996 resultados para Spatial datasets


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Aims. Although the time of the Maunder minimum (1645–1715) is widely known as a period of extremely low solar activity, it is still being debated whether solar activity during that period might have been moderate or even higher than the current solar cycle (number 24). We have revisited all existing evidence and datasets, both direct and indirect, to assess the level of solar activity during the Maunder minimum. Methods. We discuss the East Asian naked-eye sunspot observations, the telescopic solar observations, the fraction of sunspot active days, the latitudinal extent of sunspot positions, auroral sightings at high latitudes, cosmogenic radionuclide data as well as solar eclipse observations for that period. We also consider peculiar features of the Sun (very strong hemispheric asymmetry of the sunspot location, unusual differential rotation and the lack of the K-corona) that imply a special mode of solar activity during the Maunder minimum. Results. The level of solar activity during the Maunder minimum is reassessed on the basis of all available datasets. Conclusions. We conclude that solar activity was indeed at an exceptionally low level during the Maunder minimum. Although the exact level is still unclear, it was definitely lower than during the Dalton minimum of around 1800 and significantly below that of the current solar cycle #24. Claims of a moderate-to-high level of solar activity during the Maunder minimum are rejected with a high confidence level.

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Housebuilding firms vary across the world in size and in the scope of their activities. This variety may seem surprising in an industry with open technologies and ease of entry. While market and technological factors may go some way to explain such differences, much of the causes of variation lie in dissimilarities in regulatory and institutional frameworks. These themes are explored through a comparative analysis of the structure of the residential development industry in Australia, the UK and the USA and in analysis of firm size hierarchies. The firm concentration ratio is much higher in the UK than the other two countries and the reasons may lie in the geography of the country but also in the peculiarities of its planning system.

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The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

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We present the first multi-event study of the spatial and temporal structuring of the aurora to provide statistical evidence of the near-Earth plasma instability which causes the substorm onset arc. Using data from ground-based auroral imagers, we study repeatable signatures of along-arc auroral beads, which are thought to represent the ionospheric projection of magnetospheric instability in the near-Earth plasma sheet. We show that the growth and spatial scales of these wave-like fluctuations are similar across multiple events, indicating that each sudden auroral brightening has a common explanation. We find statistically that growth rates for auroral beads peak at low wavenumber with the most unstable spatial scales mapping to an azimuthal wavelength λ≈1700 − 2500 km in the equatorial magnetosphere at around 9-12 RE. We compare growth rates and spatial scales with a range of theoretical predictions of magnetotail instabilities, including the cross-field current instability and the shear-flow ballooning instability. We conclude that, although the cross-field current instability can generate similar magnitude of growth rates, the range of unstable wavenumbers indicates that the shear-flow ballooning instability is the most likely explanation for our observations.

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In many lower-income countries, the establishment of marine protected areas (MPAs) involves significant opportunity costs for artisanal fishers, reflected in changes in how they allocate their labor in response to the MPA. The resource economics literature rarely addresses such labor allocation decisions of artisanal fishers and how, in turn, these contribute to the impact of MPAs on fish stocks, yield, and income. This paper develops a spatial bio-economic model of a fishery adjacent to a village of people who allocate their labor between fishing and on-shore wage opportunities to establish a spatial Nash equilibrium at a steady state fish stock in response to various locations for no-take zone MPAs and managed access MPAs. Villagers’ fishing location decisions are based on distance costs, fishing returns, and wages. Here, the MPA location determines its impact on fish stocks, fish yield, and villager income due to distance costs, congestion, and fish dispersal. Incorporating wage labor opportunities into the framework allows examination of the MPA’s impact on rural incomes, with results determining that win-wins between yield and stocks occur in very different MPA locations than do win-wins between income and stocks. Similarly, villagers in a high-wage setting face a lower burden from MPAs than do those in low-wage settings. Motivated by issues of central importance in Tanzania and Costa Rica, we impose various policies on this fishery – location specific no-take zones, increasing on-shore wages, and restricting MPA access to a subset of villagers – to analyze the impact of an MPA on fish stocks and rural incomes in such settings.

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The seasonal sea level variations observed from tide gauges over 1900-2013 and gridded satellite altimeter product AVISO over 1993-2013 in the northwest Pacific have been explored. The seasonal cycle is able to explain 60-90% of monthly sea level variance in the marginal seas, while it explains less than 20% of variance in the eddy-rich regions. The maximum annual and semi-annual sea level cycles (30cm and 6cm) are observed in the north of the East China Sea and the west of the South China Sea respectively. AVISO was found to underestimate the annual amplitude by 25% compared to tide gauge estimates along the coasts of China and Russia. The forcing for the seasonal sea level cycle was identified. The atmospheric pressure and the steric height produce 8-12cm of the annual cycle in the middle continental shelf and in the Kuroshio Current regions separately. The removal of the two attributors from total sea level permits to identify the sea level residuals that still show significant seasonality in the marginal seas. Both nearby wind stress and surface currents can explain well the long-term variability of the seasonal sea level cycle in the marginal seas and the tropics because of their influence on the sea level residuals. Interestingly, the surface currents are a better descriptor in the areas where the ocean currents are known to be strong. Here, they explain 50-90% of inter-annual variability due to the strong links between the steric height and the large-scale ocean currents.

