jitter and drift. The measurement is also relatively insensitive to the laser spectral width for widths less than the width of the edge filter. Thus, the goal is to develop a system which will yield a substantial improvement in the state of the art of wind profile measurement in terms of both vertical resolution and accuracy and which will provide a unique capability for atmospheric wind studies.

Towards spatially constrained gust models

NASA Astrophysics Data System (ADS)

Bos, René; Bierbooms, Wim; van Bussel, Gerard

2014-06-01

With the trend of moving towards 10-20 MW turbines, rotor diameters are growing beyond the size of the largest turbulent structures in the atmospheric boundary layer. As a consequence, the fully uniform transients that are commonly used to predict extreme gust loads are losing their connection to reality and may lead to gross overdimensioning. More suiting would be to represent gusts by advecting air parcels and posing certain physical constraints on size and position. However, this would introduce several new degrees of freedom that significantly increase the computational burden of extreme load prediction. In an attempt to elaborate on the costs and benefits of such an approach, load calculations were done on the DTU 10 MW reference turbine where a single uniform gust shape was given various spatial dimensions with the transverse wavelength ranging up to twice the rotor diameter (357 m). The resulting loads displayed a very high spread, but remained well under the level of a uniform gust. Moving towards spatially constrained gust models would therefore yield far less conservative, though more realistic predictions at the cost of higher computation time.

Automated feature extraction and spatial organization of seafloor pockmarks, Belfast Bay, Maine, USA

USGS Publications Warehouse

Andrews, Brian D.; Brothers, Laura L.; Barnhardt, Walter A.

2010-01-01

Seafloor pockmarks occur worldwide and may represent millions of m3 of continental shelf erosion, but few numerical analyses of their morphology and spatial distribution of pockmarks exist. We introduce a quantitative definition of pockmark morphology and, based on this definition, propose a three-step geomorphometric method to identify and extract pockmarks from high-resolution swath bathymetry. We apply this GIS-implemented approach to 25 km2 of bathymetry collected in the Belfast Bay, Maine USA pockmark field. Our model extracted 1767 pockmarks and found a linear pockmark depth-to-diameter ratio for pockmarks field-wide. Mean pockmark depth is 7.6 m and mean diameter is 84.8 m. Pockmark distribution is non-random, and nearly half of the field's pockmarks occur in chains. The most prominent chains are oriented semi-normal to the steepest gradient in Holocene sediment thickness. A descriptive model yields field-wide spatial statistics indicating that pockmarks are distributed in non-random clusters. Results enable quantitative comparison of pockmarks in fields worldwide as well as similar concave features, such as impact craters, dolines, or salt pools.

Multi-Scale Modeling to Improve Single-Molecule, Single-Cell Experiments

NASA Astrophysics Data System (ADS)

Munsky, Brian; Shepherd, Douglas

2014-03-01

Single-cell, single-molecule experiments are producing an unprecedented amount of data to capture the dynamics of biological systems. When integrated with computational models, observations of spatial, temporal and stochastic fluctuations can yield powerful quantitative insight. We concentrate on experiments that localize and count individual molecules of mRNA. These high precision experiments have large imaging and computational processing costs, and we explore how improved computational analyses can dramatically reduce overall data requirements. In particular, we show how analyses of spatial, temporal and stochastic fluctuations can significantly enhance parameter estimation results for small, noisy data sets. We also show how full probability distribution analyses can constrain parameters with far less data than bulk analyses or statistical moment closures. Finally, we discuss how a systematic modeling progression from simple to more complex analyses can reduce total computational costs by orders of magnitude. We illustrate our approach using single-molecule, spatial mRNA measurements of Interleukin 1-alpha mRNA induction in human THP1 cells following stimulation. Our approach could improve the effectiveness of single-molecule gene regulation analyses for many other process.

Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication.

PubMed

Kelly, Simon P; Lalor, Edmund C; Reilly, Richard B; Foxe, John J

2005-06-01

The steady-state visual evoked potential (SSVEP) has been employed successfully in brain-computer interface (BCI) research, but its use in a design entirely independent of eye movement has until recently not been reported. This paper presents strong evidence suggesting that the SSVEP can be used as an electrophysiological correlate of visual spatial attention that may be harnessed on its own or in conjunction with other correlates to achieve control in an independent BCI. In this study, 64-channel electroencephalography data were recorded from subjects who covertly attended to one of two bilateral flicker stimuli with superimposed letter sequences. Offline classification of left/right spatial attention was attempted by extracting SSVEPs at optimal channels selected for each subject on the basis of the scalp distribution of SSVEP magnitudes. This yielded an average accuracy of approximately 71% across ten subjects (highest 86%) comparable across two separate cases in which flicker frequencies were set within and outside the alpha range respectively. Further, combining SSVEP features with attention-dependent parieto-occipital alpha band modulations resulted in an average accuracy of 79% (highest 87%).

Functional Geometry Alignment and Localization of Brain Areas.

PubMed

Langs, Georg; Golland, Polina; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J

2010-01-01

Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.

Spatial analysis of falls in an urban community of Hong Kong

PubMed Central

Lai, Poh C; Low, Chien T; Wong, Martin; Wong, Wing C; Chan, Ming H

2009-01-01

Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh) and Standard Deviational Ellipse (SDE) techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies. PMID:19291326

A high-resolution genetic signature of demographic and spatial expansion in epizootic rabies virus

PubMed Central

Biek, Roman; Henderson, J. Caroline; Waller, Lance A.; Rupprecht, Charles E.; Real, Leslie A.

2007-01-01

Emerging pathogens potentially undergo rapid evolution while expanding in population size and geographic range during the course of invasion, yet it is generally difficult to demonstrate how these processes interact. Our analysis of a 30-yr data set covering a large-scale rabies virus outbreak among North American raccoons reveals the long lasting effect of the initial infection wave in determining how viral populations are genetically structured in space. We further find that coalescent-based estimates derived from the genetic data yielded an amazingly accurate reconstruction of the known spatial and demographic dynamics of the virus over time. Our study demonstrates the combined evolutionary and population dynamic processes characterizing the spread of pathogen after its introduction into a fully susceptible host population. Furthermore, the results provide important insights regarding the spatial scale of rabies persistence and validate the use of coalescent approaches for uncovering even relatively complex population histories. Such approaches will be of increasing relevance for understanding the epidemiology of emerging zoonotic diseases in a landscape context. PMID:17470818

A small-area study of environmental risk assessment of outdoor falls.

PubMed

Lai, Poh-Chin; Wong, Wing-Cheung; Low, Chien-Tat; Wong, Martin; Chan, Ming-Houng

2011-12-01

Falls in public places are an issue of great health concern especially for the elderly. Falls among the elderly is also a major health burden in many countries. This study describes a spatial approach to assess environmental causes of outdoor falls using a small urban community in Hong Kong as an example. The method involves collecting data on fall occurrences and mapping their geographic positions to examine circumstances and environmental evidence that contribute to falls. High risk locations or hot spots of falls are identified on the bases of spatial proximity and concentration of falls within a threshold distance by means of kernel smoothing and standard deviational ellipses. This method of geographic aggregation of individual fall incidents for a small-area study yields hot spots of manageable sizes. The spatial clustering approach is effective in two ways. Firstly, it allows visualisation and isolation of fall hot spots to draw focus. Secondly and especially under conditions of resource decline, policy makers are able to target specific locations to examine the underlying causal mechanisms and strategise effective response and preventive measures based on the types of environmental risk factors identified.

Comparison of SPI and SPEI applicability for drought impact assessment on crop production in the Danubian Lowland and the East Slovakian Lowland

NASA Astrophysics Data System (ADS)

Labudová, L.; Labuda, M.; Takáč, J.

2017-04-01

Drought belongs among the main impact factors considering crop yields. Therefore, this paper is focused on the assessment of drought occurrence and intensity as well as on its impact on crop yields on the Danubian and the East Slovakian lowlands with the spatial resolution at district level. Yield data were the main limitation of the study, which resulted in the limited length of the assessed period (1996-2013). The standardized yields of ten crops (winter wheat, spring wheat, winter barley, spring barley, rye, maize, potatoes, oilseed rape, sunflower, and sugar beet) were correlated with monthly, 2-, and 3-monthly standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI). For this purpose, the common significance level of alpha = 0.05 was used. The temporal evolution of both indices and drought occurrence during the period 1961-2013 were assessed for each district. Most crops show a higher correlation with the SPEI than with the SPI in contrast to potatoes, which reached a higher significant correlation using the SPI. The correlation also increases with increasing number of months within a time step. The highest correlation can be seen between maize and the 3-monthly SPEI in August representing summer precipitation and potential evapotranspiration conditions. Furthermore, a very high correlation was recorded considering sugar beet, which is influenced mainly by summer precipitation, because the correlation coefficient between the sugar beet and the 3-monthly SPI is as high as using the 3-monthly SPEI. Crop yields in the East Slovakian Lowland do not seem to be influenced by wet/dry periods identified using the SPI and the SPEI as their correlation with both indices is quite low and insignificant.

Nitrogen Fertilization Elevated Spatial Heterogeneity of Soil Microbial Biomass Carbon and Nitrogen in Switchgrass and Gamagrass Croplands

NASA Astrophysics Data System (ADS)

Jian, S.; Li, J.; Guo, C.; Hui, D.; Deng, Q.; Yu, C. L.; Dzantor, K. E.; Lane, C.

2017-12-01

Nitrogen (N) fertilizers are widely used to increase bioenergy crop yield but intensive fertilizations on spatial distributions of soil microbial processes in bioenergy croplands remains unknown. To quantify N fertilization effect on spatial heterogeneity of soil microbial biomass carbon (MBC) and N (MBN), we sampled top mineral horizon soils (0-15cm) using a spatially explicit design within two 15-m2 plots under three fertilization treatments in two bioenergy croplands in a three-year long fertilization experiment in Middle Tennessee, USA. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The two crops were switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.). Results showed that N fertilizations little altered central tendencies of microbial variables but relative to LN, HN significantly increased MBC and MBC:MBN (GG only). HN possessed the greatest within-plot variances except for MBN (GG only). Spatial patterns were generally evident under HN and LN plots and much less so under NN plots. Substantially contrasting spatial variations were also identified between croplands (GG>SG) and among variables (MBN, MBC:MBN > MBC). No significant correlations were identified between soil pH and microbial variables. This study demonstrated that spatial heterogeneity is elevated in microbial biomass of fertilized soils likely by uneven fertilizer application, the nature of soil microbial communities and bioenergy crops. Future researchers should better match sample sizes with the heterogeneity of soil microbial property (i.e. MBN) in bioenergy croplands.

Contemporary suspended sediment dynamics within two partly glacierized mountain drainage basins in western Norway (Erdalen and Bødalen, inner Nordfjord)

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Laute, Katja; Storms, Joep E. A.

2017-06-01

This paper focuses on environmental controls, spatiotemporal variability and rates of contemporary fluvial suspended sediment transport in the neighboring, partly glacierized and steep Erdalen (79.5 km2) and Bødalen (60.1 km2) drainage basins in the fjord landscape of the inner Nordfjord in western Norway. Field work, including extended samplings and measurements, was conducted since 2004 in Erdalen and since 2008 in Bødalen. The distinct intra- and inter-annual temporal variability of suspended sediment transport found is mostly controlled by meteorological events, with most suspended sediment transport occurring during pluvial events in autumn (September-November), followed by mostly thermally determined glacier melt in summer (July-August), and by mostly thermally determined snowmelt in spring (April-June). Extreme rainfall events (> 70 mm d- 1) in autumn can trigger significant debris-flow activity that can cause significant transfers of suspended sediments from ice-free surface areas with sedimentary covers into main stream channels and is particularly important for fluvial suspended sediment transport. In years with occurring relevant debris-flow activity the total annual drainage-basin wide suspended sediment yields are strongly determined by these single extreme events. The proportion of glacier coverage, followed by steepness of slopes, and degree of vegetation cover in ice-free surface areas with sedimentary covers are the main controls for the detected spatial variability of suspended sediment yields. The contemporary sediment supply from glacierized surface areas and the Jostedalsbreen ice cap through different defined outlet glaciers shows a high spatial variability. The fact that the mean annual suspended sediment yield of Bødalen is with 31.3 t km- 2 yr- 1 almost twice as high as the mean annual suspended sediment yield of Erdalen (16.4 t km- 2 yr- 1) is to a large extent explained by the higher proportion of glacier coverage in Bødalen (38% of the drainage basin surface area) as compared to Erdalen (18% of the drainage basin surface area) and by a significantly higher sediment yield from the glacierized area of the Bødalen drainage basin compared to the glacierized surface area in Erdalen. When looking at the total annual mass of suspended sediments being fluvially exported from both entire drainage basin systems, the total amount of suspended sediments coming from the ice-free drainage basin surface areas altogether dominates over the total amount of suspended sediments coming from the glacierized surface area of both drainage basins. Drainage-basin wide annual suspended sediment yields are rather low when compared with yields of other partly glacierized drainage basin systems in Norway and in other cold climate environments worldwide, which is mainly due to the high resistance of the predominant gneisses towards glacial erosion and weathering, the altogether only small amounts of sediments being available within the entire drainage basin systems, the stable and nearly closed vegetation cover in the ice-free surface areas with sedimentary covers, and the efficiency of proglacial lakes in trapping sediments supplied by defined outlet glaciers. Both contemporary and long-term suspended sediment yields are altogether supply-limited. Contemporary suspended sediment transport accounts for nearly two-thirds of the total fluvial transport and, accordingly, plays an important role within the sedimentary budgets of the entire Erdalen and Bødalen drainage basins.

A compartmental-spatial system dynamics approach to ground water modeling.

PubMed

Roach, Jesse; Tidwell, Vince

2009-01-01

High-resolution, spatially distributed ground water flow models can prove unsuitable for the rapid, interactive analysis that is increasingly demanded to support a participatory decision environment. To address this shortcoming, we extend the idea of multiple cell (Bear 1979) and compartmental (Campana and Simpson 1984) ground water models developed within the context of spatial system dynamics (Ahmad and Simonovic 2004) for rapid scenario analysis. We term this approach compartmental-spatial system dynamics (CSSD). The goal is to balance spatial aggregation necessary to achieve a real-time integrative and interactive decision environment while maintaining sufficient model complexity to yield a meaningful representation of the regional ground water system. As a test case, a 51-compartment CSSD model was built and calibrated from a 100,0001 cell MODFLOW (McDonald and Harbaugh 1988) model of the Albuquerque Basin in central New Mexico (McAda and Barroll 2002). Seventy-seven percent of historical drawdowns predicted by the MODFLOW model were within 1 m of the corresponding CSSD estimates, and in 80% of the historical model run years the CSSD model estimates of river leakage, reservoir leakage, ground water flow to agricultural drains, and riparian evapotranspiration were within 30% of the corresponding estimates from McAda and Barroll (2002), with improved model agreement during the scenario period. Comparisons of model results demonstrate both advantages and limitations of the CCSD model approach.

DOE Office of Scientific and Technical Information (OSTI.GOV)

D. Muth, Jr.; K. M. Bryden; R. G. Nelson

This study provides a spatially comprehensive assessment of sustainable agricultural residue removal potential across the United States. Earlier assessments determining the quantity of agricultural residue that could be sustainably removed for bioenergy production at the regional and national scale faced a number of computational limitations. These limitations included the number of environmental factors, the number of land management scenarios, and the spatial fidelity and spatial extent of the assessment. This study utilizes integrated multi-factor environmental process modeling and high fidelity land use datasets to perform a spatially comprehensive assessment of sustainably removable agricultural residues across the conterminous United States. Soilmore » type represents the base spatial unit for this study and is modeled using a national soil survey database at the 10 – 100 m scale. Current crop rotation practices are identified by processing land cover data available from the USDA National Agricultural Statistics Service Cropland Data Layer database. Land management and residue removal scenarios are identified for each unique crop rotation and crop management zone. Estimates of county averages and state totals of sustainably available agricultural residues are provided. The results of the assessment show that in 2011 over 150 million metric tons of agricultural residues could have been sustainably removed across the United States. Projecting crop yields and land management practices to 2030, the assessment determines that over 207 million metric tons of agricultural residues will be able to be sustainably removed for bioenergy production at that time.« less

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Interferometric CO observations of the ultraluminous IRAS galaxies ARP 220, IC 694/NGC 3690, NGC 6420 and NGC 7469

NASA Technical Reports Server (NTRS)

Sargent, A. I.; Sanders, D. B.; Scoville, N. Z.; Soifer, B. T.

