378 resultados para Geostatistics


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En el marc d'un projecte més ampli sobre la comunitat de peixos de la conca lacustre de Banyoles, s'ha estudiat la distribució espacial de les diferents espècies així com l'ús que aquestes fan de l'hàbitat. El poblament piscícola de l'estany de Banyoles és el resultat d'un llarg historial d'introducció d'espècies exòtiques i extinció de les poblacions autòctones locals. S'ha revisat la seva composició actual detectant un total de 18 espècies (4 autòctones i 14 introduïdes) de les quals només 13 presenten una població estable. L'estudi de l'hàbitat s'ha centrat a l'Estany, l'element principal del sistema lacustre, analitzant per separat la zona litoral i la zona limnètica. En el primer cas s'han realitzat les captures d'individus mitjançant pesca elèctrica des d'una embarcació adaptada per aquesta pràctica. La totalitat del litoral ha estat dividida en trams de característiques homogènies on s'han obtingut les captures per unitat d'esforç per cada espècie. El mostreig s'ha desenvolupat entre l'estiu de 1997 i la primavera del 2000 realitzant un total de 10 campanyes de pesca. Les espècies més abundants al litoral són la perca americana (Micropterus salmoides) i el peix sol (Lepomis gibbosus), essent també presents la perca (Perca fluviatilis), carpa (Cyprinus carpio) i el gardí (Scardinius erythrophthalmus). S'han capturat altres espècies com ara anguila (Anguilla anguilla), bagra (Squalius cephalus), sandra (Sander lucioperca), carpí (Carassius auratus) i madrilleta vera (Rutilus rutilus), però són molt menys abundants en nombre. S'ha examinat, per cadascuna de les espècies, si existeix selecció de l'hàbitat i en cas afirmatiu, quin és el preferent en base a la classificació del litoral en sis tipus de vegetació predominant. Les espècies més abundants, perca americana i peix sol, ocupen tots els hàbitats disponibles però amb una densitat diferent. La perca mostra també una clara selecció de l'hàbitat a favor de les zones molt estructurades amb abundant presència de jonca litoral. Carpa i gardí seleccionen els ambients més fondos amb major presència de matèria orgànica d'origen vegetal procedent del bogar. En general els individus ocupen les zones amb una densitat de vegetació intermèdia, majoritàriament zones de jonca a l'estiu i zones amb mansega a l'hivern, on troben refugi i els recursos tròfics necessaris. La perca americana, a més, presenta una elevada fidelitat a un mateix punt del litoral al llarg de la seva vida. La zona limnètica ha estat prospectada mensualment mitjançant ecosondació, realitzant transectes perpendiculars a l'eix principal de l'Estany, cobrint la seva totalitat. La composició d'espècies s'ha obtingut a partir de les captures fetes amb xarxes (tresmalls) amb periodicitat estacional. L'anàlisi geoestadística de la densitat de peixos ha permès descriure l'estructura espacial d'aquesta a partir dels variogrames, així com la seva variabilitat tant espacial com temporal, i obtenir els mapes de densitat. A l'hivern, la densitat de peixos a la zona limnètica assoleix els seus valors mínims i els individus es troben formant agregats dispersos, pels diferents estrats de fondària. A partir de la primavera la densitat augmenta, pel reclutament i la major freqüència d'individus que abandonen el litoral; la densitat esdevé més homogènia a les primer capes de fondària. A l'estiu la densitat és màxima i l'estrat més homogeni coincideix amb la posició de la termoclina. Aquest estructura varia en disminuir la temperatura i barrejar-se la columna d'aigua, tornant a la situació hivernal. La perca i la madrilleta vera són les espècies predominants en aquest ambient, juntament amb la carpa. La seva distribució no és homogènia i respon a les característiques limnològiques de les diferents cubetes de l'Estany. Una particularitat d'aquest, relacionada amb el seu origen càrstic, es la formació d'una ploma hidrotermal que afecta la distribució dels peixos, probablement en augmentar la terbolesa. S'ha integrat l'ús de l'hàbitat de les espècies que ocupen tant la zona limnètica com la litoral a partir del seguiment d'individus, concretament de perca i bagra. S'ha utilitzat un sistema automàtic de posicionament que estima la localització dels individus marcats amb transmissor de telemetria acústica. L'anàlisi dels desplaçaments mostra un rang superior per la bagra en comparació amb la perca. Ambdues espècies mostren una orientació en els seus desplaçaments. La perca ocupa el litoral a la nit i es desplaça a la zona limnètica de dia, amb un ritme d'activitat marcat per dos màxims coincidint amb la sortida i posta de sol; en canvi la bagra mostra una major activitat nocturna amb zones de repòs properes al litoral. S'ha estimat igualment els dominis vital de cada individu marcat.

