920 resultados para local-scale variation
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Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.
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We contribute a quantitative and systematic model to capture etch non-uniformity in deep reactive ion etch of microelectromechanical systems (MEMS) devices. Deep reactive ion etch is commonly used in MEMS fabrication where high-aspect ratio features are to be produced in silicon. It is typical for many supposedly identical devices, perhaps of diameter 10 mm, to be etched simultaneously into one silicon wafer of diameter 150 mm. Etch non-uniformity depends on uneven distributions of ion and neutral species at the wafer level, and on local consumption of those species at the device, or die, level. An ion–neutral synergism model is constructed from data obtained from etching several layouts of differing pattern opening densities. Such a model is used to predict wafer-level variation with an r.m.s. error below 3%. This model is combined with a die-level model, which we have reported previously, on a MEMS layout. The two-level model is shown to enable prediction of both within-die and wafer-scale etch rate variation for arbitrary wafer loadings.
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Purpose: To examine the ‘interrater reliability’ of the Alberta Infant Motor Scale (AIMS) in term and preterm born infants between 10 to 16 months age from Talca province, Maule Region - Chile. Subjects: 115 infants between 10 to 16 months age were incorporated to the study; 95 term born infants were attended in the local Health Centre in Talca City, and 20 preterm infants belonged to the Premature Infants Follow-Up Programme of Talca Regional Hospital. Methods: The motor behaviour of each infant was recorded and later it was assessed by two trained assessors using AIMS. It was obtained the total AIMS’ score and also from prone, supine, seated, and stand subscales. For ‘interrater reliability’ analysis it was used the Intraclass Coefficient of Correlation (ICC), the Standard Error of Measurement (SEM) and 95% limits of agreement. Results: The obtained ICC for the total scores AIMS were major than 0.94 (p<0.0002) for term and preterm born infants. The SEM of total scores was less than 3.1 points, higher than what was found in other similar studies. The 95% limits of agreement were +5.3 to -4.1 points and +7.7 to – 3.9 points in term and preterm born, respectively, revealing ‘interrater agreement’. Conclusion: The AIMS showed adequate ‘interrater reliable’ levels when was applied in Chilean term and preterm born from 10 to 16 month’s age.
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The first part of this work presents an accurate analysis of the most relevant 3D registration techniques, including initial pose estimation, pairwise registration and multiview registration strategies. A new classification has been proposed, based on both the applications and the approach of the methods that have been discussed. The main contribution of this thesis is the proposal of a new 3D multiview registration strategy. The proposed approach detects revisited regions obtaining cycles of views that are used to reduce the inaccuracies that may exist in the final model due to error propagation. The method takes advantage of both global and local information of the registration process, using graph theory techniques in order correlate multiple views and minimize the propagated error by registering the views in an optimal way. The proposed method has been tested using both synthetic and real data, in order to show and study its behavior and demonstrate its reliability.
Resumo:
We tested the hypothesis that cryptically colored eggs would suffer less predation than conspicuous eggs in the ground-nesting red-legged partridge, Alectoris rufa. We used A. rufa as a model species because it has a wide range of natural egg colors, the eggs are widely available from breeding farms, and nests are easily mimicked because they are scrapes containing no vegetation. The study was conducted in the spring of 2001 in forest and fallow fields of central Spain in Castilla La Mancha, Ciudad Real. We used 384 clutches of natural eggs that were white, white spotted, brown, or brown spotted. Within clutches, eggs were consistent in color and size; among clutches, color differences were distributed across habitats. Clutches were checked once after 2 wk of exposure. Cryptic coloration had a survival advantage that was dependent on the local suite of predators. Rodent predation was nonselective with respect to clutch color; however, avian predation was significantly higher for conspicuous clutches. In addition, there was an interaction of landscape and egg color for avian predation. In forest landscapes, the clutches with highest survival were brown spotted, whereas in fallow landscapes, brown and brown spotted clutches had higher survival than white and white potted clutches. Thus, both the predator suite and the landscape had significant effects on the value of cryptic egg coloration. Our study is relevant for conservationists and managers in charge of restocking programs in hunting areas. The release of other partridge species or their hybrids could result in hybridization with wild partridges, potentially leading to nonoptimal clutch pigmentation and reduced survival of the native species. We therefore recommend that local authorities, managers, and conservationists be cautious with the use of alien species and hybrids and release only autochthonous species of partridges within their natural ranges.