1987-01-01

High resolution CO observations of the IRAS galaxies Arp 220, IC 694/NGC 3690, NGC 6240 and NGC 7469 were made with the Millimeter Wave Interferometer of the Owen Valley Radio Observatory. These yield spatial information on scales of 1 to 5 kpc and allow the separation of compact condensations from the more extended emission in the galaxies. In the case of the obviously interacting system IC 694/NGC 3690 the contributions of each component can be discerned. For that galaxy, and also for Arp 220, the unusually high lumonisities may be produced by nonthermal processes rather than by intense bursts of star formation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Southern Medical University, Guangzhou, Guangdong; Shen, C

Purpose: Multi-energy computed tomography (MECT) is an emerging application in medical imaging due to its ability of material differentiation and potential for molecular imaging. In MECT, image correlations at different spatial and channels exist. It is desirable to incorporate these correlations in reconstruction to improve image quality. For this purpose, this study proposes a MECT reconstruction technique that employes spatial spectral non-local means (ssNLM) regularization. Methods: We consider a kVp-switching scanning method in which source energy is rapidly switched during data acquisition. For each energy channel, this yields projection data acquired at a number of angles, whereas projection angles amongmore » channels are different. We formulate the reconstruction task as an optimziation problem. A least square term enfores data fidelity. A ssNLM term is used as regularization to encourage similarities among image patches at different spatial locations and channels. When comparing image patches at different channels, intensity difference were corrected by a transformation estimated via histogram equalization during the reconstruction process. Results: We tested our method in a simulation study with a NCAT phantom and an experimental study with a Gammex phantom. For comparison purpose, we also performed reconstructions using conjugate-gradient least square (CGLS) method and conventional NLM method that only considers spatial correlation in an image. ssNLM is able to better suppress streak artifacts. The streaks are along different projection directions in images at different channels. ssNLM discourages this dissimilarity and hence removes them. True image structures are preserved in this process. Measurements in regions of interests yield 1.1 to 3.2 and 1.5 to 1.8 times higher contrast to noise ratio than the NLM approach. Improvements over CGLS is even more profound due to lack of regularization in the CGLS method and hence amplified noise. Conclusion: The proposed ssNLM method for kVp-switching MECT reconstruction can achieve high quality MECT images.« less

Valuing investments in sustainable land management using an integrated modelling framework to support a watershed conservation scheme in the Upper Tana River, Kenya

NASA Astrophysics Data System (ADS)

Hunink, Johannes E.; Bryant, Benjamin P.; Vogl, Adrian; Droogers, Peter

2015-04-01

We analyse the multiple impacts of investments in sustainable land use practices on ecosystem services in the Upper Tana basin (Kenya) to support a watershed conservation scheme (a "water fund"). We apply an integrated modelling framework, building on previous field-based and modelling studies in the basin, and link biophysical outputs to economic benefits for the main actors in the basin. The first step in the modelling workflow is the use of a high-resolution spatial prioritization tool (Resource Investment Optimization System -- RIOS) to allocate the type and location of conservation investments in the different subbasins, subject to budget constraints and stakeholder concerns. We then run the Soil and Water Assessment Tool (SWAT) using the RIOS-identified investment scenarios to produce spatially explicit scenarios that simulate changes in water yield and suspended sediment. Finally, in close collaboration with downstream water users (urban water supply and hydropower) we link those biophysical outputs to monetary metrics, including: reduced water treatment costs, increased hydropower production, and crop yield benefits for upstream farmers in the conservation area. We explore how different budgets and different spatial targeting scenarios influence the return of the investments and the effectiveness of the water fund scheme. This study is novel in that it presents an integrated analysis targeting interventions in a decision context that takes into account local environmental and socio-economic conditions, and then relies on detailed, process-based, biophysical models to demonstrate the economic return on those investments. We conclude that the approach allows for an analysis on different spatial and temporal scales, providing conclusive evidence to stakeholders and decision makers on the contribution and benefits of the land-based investments in this basin. This is serving as foundational work to support the implementation of the Upper Tana-Nairobi Water Fund, a public-private partnership to safeguard ecosystem service provision and food security.

Crop-ecology and nutritional variability influence growth and secondary metabolites of Stevia rebaudiana Bertoni.

PubMed

Pal, Probir Kumar; Kumar, Rajender; Guleria, Vipan; Mahajan, Mitali; Prasad, Ramdeen; Pathania, Vijaylata; Gill, Baljinder Singh; Singh, Devinder; Chand, Gopi; Singh, Bikram; Singh, Rakesh Deosharan; Ahuja, Paramvir Singh

2015-02-27

Plant nutrition and climatic conditions play important roles on the growth and secondary metabolites of stevia (Stevia rebaudiana Bertoni); however, the nutritional dose is strongly governed by the soil properties and climatic conditions of the growing region. In northern India, the interactive effects of crop ecology and plant nutrition on yield and secondary metabolites of stevia are not yet properly understood. Thus, a field experiment comprising three levels of nitrogen, two levels of phosphorus and three levels of potassium was conducted at three locations to ascertain whether the spatial and nutritional variability would dominate the leaf yield and secondary metabolites profile of stevia. Principal component analysis (PCA) indicates that the applications of 90 kg N, 40 kg P2O5 and 40 kg K2O ha-1 are the best nutritional conditions in terms of dry leaf yield for CSIR-IHBT (Council of Scientific and Industrial Research- Institute Himalayan Bioresource Technology) and RHRS (Regional Horticultural Research Station) conditions. The spatial variability also exerted considerable effect on the leaf yield and stevioside content in leaves. Among the three locations, CSIR-IHBT was found most suitable in case of dry leaf yield and secondary metabolites accumulation in leaves. The results suggest that dry leaf yield and accumulation of stevioside are controlled by the environmental factors and agronomic management; however, the accumulation of rebaudioside-A (Reb-A) is not much influenced by these two factors. Thus, leaf yield and secondary metabolite profiles of stevia can be improved through the selection of appropriate growing locations and proper nutrient management.

High spatial variability in biogeochemical rates and microbial communities across Louisiana salt marsh landscapes

NASA Astrophysics Data System (ADS)

Roberts, B. J.; Chelsky, A.; Bernhard, A. E.; Giblin, A. E.

2017-12-01

Salt marshes are important sites for retention and transformation of carbon and nutrients. Much of our current marsh biogeochemistry knowledge is based on sampling at times and in locations that are convenient, most often vegetated marsh platforms during low tide. Wetland loss rates are high in many coastal regions including Louisiana which has the highest loss rates in the US. This loss not only reduces total marsh area but also changes the relative allocation of subhabitats in the remaining marsh. Climate and other anthropogenic changes lead to further changes including inundation patterns, redox conditions, salinity regimes, and shifts in vegetation patterns across marsh landscapes. We present results from a series of studies examining biogeochemical rates, microbial communities, and soil properties along multiple edge to interior transects within Spartina alterniflora across the Louisiana coast; between expanding patches of Avicennia germinans and adjacent S. alterniflora marshes; in soils associated with the four most common Louisiana salt marsh plants species; and across six different marsh subhabitats. Spartina alterniflora marsh biogeochemistry and microbial populations display high spatial variability related to variability in soil properties which appear to be, at least in part, regulated by differences in elevation, hydrology, and redox conditions. Differences in rates between soils associated with different vegetation types were also related to soil properties with S. alterniflora soils often yielding the lowest rates. Biogeochemical process rates vary significantly across marsh subhabitats with individual process rates differing in their hotspot habitat(s) across the marsh. Distinct spatial patterns may influence the roles that marshes play in retaining and transforming nutrients in coastal regions and highlight the importance of incorporating spatial sampling when scaling up plot level measurements to landscape or regional scales.

Modeling Reef Fish Biomass, Recovery Potential, and Management Priorities in the Western Indian Ocean.

PubMed

McClanahan, Timothy R; Maina, Joseph M; Graham, Nicholas A J; Jones, Kendall R

2016-01-01

Fish biomass is a primary driver of coral reef ecosystem services and has high sensitivity to human disturbances, particularly fishing. Estimates of fish biomass, their spatial distribution, and recovery potential are important for evaluating reef status and crucial for setting management targets. Here we modeled fish biomass estimates across all reefs of the western Indian Ocean using key variables that predicted the empirical data collected from 337 sites. These variables were used to create biomass and recovery time maps to prioritize spatially explicit conservation actions. The resultant fish biomass map showed high variability ranging from ~15 to 2900 kg/ha, primarily driven by human populations, distance to markets, and fisheries management restrictions. Lastly, we assembled data based on the age of fisheries closures and showed that biomass takes ~ 25 years to recover to typical equilibrium values of ~1200 kg/ha. The recovery times to biomass levels for sustainable fishing yields, maximum diversity, and ecosystem stability or conservation targets once fishing is suspended was modeled to estimate temporal costs of restrictions. The mean time to recovery for the whole region to the conservation target was 8.1(± 3SD) years, while recovery to sustainable fishing thresholds was between 0.5 and 4 years, but with high spatial variation. Recovery prioritization scenario models included one where local governance prioritized recovery of degraded reefs and two that prioritized minimizing recovery time, where countries either operated independently or collaborated. The regional collaboration scenario selected remote areas for conservation with uneven national responsibilities and spatial coverage, which could undermine collaboration. There is the potential to achieve sustainable fisheries within a decade by promoting these pathways according to their social-ecological suitability.

Modeling Reef Fish Biomass, Recovery Potential, and Management Priorities in the Western Indian Ocean

PubMed Central

McClanahan, Timothy R.; Maina, Joseph M.; Graham, Nicholas A. J.; Jones, Kendall R.

2016-01-01

Fish biomass is a primary driver of coral reef ecosystem services and has high sensitivity to human disturbances, particularly fishing. Estimates of fish biomass, their spatial distribution, and recovery potential are important for evaluating reef status and crucial for setting management targets. Here we modeled fish biomass estimates across all reefs of the western Indian Ocean using key variables that predicted the empirical data collected from 337 sites. These variables were used to create biomass and recovery time maps to prioritize spatially explicit conservation actions. The resultant fish biomass map showed high variability ranging from ~15 to 2900 kg/ha, primarily driven by human populations, distance to markets, and fisheries management restrictions. Lastly, we assembled data based on the age of fisheries closures and showed that biomass takes ~ 25 years to recover to typical equilibrium values of ~1200 kg/ha. The recovery times to biomass levels for sustainable fishing yields, maximum diversity, and ecosystem stability or conservation targets once fishing is suspended was modeled to estimate temporal costs of restrictions. The mean time to recovery for the whole region to the conservation target was 8.1(± 3SD) years, while recovery to sustainable fishing thresholds was between 0.5 and 4 years, but with high spatial variation. Recovery prioritization scenario models included one where local governance prioritized recovery of degraded reefs and two that prioritized minimizing recovery time, where countries either operated independently or collaborated. The regional collaboration scenario selected remote areas for conservation with uneven national responsibilities and spatial coverage, which could undermine collaboration. There is the potential to achieve sustainable fisheries within a decade by promoting these pathways according to their social-ecological suitability. PMID:27149673

Experimental comparison of high-density scintillators for EMCCD-based gamma ray imaging

NASA Astrophysics Data System (ADS)

Heemskerk, Jan W. T.; Kreuger, Rob; Goorden, Marlies C.; Korevaar, Marc A. N.; Salvador, Samuel; Seeley, Zachary M.; Cherepy, Nerine J.; van der Kolk, Erik; Payne, Stephen A.; Dorenbos, Pieter; Beekman, Freek J.

2012-07-01

Detection of x-rays and gamma rays with high spatial resolution can be achieved with scintillators that are optically coupled to electron-multiplying charge-coupled devices (EMCCDs). These can be operated at typical frame rates of 50 Hz with low noise. In such a set-up, scintillation light within each frame is integrated after which the frame is analyzed for the presence of scintillation events. This method allows for the use of scintillator materials with relatively long decay times of a few milliseconds, not previously considered for use in photon-counting gamma cameras, opening up an unexplored range of dense scintillators. In this paper, we test CdWO4 and transparent polycrystalline ceramics of Lu2O3:Eu and (Gd,Lu)2O3:Eu as alternatives to currently used CsI:Tl in order to improve the performance of EMCCD-based gamma cameras. The tested scintillators were selected for their significantly larger cross-sections at 140 keV (99mTc) compared to CsI:Tl combined with moderate to good light yield. A performance comparison based on gamma camera spatial and energy resolution was done with all tested scintillators having equal (66%) interaction probability at 140 keV. CdWO4, Lu2O3:Eu and (Gd,Lu)2O3:Eu all result in a significantly improved spatial resolution over CsI:Tl, albeit at the cost of reduced energy resolution. Lu2O3:Eu transparent ceramic gives the best spatial resolution: 65 µm full-width-at-half-maximum (FWHM) compared to 147 µm FWHM for CsI:Tl. In conclusion, these ‘slow’ dense scintillators open up new possibilities for improving the spatial resolution of EMCCD-based scintillation cameras.

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

PubMed Central

Tsai, Yu Hsin; Stow, Douglas; Weeks, John

2013-01-01

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst) outperformed the true object-based feature delineation approach (ENVI Feature Extraction) due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00). The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change. PMID:24415810

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

Sahelian rangeland response to changes in rainfall over two decades in the Gourma region, Mali

NASA Astrophysics Data System (ADS)

Hiernaux, Pierre; Mougin, Eric; Diarra, Lassine; Soumaguel, Nogmana; Lavenu, François; Tracol, Yann; Diawara, Mamadou

2009-08-01

SummaryTwenty-five rangeland sites were monitored over two decades (1984-2006) first to assess the impact of the 1983-1984 droughts on fodder resources, then to better understand ecosystem functioning and dynamics. Sites are sampled along the south-north bioclimatic gradient in Gourma (Mali), within three main edaphic situations: sandy, loamy-clay and shallow soils. In addition, three levels of grazing pressure where systematically sampled within sandy soils. Located at the northern edge of the area reached by the West African monsoon, the Gourma gradient has recorded extremes in inter-annual variations of rainfall and resulting variations in vegetation growth. Following rainfall variability, inter-annual variability of herbaceous yield increases as climate gets dryer with latitudes at least on the sandy soils sites. Local redistribution of rainfall explains the high patchiness of herbaceous vegetation, especially on shallow soils. Yet spatial heterogeneity of the vegetation does not buffer between year yield variability that increases with spatial heterogeneity. At short term, livestock grazing during the wet season affects plant growth and thus yield in direction and proportions that vary with the timing and intensity of grazing. In the longer term, grazing also impinges upon species composition in many ways. Hence, long histories of heavy grazing promote either long cycle annuals refused by livestock or else short cycle good quality feed species. Primary production is maintained or even increased in the case of refusal such as Sida cordifolia, and is lessened in the case of short cycle species such as Zornia glochidiata. These behaviours explain that the yield anomalies calculated for the rangelands on sandy soils relative to the yield of site less grazed under similar climate tend to be negative in northern Sahel where the scenario of short cycle species dominates, while yield anomalies are close to nil in centre Sahel and slightly positive in South Sahel where the refusal scenario is more frequent. Because grazing promotes short cycle species, grazed rangelands respond faster to droughts. Year to year changes in species composition are abrupt as expected from the transient soil seed stock. However, some decadal trends in species composition are identified, with a wave of pioneer species following the 1983-1984 droughts, and a more progressive diversification and return to typical Sahel flora from 1992 onwards.

Spatio-Temporal Dynamics of Maize Yield Water Constraints under Climate Change in Spain

PubMed Central

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent “hot-spots” in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity. PMID:24878747

Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.

PubMed

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Sediment reallocations due to erosive rainfall events in the Three Gorges Reservoir Area, Central China

NASA Astrophysics Data System (ADS)

Stumpf, Felix; Goebes, Philipp; Schmidt, Karsten; Schindewolf, Marcus; Schönbrodt-Stitt, Sarah; Wadoux, Alexandre; Xiang, Wei; Scholten, Thomas

2017-04-01

Soil erosion by water outlines a major threat to the Three Gorges Reservoir Area in China. A detailed assessment of soil conservation measures requires a tool that spatially identifies sediment reallocations due to rainfall-runoff events in catchments. We applied EROSION 3D as a physically based soil erosion and deposition model in a small mountainous catchment. Generally, we aim to provide a methodological frame that facilitates the model parametrization in a data scarce environment and to identify sediment sources and deposits. We used digital soil mapping techniques to generate spatially distributed soil property information for parametrization. For model calibration and validation, we continuously monitored the catchment on rainfall, runoff and sediment yield for a period of 12 months. The model performed well for large events (sediment yield>1 Mg) with an averaged individual model error of 7.5%, while small events showed an average error of 36.2%. We focused on the large events to evaluate reallocation patterns. Erosion occurred in 11.1% of the study area with an average erosion rate of 49.9Mgha 1. Erosion mainly occurred on crop rotation areas with a spatial proportion of 69.2% for 'corn-rapeseed' and 69.1% for 'potato-cabbage'. Deposition occurred on 11.0%. Forested areas (9.7%), infrastructure (41.0%), cropland (corn-rapeseed: 13.6%, potatocabbage: 11.3%) and grassland (18.4%) were affected by deposition. Because the vast majority of annual sediment yields (80.3%) were associated to a few large erosive events, the modelling approach provides a useful tool to spatially assess soil erosion control and conservation measures.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale

PubMed Central

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2018-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage. PMID:29888751

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale.

PubMed

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage.

Patterns of land use, extensification, and intensification of Brazilian agriculture.

PubMed

Dias, Lívia C P; Pimenta, Fernando M; Santos, Ana B; Costa, Marcos H; Ladle, Richard J

2016-08-01

Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940-2012) and productivity (1990-2012) in Brazil using a new high-resolution (approximately 1 km(2) ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making. © 2016 John Wiley & Sons Ltd.

A wavefront reconstruction method for 3-D cylindrical subsurface radar imaging.

