983 resultados para spatial distance


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Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

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The air dry-bulb temperature (t db),as well as the black globe humidity index (BGHI), exert great influence on the development of broiler chickens during their heating phase. Therefore, the aim of this study was to analyze the structure and the magnitude of the t db and BGHI spatial variability, using geostatistics tools such as semivariogram analysis and also producing kriging maps. The experiment was conducted in the west mesoregion of the states of Minas Gerais in 2010, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the firsts 14 days of the birds' life. The data were registered at intervals of five minutes in the period from 8 a.m. to 10 a.m. The variables were evaluated by variograms fitted by residual maximum likelihood (REML) testing the Spherical and Exponential models. Kriging maps were generated based on the best model used to fit the variogram. It was possible to characterize the variability of the t db and BGHI, which allowed observing the spatial dependence by using geostatistics techniques. In addition, the use of geostatistics and distribution maps made possible to identify problems in the heating system in regions inside the broiler house that may harm the development of chicks.

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This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

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Since the advent of mechanized farming and intensive use of agricultural machinery and implements on the properties, the soil began to receive greater load of machinery traffic, which can cause increased soil compaction. The aim of this study was to evaluate the spatial variability of soil mechanical resistance to penetration (RP) in the layers of 0.00-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.40m, using geostatistics in an area cultivated with mango in Haplic Vertisol of the northeastern semi-arid, with mobile unit equipped with electronic penetrometer. The RP data was collected in 56 points from an area of 3 ha, and random soil samples were collected to determine the soil moisture and texture. For RP data analysis we used descriptive statistics and geostatistics. The soil mechanical resistance to penetration presented increased variability, with adjustment of the spherical and exponential semivariograms in the layers. We found that 42% of the area in the layer of 0.10-0.20m showed RP values above 2.70 MPa. Maximum values of RP were found in the layer of 0.19-0.27m, predominantly in 56% of the area.

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The implementation of local geodetic networks for georeferencing of rural properties has become a requirement after publication of the Georeferencing Technical Standard by INCRA. According to this standard, the maximum distance of baselines to GNSS L1 receivers is of 20 km. Besides the length of the baseline, the geometry and the number of geodetic control stations are other factors to be considered in the implementation of geodetic networks. Thus, this research aimed to examine the influence of baseline lengths higher than the regulated limit of 20 km, the geometry and the number of control stations on quality of local geodetic networks for georeferencing, and also to demonstrate the importance of using specific tests to evaluate the solution of ambiguities and on the quality of the adjustment. The results indicated that the increasing number of control stations has improved the quality of the network, the geometry has not influenced on the quality and the baseline length has influenced on the quality; however, lengths higher than 20 km has not interrupted the implementation, with GPS L1 receiver, of the local geodetic network for the purpose of georeferencing. Also, the use of different statistical tests, both for the evaluation of the resolution of ambiguities and for the adjustment, have enabled greater clearness in analyzing the results, which allow that unsuitable observations may be eliminated.

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The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.

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In the current study, we performed a soybean production spatial distribution analysis in Paraná State. Seven crop-year data, from 2003-04 to 2009-10, obtained from the Paraná Department of Agriculture and Supply (SEAB) were used to develop a Boxmap for each crop-year, show soybean production throughout this time interval. Moran's index was used to measure spatial autocorrelation among municipalities at an aggregate level, while LISA index local correlation. For each index, different contiguity matrix and order were used and there was a significance level study. As a result, we have showed spatial relationship among cities regarding the production, which allowed the indication of high and low production clusters. Finally, identifying main soybean-producing cities, what may provide supply chain members with information to strengthen the crop production in Paraná.