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There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species–area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species–area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km × 10 km) and regional (290 km × 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.
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Bachman’s Sparrow (Peucaea aestivalis), an endemic North American passerine, requires frequent (≤ 3 yr) prescribed fires to maintain preferred habitat conditions. Prescribed fires that coincide with the sparrow’s nesting season are increasingly used to manage sparrow habitat, but concerns exist regarding the effects that nesting-season fires may pose to this understory-dwelling species. Previous studies suggested that threats posed by fires might be lessened by reducing the extent of prescribed fires, thereby providing unburned areas close to the areas where fires eliminate ground-cover vegetation. To assess this hypothesis, we monitored color-marked male Bachman’s Sparrows on 2 sites where the extent of nesting-season fires differed 5-fold (> 70 ha vs. < 15 ha). Monthly survival for males did not differ between the large- and small-extent treatments, and survival rates exceeded 90% for all months except one during the second year of our study when fires were applied later in the season. Male densities also did not differ between treatments, but treatment-by-year interactions pointed to effects relating to the specific time that fires were applied. The distances separating observations of marked males before and after burns were smaller on small-extent treatments in the first year of study but larger on the small-extent treatments in the second year of study. Burn extents also had no consistent effect on postburn reproductive status. The largest extent we examined could have been too small to affect sparrow populations, but responses may also reflect sustainable metapopulation dynamics in a setting where a large sparrow population is maintained at a regional scale (> 100,000 ha) using frequent prescribed fire (≤ 2-yr return intervals). Additional research is needed regarding the effects that nesting-season fires may have on small, isolated populations as well as sites where much larger burn extents (> 100 ha) or longer burn intervals (> 2 yr) are used.
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The Short-eared Owl (Asio flammeus) is an open-country species breeding in the northern United States and Canada, and has likely experienced a long-term, range-wide, and substantial decline. However, the cause and magnitude of the decline is not well understood. We set forth to address the first two of six previously proposed conservation priorities to be addressed for this species: (1) better define habitat use and (2) improve population monitoring. We recruited 131 volunteers to survey over 6.2 million ha within the state of Idaho for Short-eared Owls during the 2015 breeding season. We surveyed 75 transects, 71 of which were surveyed twice, and detected Short-eared Owls on 27 transects. We performed multiscale occupancy modeling to identify habitat associations, and performed multiscale abundance modeling to generate a state-wide population estimate. Our results suggest that within the state of Idaho, Short-eared Owls are more often found in areas with marshland or riparian habitat or areas with greater amounts of sagebrush habitat at the 1750 ha transect scale. At the 50 ha point scale, Short-eared Owls tend to associate positively with fallow and bare dirt agricultural land and negatively with grassland. Cropland was not chosen at the broader transect scale suggesting that Short-eared Owls may prefer more heterogeneous landscapes. On the surface our results may seem contradictory to the presumed land use by a “grassland” species; however, the grasslands of the Intermountain West, consisting largely of invasive cheatgrass (Bromus tectorum), lack the complex structure shown to be preferred by these owls. We suggest the local adaptation to agriculture represents the next best habitat to their historical native habitat preferences. Regardless, we have confirmed regional differences that should be considered in conservation planning for this species. Last, our results demonstrate the feasibility, efficiency, and effectiveness of utilizing public participation in scientific research to achieve a robust sampling methodology across the broad geography of the Intermountain West.
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Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data
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The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales. In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect. The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota. (c) 2006 Elsevier Ltd. All rights reserved.