PubMed

Flores-Tapia, Daniel; Thomas, Gabriel; Pistorius, Stephen

2008-10-01

In recent years, the use of radar technology has been proposed in a wide range of subsurface imaging applications. Traditionally, linear scan trajectories are used to acquire data in most subsurface radar applications. However, novel applications, such as breast microwave imaging and wood inspection, require the use of nonlinear scan trajectories in order to adjust to the geometry of the scanned area. This paper proposes a novel reconstruction algorithm for subsurface radar data acquired along cylindrical scan trajectories. The spectrum of the collected data is processed in order to locate the spatial origin of the target reflections and remove the spreading of the target reflections which results from the different signal travel times along the scan trajectory. The proposed algorithm was successfully tested using experimental data collected from phantoms that mimic high contrast subsurface radar scenarios, yielding promising results. Practical considerations such as spatial resolution and sampling constraints are discussed and illustrated as well.

Modulation transfer function cascade model for a sampled IR imaging system.

PubMed

de Luca, L; Cardone, G

1991-05-01

The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

Ecological forestry in an uneven-aged, late-successional forest: Simulated effects of contrasting treatments on structure and yield

Treesearch

Jacob J. Hanson; Craig G. Lorimer; Corey R. Halpin; Brian J. Palik

2012-01-01

Ecological forestry practices are designed to retain species and structural features important for maintaining ecosystem function but which may be deficient in conventionally managed stands. We used the spatially-explicit, individual tree model CANOPY to assess tradeoffs in enhanced ecological attributes vs. reductions in timber yield for a wide variety of treatments...

Estimating Biofuel Feedstock Water Footprints Using System Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inman, Daniel; Warner, Ethan; Stright, Dana

Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of manymore » feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user-friendly interface for on-demand, spatially explicit, water use scenario analysis for many US agricultural crops. Built-in controls permit users to quickly make modifications to the model assumptions, such as those affecting yield, and to see the implications of those results in real time. BioSpatial H2O's dynamic capabilities and adjustable climate data allow for analyses of water use and management scenarios to inform current and potential future bioenergy policies. The model could also be adapted for scenario analysis of alternative climatic conditions and comparison of multiple crops. The results of such an analysis would help identify risks associated with water use competition among feedstocks in certain regions. Results could also inform research and development efforts that seek to reduce water-related risks of biofuel pathways.« less

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

NASA Astrophysics Data System (ADS)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

Fine scale variations of surface water chemistry in an ephemeral to perennial drainage network

Treesearch

Margaret A. Zimmer; Scott W. Bailey; Kevin J. McGuire; Thomas D. Bullen

2013-01-01

Although temporal variation in headwater stream chemistry has long been used to document baseline conditions and response to environmental drivers, less attention is paid to fine scale spatial variations that could yield clues to processes controlling stream water sources. We documented spatial and temporal variation in water composition in a headwater catchment (41 ha...

Holographic monitoring of spatial distributions of singlet oxygen in water

NASA Astrophysics Data System (ADS)

Belashov, A. V.; Bel'tyukova, D. M.; Vasyutinskii, O. S.; Petrov, N. V.; Semenova, I. V.; Chupov, A. S.

2014-12-01

A method for monitoring spatial distributions of singlet oxygen in biological media has been developed. Singlet oxygen was generated using Radachlorin® photosensitizer, while thermal disturbances caused by nonradiative deactivation of singlet oxygen were detected by the holographic interferometry technique. Processing of interferograms yields temperature maps that characterize the deactivation process and show the distribution of singlet oxygen species.

Integrating remote sensing, geographic information system and modeling for estimating crop yield

NASA Astrophysics Data System (ADS)

Salazar, Luis Alonso

This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

Conflict resolved: On the role of spatial attention in reading and color naming tasks.

PubMed

Robidoux, Serje; Besner, Derek

2015-12-01

The debate about whether or not visual word recognition requires spatial attention has been marked by a conflict: the results from different tasks yield different conclusions. Experiments in which the primary task is reading based show no evidence that unattended words are processed, whereas when the primary task is color identification, supposedly unattended words do affect processing. However, the color stimuli used to date does not appear to demand as much spatial attention as explicit word reading tasks. We first identify a color stimulus that requires as much spatial attention to identify as does a word. We then demonstrate that when spatial attention is appropriately captured, distractor words in unattended locations do not affect color identification. We conclude that there is no word identification without spatial attention.

Characterization of scintillator-based detectors for few-ten-keV high-spatial-resolution x-ray imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsson, Jakob C., E-mail: jakob.larsson@biox.kth.se; Lundström, Ulf; Hertz, Hans M.

2016-06-15

Purpose: High-spatial-resolution x-ray imaging in the few-ten-keV range is becoming increasingly important in several applications, such as small-animal imaging and phase-contrast imaging. The detector properties critically influence the quality of such imaging. Here the authors present a quantitative comparison of scintillator-based detectors for this energy range and at high spatial frequencies. Methods: The authors determine the modulation transfer function, noise power spectrum (NPS), and detective quantum efficiency for Gadox, needle CsI, and structured CsI scintillators of different thicknesses and at different photon energies. An extended analysis of the NPS allows for direct measurements of the scintillator effective absorption efficiency andmore » effective light yield as well as providing an alternative method to assess the underlying factors behind the detector properties. Results: There is a substantial difference in performance between the scintillators depending on the imaging task but in general, the CsI based scintillators perform better than the Gadox scintillators. At low energies (16 keV), a thin needle CsI scintillator has the best performance at all frequencies. At higher energies (28–38 keV), the thicker needle CsI scintillators and the structured CsI scintillator all have very good performance. The needle CsI scintillators have higher absorption efficiencies but the structured CsI scintillator has higher resolution. Conclusions: The choice of scintillator is greatly dependent on the imaging task. The presented comparison and methodology will assist the imaging scientist in optimizing their high-resolution few-ten-keV imaging system for best performance.« less

Characterization of scintillator-based detectors for few-ten-keV high-spatial-resolution x-ray imaging.

PubMed

Larsson, Jakob C; Lundström, Ulf; Hertz, Hans M

2016-06-01

High-spatial-resolution x-ray imaging in the few-ten-keV range is becoming increasingly important in several applications, such as small-animal imaging and phase-contrast imaging. The detector properties critically influence the quality of such imaging. Here the authors present a quantitative comparison of scintillator-based detectors for this energy range and at high spatial frequencies. The authors determine the modulation transfer function, noise power spectrum (NPS), and detective quantum efficiency for Gadox, needle CsI, and structured CsI scintillators of different thicknesses and at different photon energies. An extended analysis of the NPS allows for direct measurements of the scintillator effective absorption efficiency and effective light yield as well as providing an alternative method to assess the underlying factors behind the detector properties. There is a substantial difference in performance between the scintillators depending on the imaging task but in general, the CsI based scintillators perform better than the Gadox scintillators. At low energies (16 keV), a thin needle CsI scintillator has the best performance at all frequencies. At higher energies (28-38 keV), the thicker needle CsI scintillators and the structured CsI scintillator all have very good performance. The needle CsI scintillators have higher absorption efficiencies but the structured CsI scintillator has higher resolution. The choice of scintillator is greatly dependent on the imaging task. The presented comparison and methodology will assist the imaging scientist in optimizing their high-resolution few-ten-keV imaging system for best performance.

Wide-field motion tuning in nocturnal hawkmoths

PubMed Central

Theobald, Jamie C.; Warrant, Eric J.; O'Carroll, David C.

2010-01-01

Nocturnal hawkmoths are known for impressive visually guided behaviours in dim light, such as hovering while feeding from nectar-bearing flowers. This requires tight visual feedback to estimate and counter relative motion. Discrimination of low velocities, as required for stable hovering flight, is fundamentally limited by spatial resolution, yet in the evolution of eyes for nocturnal vision, maintenance of high spatial acuity compromises absolute sensitivity. To investigate these trade-offs, we compared responses of wide-field motion-sensitive neurons in three species of hawkmoth: Manduca sexta (a crepuscular hoverer), Deilephila elpenor (a fully nocturnal hoverer) and Acherontia atropos (a fully nocturnal hawkmoth that does not hover as it feeds uniquely from honey in bees' nests). We show that despite smaller eyes, the motion pathway of D. elpenor is tuned to higher spatial frequencies and lower temporal frequencies than A. atropos, consistent with D. elpenor's need to detect low velocities for hovering. Acherontia atropos, however, presumably evolved low-light sensitivity without sacrificing temporal acuity. Manduca sexta, active at higher light levels, is tuned to the highest spatial frequencies of the three and temporal frequencies comparable with A. atropos. This yields similar tuning to low velocities as in D. elpenor, but with the advantage of shorter neural delays in processing motion. PMID:19906663

Effects of preference heterogeneity among landowners on spatial conservation prioritization.

PubMed

Nielsen, Anne Sofie Elberg; Strange, Niels; Bruun, Hans Henrik; Jacobsen, Jette Bredahl

2017-06-01

The participation of private landowners in conservation is crucial to efficient biodiversity conservation. This is especially the case in settings where the share of private ownership is large and the economic costs associated with land acquisition are high. We used probit regression analysis and historical participation data to examine the likelihood of participation of Danish forest owners in a voluntary conservation program. We used the results to spatially predict the likelihood of participation of all forest owners in Denmark. We merged spatial data on the presence of forest, cadastral information on participation contracts, and individual-level socioeconomic information about the forest owners and their households. We included predicted participation in a probability model for species survival. Uninformed and informed (included land owner characteristics) models were then incorporated into a spatial prioritization for conservation of unmanaged forests. The choice models are based on sociodemographic data on the entire population of Danish forest owners and historical data on their participation in conservation schemes. Inclusion in the model of information on private landowners' willingness to supply land for conservation yielded at intermediate budget levels up to 30% more expected species coverage than the uninformed prioritization scheme. Our landowner-choice model provides an example of moving toward more implementable conservation planning. © 2016 Society for Conservation Biology.

Nanoscale Spatiotemporal Diffusion Modes Measured by Simultaneous Confocal and Stimulated Emission Depletion Nanoscopy Imaging.

PubMed

Schneider, Falk; Waithe, Dominic; Galiani, Silvia; Bernardino de la Serna, Jorge; Sezgin, Erdinc; Eggeling, Christian

2018-06-19

The diffusion dynamics in the cellular plasma membrane provide crucial insights into molecular interactions, organization, and bioactivity. Beam-scanning fluorescence correlation spectroscopy combined with super-resolution stimulated emission depletion nanoscopy (scanning STED-FCS) measures such dynamics with high spatial and temporal resolution. It reveals nanoscale diffusion characteristics by measuring the molecular diffusion in conventional confocal mode and super-resolved STED mode sequentially for each pixel along the scanned line. However, to directly link the spatial and the temporal information, a method that simultaneously measures the diffusion in confocal and STED modes is needed. Here, to overcome this problem, we establish an advanced STED-FCS measurement method, line interleaved excitation scanning STED-FCS (LIESS-FCS), that discloses the molecular diffusion modes at different spatial positions with a single measurement. It relies on fast beam-scanning along a line with alternating laser illumination that yields, for each pixel, the apparent diffusion coefficients for two different observation spot sizes (conventional confocal and super-resolved STED). We demonstrate the potential of the LIESS-FCS approach with simulations and experiments on lipid diffusion in model and live cell plasma membranes. We also apply LIESS-FCS to investigate the spatiotemporal organization of glycosylphosphatidylinositol-anchored proteins in the plasma membrane of live cells, which, interestingly, show multiple diffusion modes at different spatial positions.

Can Satellite Remote Sensing be Applied in Geological Mapping in Tropics?

NASA Astrophysics Data System (ADS)

Magiera, Janusz

2018-03-01

Remote sensing (RS) techniques are based on spectral data registered by RS scanners as energy reflected from the Earth's surface or emitted by it. In "geological" RS the reflectance (or emittence) should come from rock or sediment. The problem in tropical and subtropical areas is a dense vegetation. Spectral response from the rocks and sediments is gathered only from the gaps among the trees and shrubs. Images of high resolution are appreciated here, therefore. New generation of satellites and scanners (Digital Globe WV2, WV3 and WV4) yield imagery of spatial resolution of 2 m and up to 16 spectral bands (WV3). Images acquired by Landsat (TM, ETM+, OLI) and Sentinel 2 have good spectral resolution too (6-12 bands in visible and infrared) and, despite lower spatial resolution (10-60 m of pixel size) are useful in extracting lithological information too. Lithological RS map may reveal good precision (down to a single rock or outcrop of a meter size). Supplemented with the analysis of Digital Elevation Model and high resolution ortophotomaps (Google Maps, Bing etc.) allows for quick and cheap mapping of unsurveyed areas.

Deep learning massively accelerates super-resolution localization microscopy.

PubMed

Ouyang, Wei; Aristov, Andrey; Lelek, Mickaël; Hao, Xian; Zimmer, Christophe

2018-06-01

The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PALM, a computational strategy that uses artificial neural networks to reconstruct super-resolution views from sparse, rapidly acquired localization images and/or widefield images. Simulations and experimental imaging of microtubules, nuclear pores, and mitochondria show that high-quality, super-resolution images can be reconstructed from up to two orders of magnitude fewer frames than usually needed, without compromising spatial resolution. Super-resolution reconstructions are even possible from widefield images alone, though adding localization data improves image quality. We demonstrate super-resolution imaging of >1,000 fields of view containing >1,000 cells in ∼3 h, yielding an image spanning spatial scales from ∼20 nm to ∼2 mm. The drastic reduction in acquisition time and sample irradiation afforded by ANNA-PALM enables faster and gentler high-throughput and live-cell super-resolution imaging.

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation

NASA Astrophysics Data System (ADS)

Zhou, Xiran; Liu, Jun; Liu, Shuguang; Cao, Lei; Zhou, Qiming; Huang, Huawen

2014-02-01

High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity-hue-saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.

Combining Crop Model and Remote Sensing Data at High Resolution for the Assessment of Rice Agricultural Practices in the South-Eastern France (Take 5 Experiment SPOT4-SPOT5)

NASA Astrophysics Data System (ADS)

Courault, D.; Ruget, F.; Talab-ou-Ali, H.; Hagolle, O.; Delmotte, S.; Barbier, J. M.; Boschetti, M.; Mouret, J. C.

2016-08-01

Crop systems are constantly changing due to modifications in the agricultural practices to respond to market changes, the constraints of the environment, the climate hazards... Rice cultivation practiced in the Camargue region (SE France) have decreased these last years, however rice plays a crucial role for the hydrological balance of the region and for crop systems desalinizing soils. The aim of this study is to analyze the potentialities of remote sensing data acquired at high spatial and temporal resolution (HRST) to identify the main agricultural practices and estimate their impact on rice production. A large dataset acquired over the Camargue from the Take5 experiment (SPOT4 in 2013 and SPOT5 in 2015), completed by Landsat data has been used. Two assimilation methods of HRST data were evaluated within a crop model. Results showed the impact of the spatial variability of practices on the yields. The sowing dates were retrieved from inverse procedures and gave satisfactory results compared to ground surveys.

Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolb, A., E-mail: armin.kolb@med.uni-tuebingen.de; Parl, C.; Liu, C. C.

Purpose: The aim of this study was to develop a prototype PET detector module for a combined small animal positron emission tomography and magnetic resonance imaging (PET/MRI) system. The most important factor for small animal imaging applications is the detection sensitivity of the PET camera, which can be optimized by utilizing longer scintillation crystals. At the same time, small animal PET systems must yield a high spatial resolution. The measured object is very close to the PET detector because the bore diameter of a high field animal MR scanner is limited. When used in combination with long scintillation crystals, thesemore » small-bore PET systems generate parallax errors that ultimately lead to a decreased spatial resolution. Thus, we developed a depth of interaction (DoI) encoding PET detector module that has a uniform spatial resolution across the whole field of view (FOV), high detection sensitivity, compactness, and insensitivity to magnetic fields. Methods: The approach was based on Geiger mode avalanche photodiode (G-APD) detectors with cross-strip encoding. The number of readout channels was reduced by a factor of 36 for the chosen block elements. Two 12 × 2 G-APD strip arrays (25μm cells) were placed perpendicular on each face of a 12 × 12 lutetium oxyorthosilicate crystal block with a crystal size of 1.55 × 1.55 × 20 mm. The strip arrays were multiplexed into two channels and used to calculate the x, y coordinates for each array and the deposited energy. The DoI was measured in step sizes of 1.8 mm by a collimated {sup 18}F source. The coincident resolved time (CRT) was analyzed at all DoI positions by acquiring the waveform for each event and applying a digital leading edge discriminator. Results: All 144 crystals were well resolved in the crystal flood map. The average full width half maximum (FWHM) energy resolution of the detector was 12.8% ± 1.5% with a FWHM CRT of 1.14 ± 0.02 ns. The average FWHM DoI resolution over 12 crystals was 2.90 ± 0.15 mm. Conclusions: The novel DoI PET detector, which is based on strip G-APD arrays, yielded a DoI resolution of 2.9 mm and excellent timing and energy resolution. Its high multiplexing factor reduces the number of electronic channels. Thus, this cross-strip approach enables low-cost, high-performance PET detectors for dedicated small animal PET and PET/MRI and potentially clinical PET/MRI systems.« less

Spatial partitioning of environmental correlates of avian biodiversity in the conterminous United States

USGS Publications Warehouse

O'Connor, R.J.; Jones, M.T.; White, D.; Hunsaker, C.; Loveland, Tom; Jones, Bruce; Preston, E.