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Precision agriculture based on the physical and chemical properties of soil requires dense sampling to determine the spatial variability of these properties. This dense sampling is often expensive and time-consuming. One technique used to reduce sample numbers involves defining management zones based on information collected in the field. Some researchers have demonstrated the importance of soil electrical variables in defining management zones. The objective of this study was to evaluate the relationship between the spatial variability of the apparent electrical conductivity and the soil properties in the coffee production of mountain regions. Spatial variability maps were generated using a geostatistical method. Based on the spatial variability results, a correlation analysis, using bivariate Moran's index, was done to evaluate the relationship between the apparent electrical conductivity and soil properties. The maps of potassium (K) and remaining phosphorus (P-rem) were the closest to the spatial variability pattern of the apparent electrical conductivity.

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Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

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ABSTRACT Precision agriculture adoption in Brazilian apple orchards is still incipient. This study aimed at evaluating the spatial variability of certain soil properties as soil density, soil penetration resistance, electrical conductivity, yield, and fruit quality in an apple orchard through digital mapping, as well as assessing the correlation between these factors by means of geostatistics, establishing management zones. Forty representative points were set within 2.5 hectares of apple orchard, wherein soil samples were collected and analyzed, besides measurements of fruit quality (Brix degree, size or diameter, pulp firmness and color) to generate an overall index quality. We concluded that the fruit quality indexes, when isolated, did not show strong spatial dependence, unlike the index of fruit quality (FQI), derived from a combination of these parameters, allowing orchard planning according to management zones based on quality.

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ABSTRACT The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.

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The general goal of the present work was to study whether spatial perceptual asymmetry initially observed in linguistic dichotic listening studies is related to the linguistic nature of the stimuli and/or is modality-specific, as well as to investigate whether the spatial perceptual/attentional asymmetry changes as a function of age and sensory deficit via praxis. Several dichotic listening studies with linguistic stimuli have shown that the inherent perceptual right ear advantage (REA), which presumably results from the left lateralized linguistic functions (bottom-up processes), can be modified with executive functions (top-down control). Executive functions mature slowly during childhood, are well developed in adulthood, and decline as a function of ageing. In Study I, the purpose was to investigate with a cross-sectional experiment from a lifespan perspective the age-related changes in top-down control of REA for linguistic stimuli in dichotic listening with a forced-attention paradigm (DL). In Study II, the aim was to determine whether the REA is linguistic-stimulus-specific or not, and whether the lifespan changes in perceptual asymmetry observed in dichotic listening would exist also in auditory spatial attention tasks that put load on attentional control. In Study III, using visual spatial attention tasks, mimicking the auditory tasks applied in Study II, it was investigated whether or not the stimulus-non-specific rightward spatial bias found in auditory modality is a multimodal phenomenon. Finally, as it has been suggested that the absence of visual input in blind participants leads to improved auditory spatial perceptual and cognitive skills, the aim in Study IV was to determine, whether blindness modifies the ear advantage in DL. Altogether 180-190 right-handed participants between 5 and 79 years of age were studied in Studies I to III, and in Study IV the performance of 14 blind individuals was compared with that of 129 normally sighted individuals. The results showed that only rightward spatial bias was observed in tasks with intensive attentional load, independent of the type of stimuli (linguistic vs. non-linguistic) or the modality (auditory vs. visual). This multimodal rightward spatial bias probably results from a complex interaction of asymmetrical perceptual, attentional, and/or motor mechanisms. Most importantly, the strength of the rightward spatial bias changed as a function of age and augmented praxis due to sensory deficit. The efficiency of the performance in spatial attention tasks and the ability to overcome the rightward spatial bias increased during childhood, was at its best in young adulthood, and decreased as a function of ageing. Between the ages of 5 and 11 years probably at first develops movement and impulse control, followed by the gradual development of abilities to inhibit distractions and disengage attention. The errors especially in bilateral stimulus conditions suggest that a mild phenomenon resembling extinction can be observed throughout the lifespan, but especially the ability to distribute attention to multiple targets simultaneously decreases in the course of ageing. Blindness enhances the processing of auditory bilateral linguistic stimuli, the ability to overcome a stimulus-driven laterality effect related to speech sound perception, and the ability to direct attention to an appropriate spatial location. It was concluded that the ability to voluntarily suppress and inhibit the multimodal rightward spatial bias changes as a function of age and praxis due to sensory deficit and probably reflects the developmental level of executive functions.