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The Representative Soil Sampling Scheme (RSSS) has monitored the soil of agricultural land in England and Wales since 1969. Here we describe the first spatial analysis of the data from these surveys using geostatistics. Four years of data (1971, 1981, 1991 and 2001) were chosen to examine the nutrient (available K, Mg and P) and pH status of the soil. At each farm, four fields were sampled; however, for the earlier years, coordinates were available for the farm only and not for each field. The averaged data for each farm were used for spatial analysis and the variograms showed spatial structure even with the smaller sample size. These variograms provide a reasonable summary of the larger scale of variation identified from the data of the more intensively sampled National Soil Inventory. Maps of kriged predictions of K generally show larger values in the central and southeastern areas (above 200 mg L-1) and an increase in values in the west over time, whereas Mg is fairly stable over time. The kriged predictions of P show a decline over time, particularly in the east, and those of pH show an increase in the east over time. Disjunctive kriging was used to examine temporal changes in available P using probabilities less than given thresholds of this element. The RSSS was not designed for spatial analysis, but the results show that the data from these surveys are suitable for this purpose. The results of the spatial analysis, together with those of the statistical analyses, provide a comprehensive view of the RSSS database as a basis for monitoring the soil. These data should be taken into account when future national soil monitoring schemes are designed.
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ATSR-2 active fire data from 1996 to 2000, TRMM VIRS fire counts from 1998 to 2000 and burn scars derived from SPOT VEGETATION ( the Global Burnt Area 2000 product) were mapped for Peru and Bolivia to analyse the spatial distribution of burning and its intra- and inter-annual variability. The fire season in the region mainly occurs between May and October; though some variation was found between the six broad habitat types analysed: desert, grassland, savanna, dry forest, moist forest and yungas (the forested valleys on the eastern slope of the Andes). Increased levels of burning were generally recorded in ATSR-2 and TRMM VIRS fire data in response to the 1997/1998 El Nino, but in some areas the El Nino effect was masked by the more marked influences of socio-economic change on land use and land cover. There were differences between the three global datasets: ATSR-2 under-recorded fires in ecosystems with low net primary productivities. This was because fires are set during the day in this region and, when fuel loads are low, burn out before the ATSR-2 overpass in the region which is between 02.45 h and 03.30 h. TRMM VIRS was able to detect these fires because its overpasses cover the entire diurnal range on a monthly basis. The GBA2000 product has significant errors of commission (particularly areas of shadow in the well-dissected eastern Andes) and omission (in the agricultural zone around Santa Cruz, Bolivia and in north-west Peru). Particular attention was paid to biomass burning in high-altitude grasslands, where fire is an important pastoral management technique. Fires and burn scars from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for a range of years between 1987 and 2000 were mapped for areas around Parque Nacional Rio Abiseo (Peru) and Parque Nacional Carrasco (Bolivia). Burn scars mapped in the grasslands of these two areas indicate far more burning had taken place than either the fires or the burn scars derived from global datasets. Mean scar sizes are smaller and have a smaller range in size between years the in the study area in Peru (6.6-7.1 ha) than Bolivia (16.9-162.5 ha). Trends in biomass burning in the two highland areas can be explained in terms of the changing socio-economic environments and impacts of conservation. The mismatch between the spatial scale of biomass burning in the high-altitude grasslands and the sensors used to derive global fire products means that an entire component of the fire regime in the region studied is omitted, despite its importance in the farming systems on the Andes.
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Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.
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A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.
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Experimental acoustic measurements on sandstone rocks at both sonic and ultrasonic frequencies show that fluid saturation can cause a noticeable change in both the dynamic bulk and shear elastic moduli of sandstones. We observed that the change in dynamic shear modulus upon fluid saturation is highly dependent on the type of saturant, its viscosity, rock microstructure, and applied pressures. Frequency dispersion has some influence on dynamic elastic moduli too, but its effect is limited to the ultrasonic frequency ranges and above. We propose that viscous coupling, reduction in free surface energy, and, to a limited extent, frequency dispersion due to both local and global flow are the main mechanisms responsible for the change in dynamic shear elastic modulus upon fluid saturation and substitution, and we quantify influences.