1996-01-01

Classification and regression tree (CART) analysis was used to create hierarchically organized models of the distribution of bird species richness across the conterminous United States. Species richness data were taken from the Breeding Bird Survey and were related to climatic and land use data. We used a systematic spatial grid of approximately 12,500 hexagons, each approximately 640 square kilometres in area. Within each hexagon land use was characterized by the Loveland et al. land cover classification based on Advanced Very High Resolution Radiometer (AVHRR) data from NOAA polar orbiting meteorological satellites. These data were aggregated to yield fourteen land classes equivalent to an Anderson level II coverage; urban areas were added from the Digital Chart of the World. Each hexagon was characterized by climate data and landscape pattern metrics calculated from the land cover. A CART model then related the variation in species richness across the 1162 hexagons for which bird species richness data were available to the independent variables, yielding an R2-type goodness of fit metric of 47.5% deviance explained. The resulting model recognized eleven groups of hexagons, with species richness within each group determined by unique sequences of hierarchically constrained independent variables. Within the hierarchy, climate data accounted for more variability in the bird data, followed by land cover proportion, and then pattern metrics. The model was then used to predict species richness in all 12,500 hexagons of the conterminous United States yielding a map of the distribution of these eleven classes of bird species richness as determined by the environmental correlates. The potential for using this technique to interface biogeographic theory with the hierarchy theory of ecology is discussed. ?? 1996 Blackwell Science Ltd.

Brownian systems with spatially inhomogeneous activity

NASA Astrophysics Data System (ADS)

Sharma, A.; Brader, J. M.

2017-09-01

We generalize the Green-Kubo approach, previously applied to bulk systems of spherically symmetric active particles [J. Chem. Phys. 145, 161101 (2016), 10.1063/1.4966153], to include spatially inhomogeneous activity. The method is applied to predict the spatial dependence of the average orientation per particle and the density. The average orientation is given by an integral over the self part of the Van Hove function and a simple Gaussian approximation to this quantity yields an accurate analytical expression. Taking this analytical result as input to a dynamic density functional theory approximates the spatial dependence of the density in good agreement with simulation data. All theoretical predictions are validated using Brownian dynamics simulations.

Modeling suspended sediment sources and transport in the Ishikari River Basin, Japan using SPARROW

NASA Astrophysics Data System (ADS)

Duan, W.; He, B.; Takara, K.; Luo, P.; Nover, D.; Hu, M.

2014-10-01

It is important to understand the mechanisms that control suspended sediment (SS) fate and transport in rivers as high suspended sediment loads have significant impacts on riverine hydroecology. In this study, the watershed model SPARROW (SPAtially Referenced Regression on Watershed Attributes) was applied to estimate the sources and transport of SS in surface waters of the Ishikari River Basin (14 330 km2), the largest watershed on Hokkaido Island, Japan. The final developed SPARROW model has four source variables (developing lands, forest lands, agricultural lands, and stream channels), three landscape delivery variables (slope, soil permeability, and precipitation), two in-stream loss coefficients including small stream (streams with drainage area < 200 km2), large stream, and reservoir attenuation. The model was calibrated using measurements of SS from 31 monitoring sites of mixed spatial data on topography, soils and stream hydrography. Calibration results explain approximately 95.96% (R2) of the spatial variability in the natural logarithm mean annual SS flux (kg km-2 yr-1) and display relatively small prediction errors at the 31 monitoring stations. Results show that developing-land is associated with the largest sediment yield at around 1006.27 kg km-2 yr-1, followed by agricultural-land (234.21 kg km-2 yr-1). Estimation of incremental yields shows that 35.11% comes from agricultural lands, 23.42% from forested lands, 22.91% from developing lands, and 18.56% from stream channels. The results of this study improve our understanding of sediments production and transportation in the Ishikari River Basin in general, which will benefit both the scientific and the management community in safeguarding water resources.

High-speed spectral nanocytology for early cancer screening

PubMed Central

Subramanian, Hariharan; Maneval, Charles D.; White, Craig A.; Levenson, Richard M.; Backman, Vadim

2013-01-01

Abstract. High-throughput partial wave spectroscopy (HTPWS) is introduced as a high-speed spectral nanocytology technique that utilizes the field effect of carcinogenesis to perform minimally invasive cancer screening on at-risk populations. HTPWS uses fully automated hardware and an acousto-optic tunable filter to scan slides at low magnification, to select cells, and to rapidly acquire spectra at each spatial pixel in a cell between 450 and 700 nm, completing measurements of 30 cells in 40 min. Statistical quantitative analysis on the size and density of intracellular nanostructures extracted from the spectra at each pixel in a cell yields the diagnostic biomarker, disorder strength (Ld). Linear correlation between Ld and the length scale of nanostructures was measured in phantoms with R2=0.93. Diagnostic sensitivity was demonstrated by measuring significantly higher Ld from a human colon cancer cell line (HT29 control vector) than a less aggressive variant (epidermal growth factor receptor knockdown). Clinical diagnostic performance for lung cancer screening was tested on 23 patients, yielding a significant difference in Ld between smokers and cancer patients, p=0.02 and effect size=1.00. The high-throughput performance, nanoscale sensitivity, and diagnostic sensitivity make HTPWS a potentially clinically relevant modality for risk stratification of the large populations at risk of developing cancer. PMID:24193949

Correlated topographic and structural modification on Si surface during multi-shot femtosecond laser exposures: Si nanopolymorphs as potential local structural nanomarkers

NASA Astrophysics Data System (ADS)

Ionin, A. A.; Kudryashov, S. I.; Levchenko, A. O.; Nguyen, L. V.; Saraeva, I. N.; Rudenko, A. A.; Ageev, E. I.; Potorochin, D. V.; Veiko, V. P.; Borisov, E. V.; Pankin, D. V.; Kirilenko, D. A.; Brunkov, P. N.

2017-09-01

High-pressure Si-XII and Si-III nanocrystalline polymorphs, as well as amorphous Si phase, appear consequently during multi-shot femtosecond-laser exposure of crystalline Si wafer surface above its spallation threshold along with permanently developing quasi-regular surface texture (ripples, microcones), residual hydrostatic stresses and subsurface damage, which are characterized by scanning and transmission electron microscopy, as well as by Raman micro-spectroscopy. The consequent yields of these structural Si phases indicate not only their spatially different appearance, but also potentially enable to track nanoscale, transient laser-induced high-pressure, high-temperature physical processes - local variation of ablation mechanism and rate, pressurization/pressure release, melting/resolidification, amorphization, annealing - versus cumulative laser exposure and the related development of the surface topography.

The spatial extent of agriculturally-induced topsoil removal in the Midwestern United States

NASA Astrophysics Data System (ADS)

Thaler, E.; Larsen, I. J.; Yu, Q.; Keiluweit, M.

2017-12-01

Human-induced erosion of soil organic carbon (SOC) degrades soils, leading to decreased crop yields. Here we develop a novel approach for mapping the spatial distribution of complete topsoil loss in agricultural landscapes, focusing on the Midwestern U.S. We used the ferric iron index (FeI) derived from high-resolution satellite imagery to map Fe-rich subsoil exposed by the loss of carbon-rich topsoil. Integrating topographic curvature derived from high resolution topographic data with FeI values demonstrates that FeI values are lowest in concave hollows where eroded soil accumulates, and increase linearly with topographic curvature on convex hilltops. The relationship between FeI and curvature indicates diffusion-like erosion by tillage is a dominant mechanism of soil loss, a mechanism generally not included in soil loss prediction in the U.S. Moreover, the FeI and curvature data indicate SOC-rich topsoil has been completely removed from hilltops, exposing Fe-rich subsoil. This interpretation supported by measurements of FeI using laboratory spectra, extractable-Fe, and organic C from two soil profiles from native prairies, which preserve the pre-agricultural soil profile. FeI increased sharply from the topsoil through the subsoil and total C and extractable Fe content are negatively correlated in both profiles. We calculated topographic curvature for 3.8 x105 km2 of the formerly-glaciated Midwestern U.S. using LiDAR data and found that convex topography, where FeI values suggest topsoil has been completely stripped, covers half of the landscape. Assuming complete removal of original SOC on all hilltops, we estimate that 784 Tg of C has been removed since cultivation began in the mid-1800s and that the SOC decline results in billions of dollars in annual economic losses from decreased crop yields. Restoration of eroded SOC has been proposed as a method to sequester atmospheric CO2 while simultaneously increasing crop yields, and our estimates suggest that replenishing eroded SOC within the Midwestern U.S. to pre-settlement levels could sequester 2900 Tg of CO2, equivalent to more than half of 2016 U.S. CO2 emissions. Our study highlights both the necessity to incorporate tillage into soil erosion models and the potential for SOC restoration to increase crop yields and offset carbon emissions.

Hypervelocity Dust Injection for Plasma Diagnostic Applications

NASA Astrophysics Data System (ADS)

Ticos, Catalin

2005-10-01

Hypervelocity micron-size dust grain injection was proposed for high-temperature magnetized plasma diagnosis. Multiple dust grains are launched simultaneously into high temperature plasmas at several km/s or more. The hypervelocity dust grains are ablated by the electron and ion fluxes. Fast imaging of the resulting luminous plumes attached to each grain is expected to yield local magnetic field vectors. Combination of multiple local magnetic field vectors reproduces 2D or even 3D maps of the internal magnetic field topology. Key features of HDI are: (1) a high spatial resolution, due to a relatively small transverse size of the elongated tail, and (2) a small perturbation level, as the dust grains introduce negligible number of particles compared to the plasma particle inventory. The latter advantage, however, could be seriously compromised if the gas load from the accelerator has an unobstructed access to the diagnosed plasma. Construction of a HDI diagnostic for National Spherical Torus Experiment (NSTX), which includes a coaxial plasma gun for dust grain acceleration, is underway. Hydrogen and deuterium gas discharges inside accelerator are created by a ˜ 1 mF capacitor bank pre-charged up to 10 kV. The diagnostic apparatus also comprises a dust dispenser for pre-loading the accelerator with dust grains, and an imaging system that has a high spatial and temporal resolution.

Bilateral parietal contributions to spatial language.

PubMed

Conder, Julie; Fridriksson, Julius; Baylis, Gordon C; Smith, Cameron M; Boiteau, Timothy W; Almor, Amit

2017-01-01

It is commonly held that language is largely lateralized to the left hemisphere in most individuals, whereas spatial processing is associated with right hemisphere regions. In recent years, a number of neuroimaging studies have yielded conflicting results regarding the role of language and spatial processing areas in processing language about space (e.g., Carpenter, Just, Keller, Eddy, & Thulborn, 1999; Damasio et al., 2001). In the present study, we used sparse scanning event-related functional magnetic resonance imaging (fMRI) to investigate the neural correlates of spatial language, that is; language used to communicate the spatial relationship of one object to another. During scanning, participants listened to sentences about object relationships that were either spatial or non-spatial in nature (color or size relationships). Sentences describing spatial relationships elicited more activation in the superior parietal lobule and precuneus bilaterally in comparison to sentences describing size or color relationships. Activation of the precuneus suggests that spatial sentences elicit spatial-mental imagery, while the activation of the SPL suggests sentences containing spatial language involve integration of two distinct sets of information - linguistic and spatial. Copyright © 2016 Elsevier Inc. All rights reserved.

A technique for enhancing and matching the resolution of microwave measurements from the SSM/I instrument

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.

1992-01-01

A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.

Water yield responses to climate change and variability across the North–South Transect of Eastern China (NSTEC)

Treesearch

Nan Lu; Ge Sun; Xiaoming Feng; Bojie Fu

2013-01-01

China is facing a growing water crisis due to climate and land use change, and rise in human water demand across this rapidly developing country. Understanding the spatial and temporal ecohydrologic responses to climate change is critical to sustainable water resource management. We investigated water yield (WY) responses to historical (1981–2000) and projected...

Qualitative and quantitative mass spectrometry imaging of drugs and metabolites in tissue at therapeutic levels.

PubMed

Sun, Na; Walch, Axel

2013-08-01

Mass spectrometry imaging (MSI) is a rapidly evolving technology that yields qualitative and quantitative distribution maps of small pharmaceutical-active molecules and their metabolites in tissue sections in situ. The simplicity, high sensitivity and ability to provide comprehensive spatial distribution maps of different classes of biomolecules make MSI a valuable tool to complement histopathology for diagnostics and biomarker discovery. In this review, qualitative and quantitative MSI of drugs and metabolites in tissue at therapeutic levels are discussed and the impact of this technique in drug discovery and clinical research is highlighted.

Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy.

PubMed

Rappaz, Benjamin; Cano, Elena; Colomb, Tristan; Kühn, Jonas; Depeursinge, Christian; Simanis, Viesturs; Magistretti, Pierre J; Marquet, Pierre

2009-01-01

Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Continental-scale Sensitivity of Water Yield to Changes in Impervious Cover

NASA Astrophysics Data System (ADS)

Caldwell, P.; Sun, G.; McNulty, S.; Cohen, E.; Moore Myers, J.

2012-12-01

Projected land conversion from native forest, grassland, and shrubland to urban impervious cover will alter watershed water balances by reducing groundwater recharge and evapotranspiration, increasing surface runoff, and potentially altering regional weather patterns. These hydrologic changes have important ecohydrological implications to local watersheds, including stream channel habitat degradation and the loss of aquatic biodiversity. Many observational studies have evaluated the impact of urbanization on water yield in small catchments downstream of specific urban areas. However it is often difficult to separate the impact of impervious cover from other impacts of urbanization such as leaking water infrastructure, irrigation runoff, water supply withdrawals, and effluent discharge. In addition, the impact of impervious cover has not been evaluated at scales large enough to assess spatial differences in water yield sensitivity to changes in impervious cover. The objective of this study was to assess the sensitivity of water yield to impervious cover across the conterminous U.S., and to identify locations where water yield will be most impacted by future urbanization. We used the Water Supply Stress Index (WaSSI) model to simulate monthly water yield as impacted by impervious cover for the approximately 82,000 12-digit HUC watersheds across the conterminous U.S. WaSSI computed infiltration, surface runoff, soil moisture, and baseflow processes explicitly for ten vegetative land cover classes and impervious cover in each watershed using the 2006 National Land Cover Dataset estimates of impervious cover. Our results indicate that impervious cover has increased total water yield in urban areas (relative to native vegetation), and that the increase was most significant during the growing season. The proportion of stream flow that occurred as baseflow decreased, even though total water yield increased as a result of impervious cover. Water yield was most sensitive to changes in impervious cover in areas where annual evapotranspiration is high relative to precipitation (e.g. the Southwestern States, Texas, and Florida). Water yield was less sensitive in areas with low evapotranspiration relative to precipitation (e.g. Pacific Northwest and Northeastern States). Additionally, water yield was most impacted when high evapotranspiration land cover types (e.g. forests) were converted to impervious cover than when lower evapotranspiration land cover types (e.g. grassland) were converted. Using projections of future impervious cover provided by the U.S. EPA Integrated Climate and Land Use Scenarios project, water yield in urban areas of the Southwest, Texas, and Florida will be the most impacted by 2050, in part because these areas are projected to have significant increases in impervious cover, but also because they are in areas where evapotranspiration is high relative to precipitation. Our study suggests that watershed management should consider the climate-driven sensitivity of water yield to increases in impervious cover and the type of land cover being converted in addition to the magnitude of projected increases in impervious cover when evaluating impacts of urbanization on water resources.

How useful are meteorological drought indicators to assess agricultural drought impacts across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Tanguy, Maliko; Hannaford, Jamie; Stahl, Kerstin

2016-04-01

Drought monitoring and early warning (M&EW) is an important component of agricultural and silvicultural risk management. Meteorological indicators such as the Standardized Precipitation Index (SPI) are widely used in operational M&EW systems and for drought hazard assessment. Meteorological drought yet does not necessarily equate to agricultural drought given differences in drought susceptibility, e.g. crop-specific vulnerability, soil water holding capacity, irrigation and other management practices. How useful are meteorological indicators such as SPI to assess agricultural drought? Would the inclusion of vegetation indicators into drought M&EW systems add value for the agricultural sector? To answer these questions, it is necessary to investigate the link between meteorological indicators and agricultural impacts of drought. Crop yield or loss data is one source of information for drought impacts, yet mostly available as aggregated data at the annual scale. Remotely sensed vegetation stress data offer another possibility to directly assess agricultural impacts with high spatial and temporal resolution and are already used by some M&EW systems. At the same time, reduced crop yield and satellite-based vegetation stress potentially suffer from multi-causality. The aim of this study is therefore to investigate the relation between meteorological drought indicators and agricultural drought impacts for Europe, and to intercompare different agricultural impact variables. As drought indicators we used SPI and the Standardized Precipitation Evaporation Index (SPEI) for different accumulation periods. The focus regarding drought impact variables was on remotely sensed vegetation stress derived from MODIS NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) data, but the analysis was complemented with crop yield data and text-based information from the European Drought Impact report Inventory (EDII) for selected countries. A correlation analysis between meteorological drought indicators and remotely sensed vegetation stress at the EU NUTS3 region level revealed a high correlation between the two types of indicators for many regions; however some spatial variability was observed in (i) strength of correlation, (ii) performance of SPI versus SPEI, and (iii) best linked SPI/SPEI time scale. We additionally explored whether geographic properties like climate, soil texture, land use, and location explain the observed spatial patterns. Our study revealed that climatically dryer areas (water limited) showed high correlations between SPI/SPEI and vegetation stress, whereas the wettest parts of Europe (radiation limited regions) showed negative correlations especially for short accumulation periods, suggesting that for these regions, short droughts could actually be beneficial for vegetation growth. These findings suggest that relying solely on meteorological indicators for agricultural risk assessment in some regions might be inadequate. Overall, such information may help to tailor agricultural drought M&EW systems to specific regions.

