980 resultados para Geostatistical inversion


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Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

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Based on theoretical arguments we propose a possible route for controlling the band-gap in the promising photovoltaic material CdIn2S4. Our ab initio calculations show that the experimental degree of inversion in this spinel (fraction of tetrahedral sites occupied by In) corresponds approximately to the equilibrium value given by the minimum of the theoretical inversion free energy at a typical synthesis temperature. Modification of this temperature, or of the cooling rate after synthesis, is then expected to change the inversion degree, which in turn sensitively tunes the electronic band-gap of the solid, as shown here by Heyd-Scuseria-Ernzerhof screened hybrid functional calculations.

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Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model.

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FeM2X4 spinels, where M is a transition metal and X is oxygen or sulfur, are candidate materials for spin filters, one of the key devices in spintronics. We present here a computational study of the inversion thermodynamics and the electronic structure of these (thio)spinels for M = Cr, Mn, Co, Ni, using calculations based on the density functional theory with on-site Hubbard corrections (DFT+U). The analysis of the configurational free energies shows that different behaviour is expected for the equilibrium cation distributions in these structures: FeCr2X4 and FeMn2S4 are fully normal, FeNi2X4 and FeCo2S4 are intermediate, and FeCo2O4 and FeMn2O4 are fully inverted. We have analyzed the role played by the size of the ions and by the crystal field stabilization effects in determining the equilibrium inversion degree. We also discuss how the electronic and magnetic structure of these spinels is modified by the degree of inversion, assuming that this could be varied from the equilibrium value. We have obtained electronic densities of states for the completely normal and completely inverse cation distribution of each compound. FeCr2X4, FeMn2X4, FeCo2O4 and FeNi2O4 are half-metals in the ferrimagnetic state when Fe is in tetrahedral positions. When M is filling the tetrahedral positions, the Cr-containing compounds and FeMn2O4 are half-metallic systems, while the Co and Ni spinels are insulators. The Co and Ni sulfide counterparts are metallic for any inversion degree together with the inverse FeMn2S4. Our calculations suggest that the spin filtering properties of the FeM2X4 (thio)spinels could be modified via the control of the cation distribution through variations in the synthesis conditions.

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Although estimation of turbulent transport parameters using inverse methods is not new, there is little evaluation of the method in the literature. Here, it is shown that extended observation of the broad scale hydrography by Argo provides a path to improved estimates of regional turbulent transport rates. Results from a 20 year ocean state estimate produced with the ECCO v4 non-linear inverse modeling framework provide supporting evidence. Turbulent transport parameter maps are estimated under the constraints of fitting the extensive collection of Argo profiles collected through 2011. The adjusted parameters dramatically reduce misfits to in situ profiles as compared with earlier ECCO solutions. They also yield a clear reduction in the model drift away from observations over multi-century long simulations, both for assimilated variables (temperature and salinity) and independent variables (bio-geochemical tracers). Despite the minimal constraints imposed specifically on the estimated parameters, their geography is physically plausible and exhibits close connections with the upper ocean ocean stratification as observed by Argo. The estimated parameter adjustments furthermore have first order impacts on upper-ocean stratification and mixed layer depths over 20 years. These results identify the constraint of fitting Argo profiles as an effective observational basis for regional turbulent transport rates. Uncertainties and further improvements of the method are discussed.

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Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.

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Knowing the best 1D model of the crustal and upper mantle structure is useful not only for routine hypocenter determination, but also for linearized joint inversions of hypocenters and 3D crustal structure, where a good choice of the initial model can be very important. Here, we tested the combination of a simple GA inversion with the widely used HYPO71 program to find the best three-layer model (upper crust, lower crust, and upper mantle) by minimizing the overall P- and S-arrival residuals, using local and regional earthquakes in two areas of the Brazilian shield. Results from the Tocantins Province (Central Brazil) and the southern border of the Sao Francisco craton (SE Brazil) indicated an average crustal thickness of 38 and 43 km, respectively, consistent with previous estimates from receiver functions and seismic refraction lines. The GA + HYPO71 inversion produced correct Vp/Vs ratios (1.73 and 1.71, respectively), as expected from Wadati diagrams. Tests with synthetic data showed that the method is robust for the crustal thickness, Pn velocity, and Vp/Vs ratio when using events with distance up to about 400 km, despite the small number of events available (7 and 22, respectively). The velocities of the upper and lower crusts, however, are less well constrained. Interestingly, in the Tocantins Province, the GA + HYPO71 inversion showed a secondary solution (local minimum) for the average crustal thickness, besides the global minimum solution, which was caused by the existence of two distinct domains in the Central Brazil with very different crustal thicknesses. (C) 2010 Elsevier Ltd. All rights reserved.