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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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Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

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The resolution of remotely sensed data is becoming increasingly fine, and there are now many sources of data with a pixel size of 1 m x 1 m. This produces huge amounts of data that have to be stored, processed and transmitted. For environmental applications this resolution possibly provides far more data than are needed: data overload. This poses the question: how much is too much? We have explored two resolutions of data-20 in pixel SPOT data and I in pixel Computerized Airborne Multispectral Imaging System (CAMIS) data from Fort A. P. Hill (Virginia, USA), using the variogram of geostatistics. For both we used the normalized difference vegetation index (NDVI). Three scales of spatial variation were identified in both the SPOT and 1 in data: there was some overlap at the intermediate spatial scales of about 150 in and of 500 m-600 in. We subsampled the I in data and scales of variation of about 30 in and of 300 in were identified consistently until the separation between pixel centroids was 15 in (or 1 in 225pixels). At this stage, spatial scales of about 100m and 600m were described, which suggested that only now was there a real difference in the amount of spatial information available from an environmental perspective. These latter were similar spatial scales to those identified from the SPOT image. We have also analysed I in CAMIS data from Fort Story (Virginia, USA) for comparison and the outcome is similar.:From these analyses it seems that a pixel size of 20m is adequate for many environmental applications, and that if more detail is required the higher resolution data could be sub-sampled to a 10m separation between pixel centroids without any serious loss of information. This reduces significantly the amount of data that needs to be stored, transmitted and analysed and has important implications for data compression.

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The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

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Mediterranean ecosystems rival tropical ecosystems in terms of plant biodiversity. The Mediterranean Basin (MB) itself hosts 25 000 plant species, half of which are endemic. This rich biodiversity and the complex biogeographical and political issues make conservation a difficult task in the region. Species, habitat, ecosystem and landscape approaches have been used to identify conservation targets at various scales: ie, European, national, regional and local. Conservation decisions require adequate information at the species, community and habitat level. Nevertheless and despite recent improvements/efforts, this information is still incomplete, fragmented and varies from one country to another. This paper reviews the biogeographic data, the problems arising from current conservation efforts and methods for the conservation assessment and prioritization using GIS. GIS has an important role to play for managing spatial and attribute information on the ecosystems of the MB and to facilitate interactions with existing databases. Where limited information is available it can be used for prediction when directly or indirectly linked to externally built models. As well as being a predictive tool today GIS incorporate spatial techniques which can improve the level of information such as fuzzy logic, geostatistics, or provide insight about landscape changes such as 3D visualization. Where there are limited resources it can assist with identifying sites of conservation priority or the resolution of environmental conflicts (scenario building). Although not a panacea, GIS is an invaluable tool for improving the understanding of Mediterranean ecosystems and their dynamics and for practical management in a region that is under increasing pressure from human impact.

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Mediterranean ecosystems rival tropical ecosystems in terms of plant biodiversity. The Mediterranean Basin (MB) itself hosts 25 000 plant species, half of which are endemic. This rich biodiversity and the complex biogeographical and political issues make conservation a difficult task in the region. Species, habitat, ecosystem and landscape approaches have been used to identify conservation targets at various scales: ie, European, national, regional and local. Conservation decisions require adequate information at the species, community and habitat level. Nevertheless and despite recent improvements/efforts, this information is still incomplete, fragmented and varies from one country to another. This paper reviews the biogeographic data, the problems arising from current conservation efforts and methods for the conservation assessment and prioritization using GIS. GIS has an important role to play for managing spatial and attribute information on the ecosystems of the MB and to facilitate interactions with existing databases. Where limited information is available it can be used for prediction when directly or indirectly linked to externally built models. As well as being a predictive tool today GIS incorporate spatial techniques which can improve the level of information such as fuzzy logic, geostatistics, or provide insight about landscape changes such as 3D visualization. Where there are limited resources it can assist with identifying sites of conservation priority or the resolution of environmental conflicts (scenario building). Although not a panacea, GIS is an invaluable tool for improving the understanding of Mediterranean ecosystems and their dynamics and for practical management in a region that is under increasing pressure from human impact.