Estimation of total nitrogen and total phosphorus in streams of the Middle Columbia River Basin (Oregon, Washington, and Idaho) using SPARROW models, with emphasis on the Yakima River Basin, Washington

USGS Publications Warehouse

Johnson, Henry M.; Black, Robert W.; Wise, Daniel R.

2013-01-01

The watershed model SPARROW (Spatially Related Regressions on Watershed attributes) was used to predict total nitrogen (TN) and total phosphorus (TP) loads and yields for the Middle Columbia River Basin in Idaho, Oregon, and Washington. The new models build on recently published models for the entire Pacific Northwest, and provide revised load predictions for the arid interior of the region by restricting the modeling domain and recalibrating the models. Results from the new TN and TP models are provided for the entire region, and discussed with special emphasis on the Yakima River Basin, Washington. In most catchments of the Yakima River Basin, the TN and TP in streams is from natural sources, specifically nitrogen fixation in forests (TN) and weathering and erosion of geologic materials (TP). The natural nutrient sources are overshadowed by anthropogenic sources of TN and TP in highly agricultural and urbanized catchments; downstream of the city of Yakima, most of the load in the Yakima River is derived from anthropogenic sources. Yields of TN and TP from catchments with nearly uniform land use were compared with other yield values and export coefficients published in the scientific literature, and generally were in agreement. The median yield of TN was greatest in catchments dominated by agricultural land and smallest in catchments dominated by grass and scrub land. The median yield of TP was greatest in catchments dominated by forest land, but the largest yields (90th percentile) of TP were from agricultural catchments. As with TN, the smallest TP yields were from catchments dominated by grass and scrub land.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2.

PubMed

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali; Archontoulis, Sotirios V; Zobel, Zachary; Kotamarthi, Veerabhadra R

2017-07-01

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO 2 concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high-resolution (12 km) dynamically downscaled climate projections for 1995-2004 and 2085-2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO 2 partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems. © 2017 John Wiley & Sons Ltd.

Topics in strong Langmuir turbulence

NASA Technical Reports Server (NTRS)

Nicholson, D. R.

1983-01-01

Progress in two approaches to the study of strong Langmuir turbulence is reported. In two spatial dimensions, numerical solution of the Zakharov equations yields a steady state involving linear growth, linear damping, and a collection of coherent, long-lived entities which might loosely be called solitons. In one spatial dimension, a statistical theory is applied to the cubically nonlinear Schroedinger equation and is solved analytically in a special case.

Topics in strong Langmuir turbulence

NASA Technical Reports Server (NTRS)

Nicholson, D. R.

1982-01-01

Progress in two approaches to the study of strong Langmuir turbulence is reported. In two spatial dimensions, numerical solution of the Zakharov equations yields a steady state involving linear growth, linear damping, and a collection of coherent, long-lived entities which might loosely be called solitons. In one spatial dimension, a statistical theory is applied to the cubically nonlinear Schroedinger equation and is solved analytically in a special case.

Predicting the Spatial Distribution of Aspen Growth Potential in the Upper Great Lakes Region

Treesearch

Eric J. Gustafson; Sue M. Lietz; John L. Wright

2003-01-01

One way to increase aspen yields is to produce aspen on sites where aspen growth potential is highest. Aspen growth rates are typically predicted using site index, but this is impractical for landscape-level assessments. We tested the hypothesis that aspen growth can be predicted from site and climate variables and generated a model to map the spatial variability of...

Bright Lu2O3:Eu thin-film scintillators for high-resolution radioluminescence microscopy

PubMed Central

Sengupta, Debanti; Miller, Stuart; Marton, Zsolt; Chin, Frederick; Nagarkar, Vivek

2015-01-01

We investigate the performance of a new thin-film Lu2O3:Eu scintillator for single-cell radionuclide imaging. Imaging the metabolic properties of heterogeneous cell populations in real time is an important challenge with clinical implications. We have developed an innovative technique called radioluminescence microscopy, to quantitatively and sensitively measure radionuclide uptake in single cells. The most important component of this technique is the scintillator, which converts the energy released during radioactive decay into luminescent signals. The sensitivity and spatial resolution of the imaging system depend critically on the characteristics of the scintillator, i.e. the material used and its geometrical configuration. Scintillators fabricated using conventional methods are relatively thick, and therefore do not provide optimal spatial resolution. We compare a thin-film Lu2O3:Eu scintillator to a conventional 500 μm thick CdWO4 scintillator for radioluminescence imaging. Despite its thinness, the unique scintillation properties of the Lu2O3:Eu scintillator allow us to capture single positron decays with over fourfold higher sensitivity, a significant achievement. The thin-film Lu2O3:Eu scintillators also yield radioluminescence images where individual cells appear smaller and better resolved on average than with the CdWO4 scintillators. Coupled with the thin-film scintillator technology, radioluminescence microscopy can yield valuable and clinically relevant data on the metabolism of single cells. PMID:26183115

Transverse Space-Charge Field-Induced Plasma Dynamics for Ultraintense Electron-Beam Characterization

NASA Astrophysics Data System (ADS)

Tarkeshian, R.; Vay, J. L.; Lehe, R.; Schroeder, C. B.; Esarey, E. H.; Feurer, T.; Leemans, W. P.

2018-04-01

Similarly to laser or x-ray beams, the interaction of sufficiently intense particle beams with neutral gases will result in the creation of plasma. In contrast to photon-based ionization, the strong unipolar field of a particle beam can generate a plasma where the electron population receives a large initial momentum kick and escapes, leaving behind unshielded ions. Measuring the properties of the ensuing Coulomb exploding ions—such as their kinetic energy distribution, yield, and spatial distribution—can provide information about the peak electric fields that are achieved in the electron beams. Particle-in-cell simulations and analytical models are presented for high-brightness electron beams of a few femtoseconds or even hundreds of attoseconds, and transverse beam sizes on the micron scale, as generated by today's free electron lasers. Different density regimes for the utilization as a potential diagnostics are explored, and the fundamental differences in plasma dynamical behavior for e-beam or photon-based ionization are highlighted. By measuring the dynamics of field-induced ions for different gas and beam densities, a lower bound on the beam charge density can be obtained in a single shot and in a noninvasive way. The exponential dependency of the ionization yield on the beam properties can provide unprecedented spatial and temporal resolution, at the submicrometer and subfemtosecond scales, respectively, offering a practical and powerful approach to characterizing beams from accelerators at the frontiers of performance.

Snow Pattern Delineation, Scaling, Fidelity, and Landscape Factors

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.; Wagner, A. M.; Deeb, E. J.; Morriss, B. F.; Sturm, M.

2014-12-01

In many snow-covered landscapes, snow tends to be shallow or deep in the same locations year after year. As snowmelt progresses in spring, areas of shallow snow become snow-free earlier than areas with deep snow. This pattern (Sturm and Wagner 2010) could likely be used to inform or improve modeled snow depth estimates where ground measurements are not collected; however, we must be certain of their utility before ingesting them into model calculations. Do patterns, as we detect them, have a relationship with earlier measured snow distributions? Second, are certain areas on the landscape likely to yield patterns that are influenced too highly by melting to be useful? Our Imnavait Creek Study Area (11 by 19 km) is on Alaska's North Slope, where we have examined a vast library of spring satellite imagery (ranging from mostly snow-covered to mostly snow-free). Landsat TM Imagery has been collected from the early 1980s-present, and the temporal and spatial resolution is roughly two weeks and 30 m, respectively. High resolution satellite imagery (WorldView 1, WorldView 2, IKONOS) has been obtained from 2010-2013 for the same area with almost daily- to monthly-temporal and at 2.5 m spatial resolutions, respectively. We found that there is a striking similarity among patterns from year to year across the span of decades and resolutions. However, the relationship of pattern with observed snow depths was strong in some areas and less clear in others. Overall, we suspect spatial scaling, spatial mismatch, sampling errors, and melt patterns explain most of the areas of pattern and depth disparity.

Interpolating precipitation and its relation to runoff and non-point source pollution.

PubMed

Chang, Chia-Ling; Lo, Shang-Lien; Yu, Shaw-L

2005-01-01

When rainfall spatially varies, complete rainfall data for each region with different rainfall characteristics are very important. Numerous interpolation methods have been developed for estimating unknown spatial characteristics. However, no interpolation method is suitable for all circumstances. In this study, several methods, including the arithmetic average method, the Thiessen Polygons method, the traditional inverse distance method, and the modified inverse distance method, were used to interpolate precipitation. The modified inverse distance method considers not only horizontal distances but also differences between the elevations of the region with no rainfall records and of its surrounding rainfall stations. The results show that when the spatial variation of rainfall is strong, choosing a suitable interpolation method is very important. If the rainfall is uniform, the precipitation estimated using any interpolation method would be quite close to the actual precipitation. When rainfall is heavy in locations with high elevation, the rainfall changes with the elevation. In this situation, the modified inverse distance method is much more effective than any other method discussed herein for estimating the rainfall input for WinVAST to estimate runoff and non-point source pollution (NPSP). When the spatial variation of rainfall is random, regardless of the interpolation method used to yield rainfall input, the estimation errors of runoff and NPSP are large. Moreover, the relationship between the relative error of the predicted runoff and predicted pollutant loading of SS is high. However, the pollutant concentration is affected by both runoff and pollutant export, so the relationship between the relative error of the predicted runoff and the predicted pollutant concentration of SS may be unstable.

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

NASA Astrophysics Data System (ADS)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

The infield varietu of available forms in the forest-steppe of western part Central Chernozemic region

NASA Astrophysics Data System (ADS)

Belik, Anton; Devyatova, Tatiana; Bozhko, Svetlana; Gorbunova, Yulia

2016-04-01

The infield varietu of available forms in the forest-steppe of western part Central Chernozemic region The Central Chernozemic region of Russia has been a region with a strong agricultural industry and determines the food security of the state by most part. The soil cover of the region is represented mainly by chernozems and is favorable for the cultivation of major crops and produce high crop yields. However, the high development of agriculture in the territory of Central Chernozemic region are led to the development of agrogenic degradation processes which impacts on the growth of the soil cover complexity and contrast, and as a consequence a significant infield variety of soil fertility and yields of major crops. In this regard, very promising direction in CChR is the development and practical application technologies of precision agriculture, which implies the spatial variety of soil fertility analysis within specific fields and work areas, especially the content of available forms of nutrients. The aim of our research was a study of the agro-ecological characteristics of the spatial variety of the content by available forms to plants of major nutrients in representative areas of sloping agricultural landscapes with forest-steppe chernozems in the western part of Central Chernozemic region of Russia. The research of infield variety by content of available forms of major nutrients are carried in the fields of Russian Research Institute of Agriculture and Protect the Soil from Erosion experimental and industrial farm in Medvensky district of Kursk region. The area characterized by a complex organization of relief. The soil cover is represented by full-profile typical (conventional and carbonate), leached chernozems. The growth of contrast of the soil cover are largely determined by the appearance of eroded soils of these analogues, as well as zoogenic dug and accumulative soils All of the studied areas with the forest-steppe chernozems were characterized by pronounced variation in the content of available forms of nitrogen, phosphorus and potassium. In the most varied contents of available phosphorus and potassium (coefficients of variation increase by 1.2 - 1.3 times as the complexity of the soil cover and reduced 1.3 - 1.6 times as reducing the area of the site and the growth detailed studies). The least within the fields of content of nitrogen are varied at its most high average grade. As the most important factors determining the spatial variety of the batteries for the phosphorus and potassium should be made kind of soil, the degree of erosion, the depth of the carbonates. The above factors the humus content is added the level of applied agricultural technologies and the history of land use within the studied areas for the nitrogen. Thus, the identification of significant infield variety in the content of available forms of nutrients in the forest-steppe chernozems is the result of processes of water erosion. In terms of slope forest-steppe agricultural landscapes of Central Chernozemic region of spatial variability of available forms of nitrogen, phosphorus and potassium is an important factor, which is limited the yields and causes the most promising application the technologies of precision agriculture.

Inventory and recently increasing GLOF susceptibility of glacial lakes in Sikkim, Eastern Himalaya

NASA Astrophysics Data System (ADS)

Aggarwal, Suruchi; Rai, S. C.; Thakur, P. K.; Emmer, Adam

2017-10-01

Climatic changes alter the climate system, leading to a decrease of glacier mass volumes and swelling glacial lakes. This study provides a new inventory of glacial and high-altitude lakes for Sikkim, Eastern Himalaya, and evaluates the susceptibility of lakes to Glacial Lake Outburst Flood (GLOF). By using satellite data of high spatial resolution (5 m), we obtain 1104 glacial and high-altitude lakes with total area 30.498 km2, of which 472 have an area > 0.01 km2. Applying pre-defined GLOF susceptibility criteria on these 472 lakes yields 21 lakes susceptible to GLOF, which all increased in area from 1972-2015. Using Analytic Hierarchy Processes (AHP), the pairwise comparison matrix further reveals that 5 of these glacial lakes have low, 14 have medium and 2 have high GLOF susceptibility. Especially these 16 glacial lakes with high and medium GLOF susceptibility may threaten downstream communities and infrastructure and need further attention.

Spatially explicit models for inference about density in unmarked or partially marked populations

USGS Publications Warehouse

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.

2017-12-01

A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

Relationship between spatial and genetic distance in Agrobacterium spp. in 1 cubic centimeter of soil.

PubMed

Vogel, J; Normand, P; Thioulouse, J; Nesme, X; Grundmann, G L

2003-03-01

The spatial and genetic unit of bacterial population structure is the clone. Surprisingly, very little is known about the spread of a clone (spatial distance between clonally related bacteria) and the relationship between spatial distance and genetic distance, especially at very short scale (microhabitat scale), where cell division takes place. Agrobacterium spp. Biovar 1 was chosen because it is a soil bacterial taxon easy to isolate. A total of 865 microsamples 500 microm in diameter were sampled with spatial coordinates in 1 cm(3) of undisturbed soil. The 55 isolates obtained yielded 42 ribotypes, covering three genomic species based on amplified ribosomal DNA restriction analysis (ARDRA) of the intergenic spacer 16S-23S, seven of which contained two to six isolates. These clonemates (identical ARDRA patterns) could be found in the same microsample or 1 cm apart. The genetic diversity did not change with distance, indicating the same habitat variability across the cube. The mixing of ribotypes, as assessed by the spatial position of clonemates, corresponded to an overlapping of clones. Although the population probably was in a recession stage in the cube (10(3) agrobacteria g(-1)), a high genetic diversity was maintained. In two independent microsamples (500 microm in diameter) at the invasion stage, the average genetic diversity was at the same level as in the cube. Quantification of the microdiversity landscape will help to estimate the probability of encounter between bacteria under realistic natural conditions and to set appropriate sampling strategies for population genetic analysis.

Spatial versus Day-To-Day Within-Lake Variability in Tropical Floodplain Lake CH4 Emissions – Developing Optimized Approaches to Representative Flux Measurements

PubMed Central

Peixoto, Roberta B.; Machado-Silva, Fausto; Marotta, Humberto; Enrich-Prast, Alex; Bastviken, David

2015-01-01

Inland waters (lakes, rivers and reservoirs) are now understood to contribute large amounts of methane (CH4) to the atmosphere. However, fluxes are poorly constrained and there is a need for improved knowledge on spatiotemporal variability and on ways of optimizing sampling efforts to yield representative emission estimates for different types of aquatic ecosystems. Low-latitude floodplain lakes and wetlands are among the most high-emitting environments, and here we provide a detailed investigation of spatial and day-to-day variability in a shallow floodplain lake in the Pantanal in Brazil over a five-day period. CH4 flux was dominated by frequent and ubiquitous ebullition. A strong but predictable spatial variability (decreasing flux with increasing distance to the shore or to littoral vegetation) was found, and this pattern can be addressed by sampling along transects from the shore to the center. Although no distinct day-to-day variability were found, a significant increase in flux was identified from measurement day 1 to measurement day 5, which was likely attributable to a simultaneous increase in temperature. Our study demonstrates that representative emission assessments requires consideration of spatial variability, but also that spatial variability patterns are predictable for lakes of this type and may therefore be addressed through limited sampling efforts if designed properly (e.g., fewer chambers may be used if organized along transects). Such optimized assessments of spatial variability are beneficial by allowing more of the available sampling resources to focus on assessing temporal variability, thereby improving overall flux assessments. PMID:25860229

Grains of connectivity: analysis at multiple spatial scales in landscape genetics.