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Weeds tend to aggregate in patches within fields and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at different scales, the strength of the relationships between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We have developed a general method that uses novel within-field nested sampling and residual maximum likelihood (REML) estimation to explore scale-dependent relationships between weeds and soil properties. We have validated the method using a case study of Alopecurus myosuroides in winter wheat. Using REML, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales we optimized the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

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This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.

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This paper presents a quantitative evaluation of a tracking system on PETS 2015 Challenge datasets using well-established performance measures. Using the existing tools, the tracking system implements an end-to-end pipeline that include object detection, tracking and post- processing stages. The evaluation results are presented on the provided sequences of both ARENA and P5 datasets of PETS 2015 Challenge. The results show an encouraging performance of the tracker in terms of accuracy but a greater tendency of being prone to cardinality error and ID changes on both datasets. Moreover, the analysis show a better performance of the tracker on visible imagery than on thermal imagery.

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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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Datasets containing information to locate and identify water bodies have been generated from data locating static-water-bodies with resolution of about 300 m (1/360 deg) recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The LC CCI water-bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR on Envisat between 2005 and 2010. The new derived datasets provide coherently: distance to land, distance to water, water-body identifiers and lake-centre locations. The water-body identifier dataset locates the water bodies assigning the identifiers of the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). During the generation and validation of the datasets some limitations of the GLWD database and of the LC CCI water-bodies mask have been found. Some examples of the inaccuracies/limitations are presented and discussed. Temporal change in water-body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.

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Three land-fast ice stations (one of them was the Finnish research ice breaker Aranda) and the German research aircraft Falcon were applied to measure the turbulent and radiation fluxes over the ice edge zone in the northern Baltic Sea during the Baltic Air-Sea-Ice Study (BASIS) field experiment from 16 February to 6 March 1998. The temporal and spatial variability of the surface fluxes is discussed. Synoptic weather systems passed the experimental area in a rapid sequence and dominated the conditions (wind speed, airsurface temperature difference, cloud field) for the variability of the turbulent and radiation fluxes. At the ice stations, the largest upward sensible heat fluxes of about 100 Wm�2 were measured during the passage of a cold front when the air cooled faster (�5 K per hour) than the surface. The largest downward flux of about �200 Wm�2 occurred during warm air advection when the air temperature reached +10�C but the surface temperature remained at 0�C. Spatial variability of fluxes was observed from the small scale (scale of ice floes and open water spots) to the mesoscale (width of the ice edge zone). The degree of spatial variability depends on the synoptic situation: during melting conditions downward heat fluxes were the same over ice and open water, whereas during strong cold-air advection upward heat fluxes differed by more than 100 Wm�2. A remarkable amount of grey ice with intermediate surface temperature was observed. The ice in the Baltic Sea cannot be described by one ice type only.

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The field campaign LOFZY 2005 (LOFoten ZYklonen, engl.: Cyclones) was carried out in the frame of Collaborative Research Centre 512, which deals with low-pressure systems (cyclones) and the climate system of the North Atlantic. Cyclones are of special interest due to their influence on the interaction between atmosphere and ocean. Cyclone activity in the northern part of the Atlantic Ocean is notably high and is of particular importance for the entire Atlantic Ocean. An area of maximum precipitation exists in front of the Norwegian Lofoten islands. One aim of the LOFZY field campaign was to clarify the role cyclones play in the interaction of ocean and atmosphere. In order to obtain a comprehensive dataset of cyclone activity and ocean-atmosphere interaction a field experiment was carried out in the Lofoten region during March and April 2005. Employed platforms were the Irish research vessel RV Celtic Explorer which conducted a meteorological (radiosondes, standard parameters, observations) and an oceanographic (CTD) program. The German research aircraft Falcon accomplished eight flight missions (between 4-21 March) to observe synoptic conditions with high spatial and temporal resolution. In addition 23 autonomous marine buoys were deployed in advance of the campaign in the observed area to measure drift, air-temperature and -pressure and water-temperature. In addition to the published datasets several other measurements were performed during the experiment. Corresonding datasets will be published in the near future and are available on request. Details about all used platforms and sensors and all performed measurements are listed in the fieldreport. The following datasets are available on request: ground data at RV Celtic Explorer