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Layer-by-layer (LBL) films of nickel tetrasulfonated phthalocyanine (NiTsPc) alternated with poly(allylamine hydrochloride) (PAH) have been prepared, whose surface charge has been evaluated using surface potential measurements. From adsorption kinetics results, we obtained the immersion time of similar to 40 s, which was used to assemble layers of NiTsPc. The effect of gold (Au) and aluminum (Al) electrodes on the charge behavior was examined. We found that the surface potential (i.e. surface charge) was inverted each time a layer of PAH was alternated with another of NiTsPc molecules for the two types of electrodes, which was attributed to charge overcompensation between positive charges of PAH molecules, and negative charges from NiTsPc molecules. (C) 2009 Elsevier B.V. All rights reserved.

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New U-Pb zircon and (40)Ar-(39)Ar K-feldspar data are presented for syn-sedimentary volcanogenic rocks from the Neoproterozoic Marica Formation, located in the southern Brazilian shield. Seven (of nine) U-Pb sensitive high-resolution ion microprobe analyses of zircons from pyroclastic cobbles yield an age of 630.2 +/- 3.4 Ma (2 sigma), interpreted as the age of syn-sedimentary volcanism, and thus of the deposition itself. This result indicates that the Marica Formation was deposited during the main collisional phase (640-620 Ma) of the Brasiliano II orogenic system, probably as a forebulge or back-bulge, craton-derived foreland succession. Thus, this unit is possibly correlative of younger portions of the Porongos, Brusque, Passo Feio, Abapa (Itaiacoca) and Lavalleja (Fuente del Puma) metamorphic complexes. Well-defined, step-heating (40)Ar-(39)Ar K-feldspar plateau ages obtained from volcanogenic beds and pyroclastic cobbles of the lower and upper successions of the Marica Formation yielded 507.3 +/- 1.8 Ma and 506.7 +/- 1.4 Ma (2 sigma), respectively. These data are interpreted to reflect total isotopic resetting during deep burial and thermal effects related to magmatic events. Late Middle Cambrian cooling below ca. 200 degrees C, probably related to uplift, is tentatively associated with intraplate effects of the Rio Doce and/or Pampean orogenies (Brasiliano III system). In the southern Brazilian shield, these intraplate stresses are possibly related to the dominantly extensional opening of a rift or a pull-apart basin, where sedimentary rocks of the Camaqua Group (Santa Barbara and Guaritas Formations) accumulated.

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Even though the term corporate inversion has been heard globally for decades, it has only become more prevalent in the United States during the past two years. This case study examines two United States companies that recently had very high profile and public corporate inversion experiences. Complicated tax laws and high tax rales have long eroded the ability of United States companies to remain competitive on a global scale. During the past two years, tax reform has been elevated to the Presidential and Congressional levei. Because these reform efforts have stalled, however, and in the constant search for ways to become more competitive and profitable, United States dorniciled companies have begun to more aggressively explore corporate inversion. This case study of Walgreens Alliance Boots and Mylan N.V., is undertaken because while the reasons to pursue a corporate inversion for both companies were very similar and done during the same time period, the internai process and final outcome were dramatically different. The other dynamic studied is the role both internai and externai politics had on these two cornpanies and how they influenced the decisions made by the executives. Lastly, the Obama Administration continues to threaten so called "corporate America" to remain in the country through regulatory pressure, but this has not stopped companies frorn pursing corporate inversions. Legislatively, attempts at corporate tax reform, another way to encourage Untied States companies to remain, have also failed. I will not try to determine i f a corporate inversion is the right path for a company to take. I am examining how the rise o f the practice o f corporate inversions has been elevated in boardroorns, on Wall Street, in Congress and at the White House during the past two years.

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The spatial distribution of Rotylenchulus reniformis on cotton cultivated in crop rotation with sorghum-peanut-velvetbean was studied using geostatistics. The experimental field, which had been continuously cropped with cotton for 20 years, comprised two 32 x 48 m-grids, each divided in sixty-four 4 x 6 in sampling plots. For all crops, 300 cm(3) soil samples were taken at the center of each plot at crop germination (Pi) and again at harvest (Pf), from which the numbers of nematodes were determined. The results revealed that the spatial distribution of R. reniformis was highly aggregated and with the aid of geostatistical techniques the nematode intensities were mapped and the risk areas accurately identified. Consequently, geostatistics is here considered a useful tool for planning nematode control strategies, particularly in precision agriculture.

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In recent years, the productivity of cotton in Brazil has been progressively decreasing, often the result of the reniform nematode Rotylenchulus reniformis. This species call reduce crop productivity by up to 40%. Nematodes can be controlled by nematicides but, because of expense and toxicity, application of nematicides to large crop areas may be undesirable. In this Work. a methodology using geostatistics for quantifying the risk of nematicide application to small crop areas is proposed. This risk, in economic terms, can be compared to nematicide cost to develop an optimal strategy for Precision Farming, Soil (300 cm(3)) was sampled in a regular network from a R. reniformis-infested area that was a cotton monoculture for 20 years. The number of nematodes in each sample was counted. The nematode number per volume of soil was characterized using geostatistics, and 100 conditional simulations were conducted. Based on the simulations, risk maps were plotted showing the areas where nematicide should be applied in a Precision Farming context. The methodology developed can be applied to farming in countries that ale highly dependent on agriculture, with useful economic implications.