PubMed

Galpern, Paul; Manseau, Micheline; Wilson, Paul

2012-08-01

Landscape genetic analyses are typically conducted at one spatial scale. Considering multiple scales may be essential for identifying landscape features influencing gene flow. We examined landscape connectivity for woodland caribou (Rangifer tarandus caribou) at multiple spatial scales using a new approach based on landscape graphs that creates a Voronoi tessellation of the landscape. To illustrate the potential of the method, we generated five resistance surfaces to explain how landscape pattern may influence gene flow across the range of this population. We tested each resistance surface using a raster at the spatial grain of available landscape data (200 m grid squares). We then used our method to produce up to 127 additional grains for each resistance surface. We applied a causal modelling framework with partial Mantel tests, where evidence of landscape resistance is tested against an alternative hypothesis of isolation-by-distance, and found statistically significant support for landscape resistance to gene flow in 89 of the 507 spatial grains examined. We found evidence that major roads as well as the cumulative effects of natural and anthropogenic disturbance may be contributing to the genetic structure. Using only the original grid surface yielded no evidence for landscape resistance to gene flow. Our results show that using multiple spatial grains can reveal landscape influences on genetic structure that may be overlooked with a single grain, and suggest that coarsening the grain of landcover data may be appropriate for highly mobile species. We discuss how grains of connectivity and related analyses have potential landscape genetic applications in a broad range of systems. © 2012 Blackwell Publishing Ltd.

What is the Best Model Specification and Earth Observation Product for Predicting Regional Grain Yields in Food Insecure Countries?

NASA Astrophysics Data System (ADS)

Davenport, F., IV; Harrison, L.; Shukla, S.; Husak, G. J.; Funk, C. C.

2017-12-01

We evaluate the predictive accuracy of an ensemble of empirical model specifications that use earth observation data to predict sub-national grain yields in Mexico and East Africa. Products that are actively used for seasonal drought monitoring are tested as yield predictors. Our research is driven by the fact that East Africa is a region where decisions regarding agricultural production are critical to preventing the loss of economic livelihoods and human life. Regional grain yield forecasts can be used to anticipate availability and prices of key staples, which can turn can inform decisions about targeting humanitarian response such as food aid. Our objective is to identify-for a given region, grain, and time year- what type of model and/or earth observation can most accurately predict end of season yields. We fit a set of models to county level panel data from Mexico, Kenya, Sudan, South Sudan, and Somalia. We then examine out of sample predicative accuracy using various linear and non-linear models that incorporate spatial and time varying coefficients. We compare accuracy within and across models that use predictor variables from remotely sensed measures of precipitation, temperature, soil moisture, and other land surface processes. We also examine at what point in the season a given model or product is most useful for determining predictive accuracy. Finally we compare predictive accuracy across a variety of agricultural regimes including high intensity irrigated commercial agricultural and rain fed subsistence level farms.

Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status

NASA Astrophysics Data System (ADS)

Kvakić, Marko; Pellerin, Sylvain; Ciais, Philippe; Achat, David L.; Augusto, Laurent; Denoroy, Pascal; Gerber, James S.; Goll, Daniel; Mollier, Alain; Mueller, Nathaniel D.; Wang, Xuhui; Ringeval, Bruno

2018-01-01

Phosphorus (P) is an essential element for plant growth. Low P availability in soils is likely to limit crop yields in many parts of the world, but this effect has never been quantified at the global scale by process-based models. Here we attempt to estimate P limitation in three major cereals worldwide for the year 2000 by combining information on soil P distribution in croplands and a generic crop model, while accounting for the nature of soil-plant P transport. As a global average, the diffusion-limited soil P supply meets the crop's P demand corresponding to the climatic yield potential, due to the legacy soil P in highly fertilized areas. However, when focusing on the spatial distribution of P supply versus demand, we found strong limitation in regions like North and South America, Africa, and Eastern Europe. Averaged over grid cells where P supply is lower than demand, the global yield gap due to soil P is estimated at 22, 55, and 26% in winter wheat, maize, and rice. Assuming that a fraction (20%) of the annual P applied in fertilizers is directly available to the plant, the global P yield gap lowers by only 5-10%, underlying the importance of the existing soil P supply in sustaining crop yields. The study offers a base for exploring P limitation in crops worldwide but with certain limitations remaining. These could be better accounted for by describing the agricultural P cycle with a fully coupled and mechanistic soil-crop model.

Maize varieties released in different eras have similar root length density distributions in the soil, which are negatively correlated with local concentrations of soil mineral nitrogen.

PubMed

Ning, Peng; Li, Sa; White, Philip J; Li, Chunjian

2015-01-01

Larger, and deeper, root systems of new maize varieties, compared to older varieties, are thought to have enabled improved acquisition of soil resources and, consequently, greater grain yields. To compare the spatial distributions of the root systems of new and old maize varieties and their relationships with spatial variations in soil concentrations of available nitrogen (N), phosphorus (P) and potassium (K), two years of field experiments were performed using six Chinese maize varieties released in different eras. Vertical distributions of roots, and available N, P and K in the 0-60 cm soil profile were determined in excavated soil monoliths at silking and maturity. The results demonstrated that new maize varieties had larger root dry weight, higher grain yield and greater nutrient accumulation than older varieties. All varieties had similar total root length and vertical root distribution at silking, but newer varieties maintained greater total root length and had more roots in the 30-60 cm soil layers at maturity. The spatial variation of soil mineral N (Nmin) in each soil horizon was larger than that of Olsen-P and ammonium-acetate-extractable K, and was inversely correlated with root length density (RLD), especially in the 0-20 cm soil layer. It was concluded that greater acquisition of mineral nutrients and higher yields of newer varieties were associated with greater total root length at maturity. The negative relationship between RLD and soil Nmin at harvest for all varieties suggests the importance of the spatial distribution of the root system for N uptake by maize.

Maize Varieties Released in Different Eras Have Similar Root Length Density Distributions in the Soil, Which Are Negatively Correlated with Local Concentrations of Soil Mineral Nitrogen

PubMed Central

Ning, Peng; Li, Sa; White, Philip J.; Li, Chunjian

2015-01-01

Larger, and deeper, root systems of new maize varieties, compared to older varieties, are thought to have enabled improved acquisition of soil resources and, consequently, greater grain yields. To compare the spatial distributions of the root systems of new and old maize varieties and their relationships with spatial variations in soil concentrations of available nitrogen (N), phosphorus (P) and potassium (K), two years of field experiments were performed using six Chinese maize varieties released in different eras. Vertical distributions of roots, and available N, P and K in the 0–60 cm soil profile were determined in excavated soil monoliths at silking and maturity. The results demonstrated that new maize varieties had larger root dry weight, higher grain yield and greater nutrient accumulation than older varieties. All varieties had similar total root length and vertical root distribution at silking, but newer varieties maintained greater total root length and had more roots in the 30–60 cm soil layers at maturity. The spatial variation of soil mineral N (Nmin) in each soil horizon was larger than that of Olsen-P and ammonium-acetate-extractable K, and was inversely correlated with root length density (RLD), especially in the 0–20 cm soil layer. It was concluded that greater acquisition of mineral nutrients and higher yields of newer varieties were associated with greater total root length at maturity. The negative relationship between RLD and soil Nmin at harvest for all varieties suggests the importance of the spatial distribution of the root system for N uptake by maize. PMID:25799291

Logistic Stick-Breaking Process

PubMed Central

Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.

2013-01-01

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593

Psychometric analysis of five measures of spatial ability.

PubMed

Hogan, Thomas P

2012-02-01

This study analyzed psychometric properties of five measures of spatial ability on 96 young adults, with supplementary analysis for three of the measures on another sample of 71 young adults. Two measures were taken from the widely cited Kit of Factor-Referenced Cognitive Tests and three other measures were taken from a relatively new source originally intended as laboratory demonstrations. Previous research provided limited information on the psychometric properties of the measures. All five measures yielded adequate reliability and loaded on a single factor. Three measures yielded markedly skewed distributions. Two measures showed clear sex differences with men scoring higher but this difference seemed contaminated by a speed factor; three measures did not show a sex difference. Recommendations for use of the measures in future studies are provided.

High-sensitivity gas-mapping 3D imager and method of operation

DOEpatents

Kreitinger, Aaron; Thorpe, Michael

2018-05-15

Measurement apparatuses and methods are disclosed for generating high-precision and -accuracy gas concentration maps that can be overlaid with 3D topographic images by rapidly scanning one or several modulated laser beams with a spatially-encoded transmitter over a scene to build-up imagery. Independent measurements of the topographic target distance and path-integrated gas concentration are combined to yield a map of the path-averaged concentration between the sensor and each point in the image. This type of image is particularly useful for finding localized regions of elevated (or anomalous) gas concentration making it ideal for large-area leak detection and quantification applications including: oil and gas pipeline monitoring, chemical processing facility monitoring, and environmental monitoring.

Spatial Distribution of the Coefficient of Variation for the Paleo-Earthquakes in Japan

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2015-12-01

Renewal processes, point prccesses in which intervals between consecutive events are independently and identically distributed, are frequently used to describe this repeating earthquake mechanism and forecast the next earthquakes. However, one of the difficulties in applying recurrent earthquake models is the scarcity of the historical data. Most studied fault segments have few, or only one observed earthquake that often have poorly constrained historic and/or radiocarbon ages. The maximum likelihood estimate from such a small data set can have a large bias and error, which tends to yield high probability for the next event in a very short time span when the recurrence intervals have similar lengths. On the other hand, recurrence intervals at a fault depend on the long-term slip rate caused by the tectonic motion in average. In addition, recurrence times are also fluctuated by nearby earthquakes or fault activities which encourage or discourage surrounding seismicity. These factors have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus, this paper introduces a spatial structure on the key parameters of renewal processes for recurrent earthquakes and estimates it by using spatial statistics. Spatial variation of mean and variance parameters of recurrence times are estimated in Bayesian framework and the next earthquakes are forecasted by Bayesian predictive distributions. The proposal model is applied for recurrent earthquake catalog in Japan and its result is compared with the current forecast adopted by the Earthquake Research Committee of Japan.

Near ground level sensing for spatial analysis of vegetation

NASA Technical Reports Server (NTRS)

Sauer, Tom; Rasure, John; Gage, Charlie

1991-01-01

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

A Fast Track approach to deal with the temporal dimension of crop water footprint

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2017-07-01

Population growth, socio-economic development and climate changes are placing increasing pressure on water resources. Crop water footprint is a key indicator in the quantification of such pressure. It is determined by crop evapotranspiration and crop yield, which can be highly variable in space and time. While the spatial variability of crop water footprint has been the objective of several investigations, the temporal variability remains poorly studied. In particular, some studies approached this issue by associating the time variability of crop water footprint only to yield changes, while considering evapotranspiration patterns as marginal. Validation of this Fast Track approach has yet to be provided. In this Letter we demonstrate its feasibility through a comprehensive validation, an assessment of its uncertainty, and an example of application. Our results show that the water footprint changes are mainly driven by yield trends, while evapotranspiration plays a minor role. The error due to considering constant evapotranspiration is three times smaller than the uncertainty of the model used to compute the crop water footprint. These results confirm the suitability of the Fast Track approach and enable a simple, yet appropriate, evaluation of time-varying crop water footprint.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Proton Energy Optimization and Spatial Distribution Analysis from a Thickness Study Using Liquid Crystal Targets

NASA Astrophysics Data System (ADS)

Willis, Christopher; Poole, Patrick; Schumacher, Douglas; Freeman, Richard; van Woerkom, Linn

2016-10-01

Laser-accelerated ions from thin targets have been widely studied for applications including secondary radiation sources and cancer therapy, with recent studies trending towards thinner targets which can provide improved ion energies and yields. Here we discuss results from an experiment on the Scarlet laser at OSU using variable thickness liquid crystal targets. On this experiment, the spatial and spectral distributions of accelerated ions were measured along target normal and laser axes at varying thicknesses from 150nm to 2000nm at a laser intensity of 1 ×1020W /cm2 . Maximum ion energy was observed for targets in the 600 - 800nm thickness range, with proton energies reaching 24MeV . The ions were further characterized using radiochromic film, revealing an unusual spatial distribution on many laser shots. Here, the peak ion yield falls in an annular ring surrounding the target normal, with an increasing divergence angle as a function of ion energy. Details of these spatial and spectral ion distributions will be presented, including spectral deconvolution of the RCF data, revealing additional trends in the accelerated ion distributions. Supported by the DARPA PULSE program through a Grant from AMRDEC, and by the NNSA under contract DE-NA0001976.

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

PubMed Central

Goovaerts, Pierre; Jacquez, Geoffrey M

2004-01-01

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. PMID:15272930

Combining Remote Sensing imagery of both fine and coarse spatial resolution to Estimate Crop Evapotranspiration and quantifying its Influence on Crop Growth Monitoring.

NASA Astrophysics Data System (ADS)

Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio; Duveiller, Gregory; Piccard, Isabelle; de Wit, Allard; Tychon, Bernard; Bakary, Djaby; Defourny, Pierre

2010-05-01

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. Evapotranspiration (ET) is a valuable parameter in the crop monitoring context since it provides information on the plant water stress status, which strongly influences crop development and, by extension, crop yield. To assess crop evapotranspiration over the GLOBAM study areas (300x300 km sites in Northern Europe and Central Ethiopia), a Soil-Vegetation-Atmosphere Transfer (SVAT) model forced with remote sensing and numerical weather prediction data has been used. This model runs at pre-operational level in the framework of the EUMETSAT LSA-SAF (Land Surface Analysis Satellite Application Facility) using SEVIRI and ECMWF data, as well as the ECOCLIMAP database to characterize the vegetation. The model generates ET images at the Meteosat Second Generation (MSG) spatial resolution (3 km at subsatellite point),with a temporal resolution of 30 min and monitors the entire MSG disk which covers Europe, Africa and part of Sud America . The SVAT model was run for 2007 using two approaches. The first approach is at the standard pre-operational mode. The second incorporates remote sensing information at various spatial resolutions going from LANDSAT (30m) to SEVIRI (3-5 km) passing by AWIFS (56m) and MODIS (250m). Fine spatial resolution data consists of crop type classification which enable to identify areas where pure crop specific MODIS time series can be compiled and used to derive Leaf Area Index estimations for the most important crops (wheat and maize). The use of this information allowed to characterize the type of vegetation and its state of development in a more accurate way than using the ECOCLIMAP database. Finally, the CASA method was applied using the evapotranspiration images with FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) images from LSA-SAF to obtain Dry Matter Productivity (DMP) and crop yield. The potential of using evapotranspiration obtained from remote sensing in crop growth modeling is studied and discussed. Results of comparing the evapotranspiration obtained with ground truth data are shown as well as the influence of using high resolution information to characterize the vegetation in the evapotranspiration estimation. The values of DMP and yield obtained with the CASA method are compared with those obtained using crop growth modeling and field data, showing the potential of using this simplified remote sensing method for crop monitoring and yield forecasting. This methodology could be applied in an operative way to the entire MSG disk, allowing the continuous crop growth monitoring.

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Reservoir Characterization using geostatistical and numerical modeling in GIS with noble gas geochemistry

NASA Astrophysics Data System (ADS)

Vasquez, D. A.; Swift, J. N.; Tan, S.; Darrah, T. H.

2013-12-01

The integration of precise geochemical analyses with quantitative engineering modeling into an interactive GIS system allows for a sophisticated and efficient method of reservoir engineering and characterization. Geographic Information Systems (GIS) is utilized as an advanced technique for oil field reservoir analysis by combining field engineering and geological/geochemical spatial datasets with the available systematic modeling and mapping methods to integrate the information into a spatially correlated first-hand approach in defining surface and subsurface characteristics. Three key methods of analysis include: 1) Geostatistical modeling to create a static and volumetric 3-dimensional representation of the geological body, 2) Numerical modeling to develop a dynamic and interactive 2-dimensional model of fluid flow across the reservoir and 3) Noble gas geochemistry to further define the physical conditions, components and history of the geologic system. Results thus far include using engineering algorithms for interpolating electrical well log properties across the field (spontaneous potential, resistivity) yielding a highly accurate and high-resolution 3D model of rock properties. Results so far also include using numerical finite difference methods (crank-nicholson) to solve for equations describing the distribution of pressure across field yielding a 2D simulation model of fluid flow across reservoir. Ongoing noble gas geochemistry results will also include determination of the source, thermal maturity and the extent/style of fluid migration (connectivity, continuity and directionality). Future work will include developing an inverse engineering algorithm to model for permeability, porosity and water saturation.This combination of new and efficient technological and analytical capabilities is geared to provide a better understanding of the field geology and hydrocarbon dynamics system with applications to determine the presence of hydrocarbon pay zones (or other reserves) and improve oil field management (e.g. perforating, drilling, EOR and reserves estimation)

SU-F-T-569: Implementation of a Patient Specific QA Method Using EBT-XD for CyberKnife SRS/SBRT Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zerouali, K; Aubry, J; Doucet, R

2016-06-15

Purpose: To implement the new EBT-XD Gafchromic films for accurate dosimetric and geometric validation of stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) CyberKnife (CK) patient specific QA. Methods: Film calibration was performed using a triplechannel film analysis on an Epson 10000XL scanner. Calibration films were irradiated using a Varian Clinac 21EX flattened beam (0 to 20 Gy), to ensure sufficient dose homogeneity. Films were scanned to a resolution of 0.3 mm, 24 hours post irradiation following a well-defined protocol. A set of 12 QA was performed for several types of CK plans: trigeminal neuralgia, brain metastasis, prostate andmore » lung tumors. A custom made insert for the CK head phantom has been manufactured to yield an accurate measured to calculated dose registration. When the high dose region was large enough, absolute dose was also measured with an ionization chamber. Dose calculation is performed using MultiPlan Ray-tracing algorithm for all cases since the phantom is mostly made from near water-equivalent plastic. Results: Good agreement (<2%) was found between the dose to the chamber and the film, when a chamber measurement was possible The average dose difference and standard deviations between film measurements and TPS calculations were respectively 1.75% and 3%. The geometric accuracy has been estimated to be <1 mm, combining robot positioning uncertainty and film registration to calculated dose. Conclusion: Patient specific QA measurements using EBT-XD films yielded a full 2D dose plane with high spatial resolution and acceptable dose accuracy. This method is particularly promising for trigeminal neuralgia plan QA, where the positioning of the spatial dose distribution is equally or more important than the absolute delivered dose to achieve clinical goals.« less

FlyAR: augmented reality supported micro aerial vehicle navigation.