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This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

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The shuttle radar topography mission (SRTM), was flow on the space shuttle Endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60 degrees north latitude and 56 degrees south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc-second (similar to 30m) for areas within the USA and at 3 arc-second (similar to 90m) resolution for the rest of the world. A resolution of 90m can be considered suitable for the small or medium-scale analysis, but it is too coarse for more detailed purposes. One alternative is to interpolate the SRTM data at a finer resolution; it will not increase the level of detail of the original digital elevation model (DEM), but it will lead to a surface where there is the coherence of angular properties (i.e. slope, aspect) between neighbouring pixels, which is an important characteristic when dealing with terrain analysis. This work intents to show how the proper adjustment of variogram and kriging parameters, namely the nugget effect and the maximum distance within which values are used in interpolation, can be set to achieve quality results on resampling SRTM data from 3"" to 1"". We present for a test area in western USA, which includes different adjustment schemes (changes in nugget effect value and in the interpolation radius) and comparisons with the original 1"" model of the area, with the national elevation dataset (NED) DEMs, and with other interpolation methods (splines and inverse distance weighted (IDW)). The basic concepts for using kriging to resample terrain data are: (i) working only with the immediate neighbourhood of the predicted point, due to the high spatial correlation of the topographic surface and omnidirectional behaviour of variogram in short distances; (ii) adding a very small random variation to the coordinates of the points prior to interpolation, to avoid punctual artifacts generated by predicted points with the same location than original data points and; (iii) using a small value of nugget effect, to avoid smoothing that can obliterate terrain features. Drainages derived from the surfaces interpolated by kriging and by splines have a good agreement with streams derived from the 1"" NED, with correct identification of watersheds, even though a few differences occur in the positions of some rivers in flat areas. Although the 1"" surfaces resampled by kriging and splines are very similar, we consider the results produced by kriging as superior, since the spline-interpolated surface still presented some noise and linear artifacts, which were removed by kriging.

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The application of thermal methods, to increase the recovery of heavy oil in mature fields through drainage with multilateral and horizontal wells, has been thoroughly studied, theorically, experimentally, testing new tools and methods. The continuous injection of steam, through a steam injector well and a horizontal producer well in order to improve horizontal sweep of the fluid reservoir, it is an efficient method. Starting from an heterogeneous model, geologically characterized, modeling geostatistics, set history and identification of the best path of permeability, with seismic 3D, has been dubbed a studying model. It was studied horizontal wells in various directions in relation to the steam and the channel of higher permeability, in eight different depths. Into in the same area were studied, the sensitivity of the trajectories of horizontal wells, according to the depth of navigation. With the purpose of obtaining the highest output of oil to a particular flow, quality, temperature and time for the injection of steam. The wells studied showed a significant improvement in the cumulative oil recovery in one of the paths by promoting an alternative to application in mature fields or under development fields with heavy oil

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O objetivo deste trabalho foi avaliar cenários de níveis freáticos extremos, em bacia hidrográfica, por meio de métodos de análise espacial de dados geográficos. Avaliou-se a dinâmica espaço‑temporal dos recursos hídricos subterrâneos em área de afloramento do Sistema Aquífero Guarani. As alturas do lençol freático foram estimadas por meio do monitoramento de níveis em 23 piezômetros e da modelagem das séries temporais disponíveis de abril de 2004 a abril de 2011. Para a geração de cenários espaciais, foram utilizadas técnicas geoestatísticas que incorporaram informações auxiliares relativas a padrões geomorfológicos da bacia, por meio de modelo digital de terreno. Esse procedimento melhorou as estimativas, em razão da alta correlação entre altura do lençol e elevação, e agregou sentido físico às predições. Os cenários apresentaram diferenças quanto aos níveis considerados extremos - muito profundos ou muito superficiais - e podem subsidiar o planejamento, o uso eficiente da água e a gestão sustentável dos recursos hídricos na bacia.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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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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The behavior of the chemical attributes is directly influenced by superficial flow and water movement inside the soil. This work aimed to study the space dependency of chemical attributes in an area with sugarcane plantation in Pereira Barreto, SP. An area of 530.67 hectares was mapped using an equipment of Global Positioning System and obtaining a Digital Elevation Model. A set of 134 soil samples were collected every seven hectares in the depths of 0-0.25 m and 0.80-1.00 m. The pH, organic matter (OM), Ca, Mg, K, BS, CEC and base saturation (BS) were analyzed. All the chemical attributes presented similar behavior in the superficial and subsuperficial layer of the soil, which provided better visualization and definition of the homogeneous tillage zones.

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The variation of soil textural characteristics is a function of the relief and parent materials. The objective of this work was to study soil texture spatial variability from different parent material in Pereira Barreto, SP. An area of 530.67 hectares was mapped through the use of Global Positioning System receivers and obtaining of Digital Elevation Models. A set of 201 soil samples was collected from every seven hectares, at three depths: 0 - 0.25 m; 0.25 - 0.50 m; and 0.80 - 1.00 m. The amounts of sand, silt and clay were obtained by the pipette method and analyzed by both descriptive statistics and geostatistics. Soil textures varied as a function of parent materials and topography.