PubMed

Zollmann, Stefanie; Hoppe, Christof; Langlotz, Tobias; Reitmayr, Gerhard

2014-04-01

Micro aerial vehicles equipped with high-resolution cameras can be used to create aerial reconstructions of an area of interest. In that context automatic flight path planning and autonomous flying is often applied but so far cannot fully replace the human in the loop, supervising the flight on-site to assure that there are no collisions with obstacles. Unfortunately, this workflow yields several issues, such as the need to mentally transfer the aerial vehicle’s position between 2D map positions and the physical environment, and the complicated depth perception of objects flying in the distance. Augmented Reality can address these issues by bringing the flight planning process on-site and visualizing the spatial relationship between the planned or current positions of the vehicle and the physical environment. In this paper, we present Augmented Reality supported navigation and flight planning of micro aerial vehicles by augmenting the user’s view with relevant information for flight planning and live feedback for flight supervision. Furthermore, we introduce additional depth hints supporting the user in understanding the spatial relationship of virtual waypoints in the physical world and investigate the effect of these visualization techniques on the spatial understanding.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ogura, Toshihiko, E-mail: t-ogura@aist.go.jp

Scanning electron microscopy (SEM) has been widely used to examine biological specimens of bacteria, viruses and proteins. Until now, atmospheric and/or wet biological specimens have been examined using various atmospheric holders or special equipment involving SEM. Unfortunately, they undergo heavy radiation damage by the direct electron beam. In addition, images of unstained biological samples in water yield poor contrast. We recently developed a new analytical technology involving a frequency transmission electric-field (FTE) method based on thermionic SEM. This method is suitable for high-contrast imaging of unstained biological specimens. Our aim was to optimise the method. Here we describe a high-resolutionmore » FTE system based on field-emission SEM; it allows for imaging and nanoscale examination of various biological specimens in water without radiation damage. The spatial resolution is 8 nm, which is higher than 41 nm of the existing FTE system. Our new method can be easily utilised for examination of unstained biological specimens including bacteria, viruses and protein complexes. Furthermore, our high-resolution FTE system can be used for diverse liquid samples across a broad range of scientific fields, e.g. nanoparticles, nanotubes and organic and catalytic materials. - Highlights: • We developed a high-resolution frequency transmission electric-field (FTE) system. • High-resolution FTE system is introduced in the field-emission SEM. • The spatial resolution of high-resolution FTE method is 8 nm. • High-resolution FTE system enables observation of the intact IgM particles in water.« less

Global scale modeling of riverine sediment loads: tropical rivers in a global context

NASA Astrophysics Data System (ADS)

Cohen, Sagy; Syvitski, James; Kettner, Albert

2015-04-01

A global scale riverine sediment flux model (termed WBMsed) is introduced. The model predicts spatially and temporally explicit water, suspended sediment and nutrients flux in relatively high resolutions (6 arc-min and daily). Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Tropical river systems, wherein much of a drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds, have comparatively low inter-annual variation in sediment yield. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries

Enhanced photocatalytic CO2 reduction to CH4 over separated dual co-catalysts Au and RuO2

NASA Astrophysics Data System (ADS)

Dong, Chunyang; Hu, Songchang; Xing, Mingyang; Zhang, Jinlong

2018-04-01

A spatially separated, dual co-catalyst photocatalytic system was constructed by the stepwise introduction of RuO2 and Au nanoparticles (NPs) at the internal and external surfaces of a three dimensional, hierarchically ordered TiO2-SiO2 (HTSO) framework (the final photocatalyst was denoted as Au/HRTSO). Characterization by HR-TEM, EDS-mapping, XRD and XPS confirmed the existence and spatially separated locations of Au and RuO2. In CO2 photocatalytic reduction (CO2PR), Au/HRTSO (0.8%) shows the optimal performance in both the activity and selectivity towards CH4; the CH4 yield is almost twice that of the singular Au/HTSO or HRTSO (0.8%, weight percentage of RuO2) counterparts. Generally, Au NPs at the external surface act as electron trapping agents and RuO2 NPs at the inner surface act as hole collectors. This advanced spatial configuration could promote charge separation and transfer efficiency, leading to enhanced CO2PR performance in both the yield and selectivity toward CH4 under simulated solar light irradiation.

Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

NASA Astrophysics Data System (ADS)

Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

2014-12-01

We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

In vitro synchrotron-based radiography of micro-gap formation at the implant-abutment interface of two-piece dental implants.

PubMed

Rack, A; Rack, T; Stiller, M; Riesemeier, H; Zabler, S; Nelson, K

2010-03-01

Micro-gap formation at the implant-abutment interface of two-piece dental implants was investigated in vitro using high-resolution radiography in combination with hard X-ray synchrotron radiation. Images were taken with the specimen under different mechanical loads of up to 100 N. The aim of this investigation was to prove the existence of micro-gaps for implants with conical connections as well as to study the mechanical behavior of the mating zone of conical implants during loading. Synchrotron-based radiography in comparison with classical laboratory radiography yields high spatial resolution in combination with high contrast even when exploiting micro-sized features in highly attenuating objects. The first illustration of a micro-gap which was previously indistinguishable by laboratory methods underlines that the complex micro-mechanical behavior of implants requires further in vitro investigations where synchrotron-based micro-imaging is one of the prerequisites.

Nanoscale Spectroscopic Imaging of Organic Semiconductor Films by Plasmon-Polariton Coupling

NASA Astrophysics Data System (ADS)

Zhang, D.; Heinemeyer, U.; Stanciu, C.; Sackrow, M.; Braun, K.; Hennemann, L. E.; Wang, X.; Scholz, R.; Schreiber, F.; Meixner, A. J.

2010-02-01

Tip-enhanced near-field optical images and correlated topographic images of an organic semiconductor film (diindenoperylene, DIP) on Si have been recorded with high optical contrast and high spatial resolution (17 nm) using a parabolic mirror with a high numerical aperture for tip illumination and signal collection. The DIP molecular domain boundaries being one to four molecular layers (1.5-6 nm) high are resolved topographically by a shear-force scanning tip and optically by simultaneously recording the 6×105 times enhanced photoluminescence (PL). The excitation is 4×104 times enhanced and the intrinsically weak PL-yield of the DIP-film is 15-fold enhanced by the tip. The Raman spectra indicate an upright orientation of the DIP molecules. The enhanced PL contrast results from the local film morphology via stronger coupling between the tip plasmon and the exciton-polariton in the DIP film.

Spatial abilities and anatomy knowledge assessment: A systematic review.

PubMed

Langlois, Jean; Bellemare, Christian; Toulouse, Josée; Wells, George A

2017-06-01

Anatomy knowledge has been found to include both spatial and non-spatial components. However, no systematic evaluation of studies relating spatial abilities and anatomy knowledge has been undertaken. The objective of this study was to conduct a systematic review of the relationship between spatial abilities test and anatomy knowledge assessment. A literature search was done up to March 20, 2014 in Scopus and in several databases on the OvidSP and EBSCOhost platforms. Of the 556 citations obtained, 38 articles were identified and fully reviewed yielding 21 eligible articles and their quality were formally assessed. Non-significant relationships were found between spatial abilities test and anatomy knowledge assessment using essays and non-spatial multiple-choice questions. Significant relationships were observed between spatial abilities test and anatomy knowledge assessment using practical examination, three-dimensional synthesis from two-dimensional views, drawing of views, and cross-sections. Relationships between spatial abilities test and anatomy knowledge assessment using spatial multiple-choice questions were unclear. The results of this systematic review provide evidence for spatial and non-spatial methods of anatomy knowledge assessment. Anat Sci Educ 10: 235-241. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

DOE PAGES

Wainwright, Haruko M.; Liljedahl, Anna K.; Dafflon, Baptiste; ...

2017-04-03

This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE=2.9cm), with a spatial sampling of 10cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE=6.0cm) andmore » a fine spatial sampling (4cm×4cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE=6.0cm), at 0.5m resolution and over the lidar domain (750m×700m).« less

High-resolution, time-resolved MRA provides superior definition of lower-extremity arterial segments compared to 2D time-of-flight imaging.

PubMed

Thornton, F J; Du, J; Suleiman, S A; Dieter, R; Tefera, G; Pillai, K R; Korosec, F R; Mistretta, C A; Grist, T M

2006-08-01

To evaluate a novel time-resolved contrast-enhanced (CE) projection reconstruction (PR) magnetic resonance angiography (MRA) method for identifying potential bypass graft target vessels in patients with Class II-IV peripheral vascular disease. Twenty patients (M:F = 15:5, mean age = 58 years, range = 48-83 years), were recruited from routine MRA referrals. All imaging was performed on a 1.5 T MRI system with fast gradients (Signa LX; GE Healthcare, Waukesha, WI). Images were acquired with a novel technique that combined undersampled PR with a time-resolved acquisition to yield an MRA method with high temporal and spatial resolution. The method is called PR hyper time-resolved imaging of contrast kinetics (PR-hyperTRICKS). Quantitative and qualitative analyses were used to compare two-dimensional (2D) time-of-flight (TOF) and PR-hyperTRICKS in 13 arterial segments per lower extremity. Statistical analysis was performed with the Wilcoxon signed-rank test. Fifteen percent (77/517) of the vessels were scored as missing or nondiagnostic with 2D TOF, but were scored as diagnostic with PR-hyperTRICKS. Image quality was superior with PR-hyperTRICKS vs. 2D TOF (on a four-point scale, mean rank = 3.3 +/- 1.2 vs. 2.9 +/- 1.2, P < 0.0001). PR-hyperTRICKS produced images with high contrast-to-noise ratios (CNR) and high spatial and temporal resolution. 2D TOF images were of inferior quality due to moderate spatial resolution, inferior CNR, greater flow-related artifacts, and absence of temporal resolution. PR-hyperTRICKS provides superior preoperative assessment of lower limb ischemia compared to 2D TOF.

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wainwright, Haruko M.; Liljedahl, Anna K.; Dafflon, Baptiste

This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE=2.9cm), with a spatial sampling of 10cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE=6.0cm) andmore » a fine spatial sampling (4cm×4cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE=6.0cm), at 0.5m resolution and over the lidar domain (750m×700m).« less

A hybrid framework for assessing maize drought vulnerability in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Kamali, B.; Abbaspour, K. C.; Wehrli, B.; Yang, H.

2017-12-01

Drought has devastating impacts on crop yields. Quantifying drought vulnerability is the first step to better design of mitigation policies. The vulnerability of crop yield to drought has been assessed with different methods, however they lack a standardized base to measure its components and a procedure that facilitates spatial and temporal comparisons. This study attempts to quantify maize drought vulnerability through linking the Drought Exposure Index (DEI) to the Crop Failure Index (CFI). DEI and CFI were defined by fitting probability distribution functions to precipitation and maize yield respectively. To acquire crop drought vulnerability index (CDVI), DEI and CFI were combined in a hybrid framework which classifies CDVI with the same base as DEI and CFI. The analysis were implemented on Sub-Saharan African countries using maize yield simulated with the Environmental Policy Integrated Climate (EPIC) model at 0.5° resolution. The model was coupled with the Sequential Uncertainty Fitting algorithm for calibration at country level. Our results show that Central Africa and those Western African countries located below the Sahelian strip receive higher amount of precipitation, but experience high crop failure. Therefore, they are identified as more vulnerable regions compared to countries such as South Africa, Tanzania, and Kenya. We concluded that our hybrid approach complements information on crop drought vulnerability quantification and can be applied to different regions and scales.

Spatial irregularities in Jupiter's upper ionosphere observed by Voyager radio occultations

NASA Technical Reports Server (NTRS)

Hinson, D. P.; Tyler, G. L.

1982-01-01

Radio scintillations (at 3.6 and 13 cm) produced by scattering from ionospheric irregularities during the Voyager occultations are interpreted using a weak-scattering theory. Least squares solutions for ionospheric parameters derived from the observed fluctuation spectra yield estimates of (1) the axial ratio, (2) angular orientation of the anisotropic irregularities, (3) the power law exponent of the spatial spectrum of irregularities, and (4) the magnitude of the spatial variations in electron density. It is shown that the measured angular orientation of the anisotropic irregularities indicates magnetic field direction and may provide a basis for refining Jovian magnetic field models.

Application of future remote sensing systems to irrigation

NASA Technical Reports Server (NTRS)

Miller, L. D.

1982-01-01

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Space-time mesh adaptation for solute transport in randomly heterogeneous porous media.

PubMed

Dell'Oca, Aronne; Porta, Giovanni Michele; Guadagnini, Alberto; Riva, Monica

2018-05-01

We assess the impact of an anisotropic space and time grid adaptation technique on our ability to solve numerically solute transport in heterogeneous porous media. Heterogeneity is characterized in terms of the spatial distribution of hydraulic conductivity, whose natural logarithm, Y, is treated as a second-order stationary random process. We consider nonreactive transport of dissolved chemicals to be governed by an Advection Dispersion Equation at the continuum scale. The flow field, which provides the advective component of transport, is obtained through the numerical solution of Darcy's law. A suitable recovery-based error estimator is analyzed to guide the adaptive discretization. We investigate two diverse strategies guiding the (space-time) anisotropic mesh adaptation. These are respectively grounded on the definition of the guiding error estimator through the spatial gradients of: (i) the concentration field only; (ii) both concentration and velocity components. We test the approach for two-dimensional computational scenarios with moderate and high levels of heterogeneity, the latter being expressed in terms of the variance of Y. As quantities of interest, we key our analysis towards the time evolution of section-averaged and point-wise solute breakthrough curves, second centered spatial moment of concentration, and scalar dissipation rate. As a reference against which we test our results, we consider corresponding solutions associated with uniform space-time grids whose level of refinement is established through a detailed convergence study. We find a satisfactory comparison between results for the adaptive methodologies and such reference solutions, our adaptive technique being associated with a markedly reduced computational cost. Comparison of the two adaptive strategies tested suggests that: (i) defining the error estimator relying solely on concentration fields yields some advantages in grasping the key features of solute transport taking place within low velocity regions, where diffusion-dispersion mechanisms are dominant; and (ii) embedding the velocity field in the error estimator guiding strategy yields an improved characterization of the forward fringe of solute fronts which propagate through high velocity regions. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Groundwater Availability in Fractured Rock Aquifers of Northern Ugandan Refugee Settlements

NASA Astrophysics Data System (ADS)

Frederiks, R.; Lowry, C.; Mutiibwa, R.; Moisy, S.; Thapa, L.; Oriba, J.

2017-12-01

In the past two years, Uganda has witnessed an influx of nearly one million refugees who have settled in the sparsely populated northwestern region of the country. This rapid population growth has created high demand for clean water resources. Water supply has been unable to keep pace with demand because the fractured rock aquifers underlying the region often produce low yielding wells. To facilitate management of groundwater resources, it is necessary to quantify the spatial distribution of groundwater. In fractured rock aquifers, there is significant spatial variability in water storage because fractures must be both connected and abundant for water to be extracted in usable quantities. Two conceptual models were evaluated to determine the groundwater storage mechanism in the fractured crystalline bedrock aquifers of northwestern Uganda where by permeability is controlled by faulting, which opens up fractures in the bedrock, or weathering, which occurs when water dissolves components of rock. In order to test these two conceptual models, geologic well logs and available hydrologic data were collected and evaluated using geostatistical and numerical groundwater models. The geostatistical analysis focused on identifying spatially distributed patterns of high and low water yield. The conceptual models were evaluated numerically using four inverse groundwater MODFLOW models based on head and estimated flux targets. The models were based on: (1) the mapped bedrock units using an equivalent porous media approach (2) bedrock units with the addition of known fault zones (3) bedrock units with predicted units of deep weathering based on surface slopes, and (4) bedrock units with discrete faults and simulated weathered zones. Predicting permeable zones is vital for water well drilling in much of East Africa and South America where there is an abundance of both fractured rock and tectonic activity. Given that the population of these developing regions is growing, the demand for sufficient clean water is likely to increase significantly in the next few decades. Thus, it is necessary to improve our ability to predict locations of permeable zones in fractured rock aquifers.

Towards a New Assessment of Urban Areas from Local to Global Scales

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Roy Chowdhury, P. K.; McKee, J.; Weaver, J.; Bright, E.; Weber, E.

2015-12-01

Since early 2000s, starting with NASA MODIS, satellite based remote sensing has facilitated collection of imagery with medium spatial resolution but high temporal resolution (daily). This trend continues with an increasing number of sensors and data products. Increasing spatial and temporal resolutions of remotely sensed data archives, from both public and commercial sources, have significantly enhanced the quality of mapping and change data products. However, even with automation of such analysis on evolving computing platforms, rates of data processing have been suboptimal largely because of the ever-increasing pixel to processor ratio coupled with limitations of the computing architectures. Novel approaches utilizing spatiotemporal data mining techniques and computational architectures have emerged that demonstrates the potential for sustained and geographically scalable landscape monitoring to be operational. We exemplify this challenge with two broad research initiatives on High Performance Geocomputation at Oak Ridge National Laboratory: (a) mapping global settlement distribution; (b) developing national critical infrastructure databases. Our present effort, on large GPU based architectures, to exploit high resolution (1m or less) satellite and airborne imagery for extracting settlements at global scale is yielding understanding of human settlement patterns and urban areas at unprecedented resolution. Comparison of such urban land cover database, with existing national and global land cover products, at various geographic scales in selected parts of the world is revealing intriguing patterns and insights for urban assessment. Early results, from the USA, Taiwan, and Egypt, indicate closer agreements (5-10%) in urban area assessments among databases at larger, aggregated geographic extents. However, spatial variability at local scales could be significantly different (over 50% disagreement).

Two-Photon-Excited Silica and Organosilica Nanoparticles for Spatiotemporal Cancer Treatment.

PubMed

Croissant, Jonas G; Zink, Jeffrey I; Raehm, Laurence; Durand, Jean-Olivier

2018-04-01

Coherent two-photon-excited (TPE) therapy in the near-infrared (NIR) provides safer cancer treatments than current therapies lacking spatial and temporal selectivities because it is characterized by a 3D spatial resolution of 1 µm 3 and very low scattering. In this review, the principle of TPE and its significance in combination with organosilica nanoparticles (NPs) are introduced and then studies involving the design of pioneering TPE-NIR organosilica nanomaterials are discussed for bioimaging, drug delivery, and photodynamic therapy. Organosilica nanoparticles and their rich and well-established chemistry, tunable composition, porosity, size, and morphology provide ideal platforms for minimal side-effect therapies via TPE-NIR. Mesoporous silica and organosilica nanoparticles endowed with high surface areas can be functionalized to carry hydrophobic and biologically unstable two-photon absorbers for drug delivery and diagnosis. Currently, most light-actuated clinical therapeutic applications with NPs involve photodynamic therapy by singlet oxygen generation, but low photosensitizing efficiencies, tumor resistance, and lack of spatial resolution limit their applicability. On the contrary, higher photosensitizing yields, versatile therapies, and a unique spatial resolution are available with engineered two-photon-sensitive organosilica particles that selectively impact tumors while healthy tissues remain untouched. Patients suffering pathologies such as retinoblastoma, breast, and skin cancers will greatly benefit from TPE-NIR ultrasensitive diagnosis and therapy. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Probing GFP-actin diffusion in living cells using fluorescence correlation spectroscopy.

PubMed

Engelke, Hanna; Heinrich, Doris; Rädler, Joachim O

2010-12-22

The cytoskeleton of eukaryotic cells is continuously remodeled by polymerization and depolymerization of actin. Consequently, the relative content of polymerized filamentous actin (F-actin) and monomeric globular actin (G-actin) is subject to temporal and spatial fluctuations. Since fluorescence correlation spectroscopy (FCS) can measure the diffusion of fluorescently labeled actin it seems likely that FCS allows us to determine the dynamics and hence indirectly the structural properties of the cytoskeleton components with high spatial resolution. To this end we investigate the FCS signal of GFP-actin in living Dictyostelium discoideum cells and explore the inherent spatial and temporal signatures of the actin cytoskeleton. Using the free green fluorescent protein (GFP) as a reference, we find that actin diffusion inside cells is dominated by G-actin and slower than diffusion in diluted cell extract. The FCS signal in the dense cortical F-actin network near the cell membrane is probed using the cytoskeleton protein LIM and is found to be slower than cytosolic G-actin diffusion. Furthermore, we show that polymerization of the cytoskeleton induced by Jasplakinolide leads to a substantial decrease of G-actin diffusion. Pronounced fluctuations in the distribution of the FCS correlation curves can be induced by latrunculin, which is known to induce actin waves. Our work suggests that the FCS signal of GFP-actin in combination with scanning or spatial correlation techniques yield valuable information about the local dynamics and concomitant cytoskeletal properties.

Characterizing fishing effort and spatial extent of coastal fisheries.

PubMed

Stewart, Kelly R; Lewison, Rebecca L; Dunn, Daniel C; Bjorkland, Rhema H; Kelez, Shaleyla; Halpin, Patrick N; Crowder, Larry B

2010-12-29

Biodiverse coastal zones are often areas of intense fishing pressure due to the high relative density of fishing capacity in these nearshore regions. Although overcapacity is one of the central challenges to fisheries sustainability in coastal zones, accurate estimates of fishing pressure in coastal zones are limited, hampering the assessment of the direct and collateral impacts (e.g., habitat degradation, bycatch) of fishing. We compiled a comprehensive database of fishing effort metrics and the corresponding spatial limits of fisheries and used a spatial analysis program (FEET) to map fishing effort density (measured as boat-meters per km²) in the coastal zones of six ocean regions. We also considered the utility of a number of socioeconomic variables as indicators of fishing pressure at the national level; fishing density increased as a function of population size and decreased as a function of coastline length. Our mapping exercise points to intra and interregional 'hotspots' of coastal fishing pressure. The significant and intuitive relationships we found between fishing density and population size and coastline length may help with coarse regional characterizations of fishing pressure. However, spatially-delimited fishing effort data are needed to accurately map fishing hotspots, i.e., areas of intense fishing activity. We suggest that estimates of fishing effort, not just target catch or yield, serve as a necessary measure of fishing activity, which is a key link to evaluating sustainability and environmental impacts of coastal fisheries.

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Astrophysics Data System (ADS)

Watts, Louis A.

1993-06-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Visualizing single molecules interacting with nuclear pore complexes by narrow-field epifluorescence microscopy

PubMed Central

Yang, Weidong; Musser, Siegfried M.

2008-01-01

The utility of single molecule fluorescence (SMF) for understanding biological reactions has been amply demonstrated by a diverse series of studies over the last decade. In large part, the molecules of interest have been limited to those within a small focal volume or near a surface to achieve the high sensitivity required for detecting the inherently weak signals arising from individual molecules. Consequently, the investigation of molecular behavior with high time and spatial resolution deep within cells using SMF has remained challenging. Recently, we demonstrated that narrow-field epifluorescence microscopy allows visualization of nucleocytoplasmic transport at the single cargo level. We describe here the methodological approach that yields 2 ms and ∼15 nm resolution for a stationary particle. The spatial resolution for a mobile particle is inherently worse, and depends on how fast the particle is moving. The signal-to-noise ratio is sufficiently high to directly measure the time a single cargo molecule spends interacting with the nuclear pore complex. Particle tracking analysis revealed that cargo molecules randomly diffuse within the nuclear pore complex, exiting as a result of a single rate-limiting step. We expect that narrow-field epifluorescence microscopy will be useful for elucidating other binding and trafficking events within cells. PMID:16879979

Evolution of miniature detectors and focal plane arrays for infrared sensors

NASA Technical Reports Server (NTRS)

Watts, Louis A.

1993-01-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

When Deriving the Spatial QRS-T Angle from the 12-lead ECG, which Transform is More Frank: Regression or Inverse Dower?

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Cortez, Daniel

2010-01-01

Our primary objective was to ascertain which commonly used 12-to-Frank-lead transformation yields spatial QRS-T angle values closest to those obtained from simultaneously collected true Frank-lead recordings. Simultaneous 12-lead and Frank XYZ-lead recordings were analyzed for 100 post-myocardial infarction patients and 50 controls. Relative agreement, with true Frank-lead results, of 12-to-Frank-lead transformed results for the spatial QRS-T angle using Kors regression versus inverse Dower was assessed via ANOVA, Lin s concordance and Bland-Altman plots. Spatial QRS-T angles from the true Frank leads were not significantly different than those derived from the Kors regression-related transformation but were significantly smaller than those derived from the inverse Dower-related transformation (P less than 0.001). Independent of method, spatial mean QRS-T angles were also always significantly larger than spatial maximum (peaks) QRS-T angles. Spatial QRS-T angles are best approximated by regression-related transforms. Spatial mean and spatial peaks QRS-T angles should also not be used interchangeably.

Large-Area High-Performance Flexible Pressure Sensor with Carbon Nanotube Active Matrix for Electronic Skin.

PubMed

Nela, Luca; Tang, Jianshi; Cao, Qing; Tulevski, George; Han, Shu-Jen

2018-03-14

Artificial "electronic skin" is of great interest for mimicking the functionality of human skin, such as tactile pressure sensing. Several important performance metrics include mechanical flexibility, operation voltage, sensitivity, and accuracy, as well as response speed. In this Letter, we demonstrate a large-area high-performance flexible pressure sensor built on an active matrix of 16 × 16 carbon nanotube thin-film transistors (CNT TFTs). Made from highly purified solution tubes, the active matrix exhibits superior flexible TFT performance with high mobility and large current density, along with a high device yield of nearly 99% over 4 inch sample area. The fully integrated flexible pressure sensor operates within a small voltage range of 3 V and shows superb performance featuring high spatial resolution of 4 mm, faster response than human skin (<30 ms), and excellent accuracy in sensing complex objects on both flat and curved surfaces. This work may pave the road for future integration of high-performance electronic skin in smart robotics and prosthetic solutions.

Algorithms for Brownian first-passage-time estimation

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2009-09-01

A class of algorithms in discrete space and continuous time for Brownian first-passage-time estimation is considered. A simple algorithm is derived that yields exact mean first-passage times (MFPTs) for linear potentials in one dimension, regardless of the lattice spacing. When applied to nonlinear potentials and/or higher spatial dimensions, numerical evidence suggests that this algorithm yields MFPT estimates that either outperform or rival Langevin-based (discrete time and continuous space) estimates.

Constraints on Water Reservoir Lifetimes From Catchment-Wide 10Be Erosion Rates—A Case Study From Western Turkey

NASA Astrophysics Data System (ADS)

Heineke, Caroline; Hetzel, Ralf; Akal, Cüneyt; Christl, Marcus

2017-11-01

The functionality and retention capacity of water reservoirs is generally impaired by upstream erosion and reservoir sedimentation, making a reliable assessment of erosion indispensable to estimate reservoir lifetimes. Widely used river gauging methods may underestimate sediment yield, because they do not record rare, high-magnitude events and may underestimate bed load transport. Hence, reservoir lifetimes calculated from short-term erosion rates should be regarded as maximum values. We propose that erosion rates from cosmogenic 10Be, which commonly integrate over hundreds to thousands of years, are useful to complement short-term sediment yield estimates and should be employed to estimate minimum reservoir lifetimes. Here we present 10Be erosion rates for the drainage basins of six water reservoirs in Western Turkey, which are located in a tectonically active region with easily erodible bedrock. Our 10Be erosion rates for these catchments are high, ranging from ˜170 to ˜1,040 t/km2/yr. When linked to reservoir volumes, they yield minimum reservoir lifetimes between 25 ± 5 and 1,650 ± 360 years until complete filling, with four reservoirs having minimum lifespans of ≤110 years. In a neighboring region with more resistant bedrock and less tectonic activity, we obtain much lower catchment-wide 10Be erosion rates of ˜33 to ˜95 t/km2/yr, illustrating that differences in lithology and tectonic boundary conditions can cause substantial variations in erosion even at a spatial scale of only ˜50 km. In conclusion, we suggest that both short-term sediment yield estimates and 10Be erosion rates should be employed to predict the lifetimes of reservoirs.

Mapping quantum yield for (Fe-Zn-Sn-Ti)Ox photoabsorbers using a high throughput photoelectrochemical screening system.

PubMed

Xiang, Chengxiang; Haber, Joel; Marcin, Martin; Mitrovic, Slobodan; Jin, Jian; Gregoire, John M

2014-03-10

Combinatorial synthesis and screening of light absorbers are critical to material discoveries for photovoltaic and photoelectrochemical applications. One of the most effective ways to evaluate the energy-conversion properties of a semiconducting light absorber is to form an asymmetric junction and investigate the photogeneration, transport and recombination processes at the semiconductor interface. This standard photoelectrochemical measurement is readily made on a semiconductor sample with a back-side metallic contact (working electrode) and front-side solution contact. In a typical combinatorial material library, each sample shares a common back contact, requiring novel instrumentation to provide spatially resolved and thus sample-resolved measurements. We developed a multiplexing counter electrode with a thin layer assembly, in which a rectifying semiconductor/liquid junction was formed and the short-circuit photocurrent was measured under chopped illumination for each sample in a material library. The multiplexing counter electrode assembly demonstrated a photocurrent sensitivity of sub-10 μA cm(-2) with an external quantum yield sensitivity of 0.5% for each semiconductor sample under a monochromatic ultraviolet illumination source. The combination of cell architecture and multiplexing allows high-throughput modes of operation, including both fast-serial and parallel measurements. To demonstrate the performance of the instrument, the external quantum yields of 1819 different compositions from a pseudoquaternary metal oxide library, (Fe-Zn-Sn-Ti)Ox, at 385 nm were collected in scanning serial mode with a throughput of as fast as 1 s per sample. Preliminary screening results identified a promising ternary composition region centered at Fe0.894Sn0.103Ti0.0034Ox, with an external quantum yield of 6.7% at 385 nm.

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Suspended sediment source areas and future climate impact on soil erosion and sediment yield in a New York City water supply watershed, USA

NASA Astrophysics Data System (ADS)

Mukundan, Rajith; Pradhanang, Soni M.; Schneiderman, Elliot M.; Pierson, Donald C.; Anandhi, Aavudai; Zion, Mark S.; Matonse, Adão H.; Lounsbury, David G.; Steenhuis, Tammo S.

2013-02-01

High suspended sediment loads and the resulting turbidity can impact the use of surface waters for water supply and other designated uses. Changes in fluvial sediment loads influence material fluxes, aquatic geochemistry, water quality, channel morphology, and aquatic habitats. Therefore, quantifying spatial and temporal patterns in sediment loads is important both for understanding and predicting soil erosion and sediment transport processes as well as watershed-scale management of sediment and associated pollutants. A case study from the 891 km2 Cannonsville watershed, one of the major watersheds in the New York City water supply system is presented. The objective of this study was to apply Soil and Water Assessment Tool-Water Balance (SWAT-WB), a physically based semi-distributed model to identify suspended sediment generating source areas under current conditions and to simulate potential climate change impacts on soil erosion and suspended sediment yield in the study watershed for a set of future climate scenarios representative of the period 2081-2100. Future scenarios developed using nine global climate model (GCM) simulations indicate a sharp increase in the annual rates of soil erosion although a similar result in sediment yield at the watershed outlet was not evident. Future climate related changes in soil erosion and sediment yield appeared more significant in the winter due to a shift in the timing of snowmelt and also due to a decrease in the proportion of precipitation received as snow. Although an increase in future summer precipitation was predicted, soil erosion and sediment yield appeared to decrease owing to an increase in soil moisture deficit and a decrease in water yield due to increased evapotranspiration.

Spatial filter system as an optical relay line

DOEpatents

Hunt, John T.; Renard, Paul A.

1979-01-01

A system consisting of a set of spatial filters that are used to optically relay a laser beam from one position to a downstream position with minimal nonlinear phase distortion and beam intensity variation. The use of the device will result in a reduction of deleterious beam self-focusing and produce a significant increase in neutron yield from the implosion of targets caused by their irradiation with multi-beam glass laser systems.

Detection of bio-signature by microscopy and mass spectrometry

NASA Astrophysics Data System (ADS)

Tulej, M.; Wiesendanger, R.; Neuland, M., B.; Meyer, S.; Wurz, P.; Neubeck, A.; Ivarsson, M.; Riedo, V.; Moreno-Garcia, P.; Riedo, A.; Knopp, G.

2017-09-01

We demonstrate detection of micro-sized fossilized bacteria by means of microscopy and mass spectrometry. The characteristic structures of lifelike forms are visualized with a micrometre spatial resolution and mass spectrometric analyses deliver elemental and isotope composition of host and fossilized materials. Our studies show that high selectivity in isolation of fossilized material from host phase can be achieved while applying a microscope visualization (location), a laser ablation ion source with sufficiently small laser spot size and applying depth profiling method. Our investigations shows that fossilized features can be well isolated from host phase. The mass spectrometric measurements can be conducted with sufficiently high accuracy and precision yielding quantitative elemental and isotope composition of micro-sized objects. The current performance of the instrument allows the measurement of the isotope fractionation in per mill level and yield exclusively definition of the origin of the investigated species by combining optical visualization of investigated samples (morphology and texture), chemical characterization of host and embedded in the host micro-sized structure. Our isotope analyses involved bio-relevant B, C, S, and Ni isotopes which could be measured with sufficiently accuracy to conclude about the nature of the micro-sized objects.