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The environmental impacts of a single mine often remain local, but acidic and metal-rich acid mine drainage (AMD) from the waste materials may pose a serious threat to adjacent surface waters and their ecosystems. Testate amoebae (thecamoebian) analysis was used together with lake sediment geochemistry to study and evaluate the ecological effects of sulphidic metal mines on aquatic environments. Three different mines were included in the study: Luikonlahti Cu-mine in Kaavi, eastern Finland, Haveri Cu-Au mine in Ylöjärvi, southern Finland and Pyhäsalmi Zn-Cu-S mine in Pyhäjärvi, central Finland. Luikonlahti and Haveri are closed mines, but Pyhäsalmi is still operating. The sampling strategy was case specific, and planned to provide a representative sediment sample series to define natural background conditions, to detect spatial and temporal variations in mine impacts, to evaluate the possible recovery after the peak contamination, and to distinguish the effects of other environmental factors from the mining impacts. In the Haveri case, diatom analyses were performed alongside thecamoebian analysis to evaluate the similarities and differences between the two proxies. The results of the analyses were investigated with multivariate methods (direct and indirect ordinations, diversity and distance measure indices). Finally, the results of each case study were harmonized, pooled, and jointly analyzed to summarize the results for this dissertation. Geochemical results showed broadly similar temporal patterns in each case. Concentrations of ions in the pre-disturbance samples defined the natural baseline against which other results were compared. The beginning of the mining activities had only minor impacts on sediment geochemistry, mainly appearing as an increased clastic input into the lakes at Haveri and Pyhäsalmi. The active mining phase was followed by the metallic contamination and, subsequently, by the most recent change towards decreased but still elevated metal concentrations in the sediments. Because of the delay in the oxidation of waste material and formation of AMD, the most intense, but transient metal contamination phase occurred in the post-mining period at Luikonlahti and Haveri. At Pyhäsalmi, the highest metal contamination preceded effluent mitigation actions. Spatial gradients were observed besides the temporal evolution in both the pre-disturbance and mine-impacted samples from Luikonlahti and Pyhäsalmi. The geochemical gradients varied with distance from the main source of contaminants (dispersion and dilution) and with water depth (redox and pH). The spatial extent of the highest metal contamination associated with these mines remained rather limited. At Haveri, the metallic impact was widespread, with the upstream site in another lake basin found to be contaminated. Changes in thecamoebian assemblages corresponded well with the geochemical results. Despite some differences, the general features and ecological responses of the faunal assemblages were rather similar in each lake. Constantly abundant strains of Difflugia oblonga, Difflugia protaeiformis and centropyxids formed the core of these assemblages. Increasing proportions of Cucurbitella tricuspis towards the surface samples were found in all of the cases. The results affirmed the indicator value of some already known indicator forms, but such as C. tricuspis and higher nutrient levels, but also elicited possible new ones such as D. oblonga ‘spinosa’ and clayey substrate, high conductivity and/or alkalinity, D. protaeiformis ‘multicornis’ and pH, water hardness and the amount of clastic material and Centropyxis constricta ‘aerophila’ and high metal and S concentrations. In each case, eutrophication appeared to be the most important environmental factor, masking the effects of other variables. Faunal responses to high metal inputs in sediments remained minor, but were nevertheless detectable. Besides the trophic state of the lake, numerical methods suggested overall geochemical conditions (pH, redox) to be the most important factor at Luikonlahti, whereas the Haveri results showed the clearest connection between metals and amoebae. At Pyhäsalmi, the strongest relationships were found between Ca- and S-rich present loading, redox conditions and substrate composition. Sediment geochemistry and testate amoeba analysis proved to be a suitable combination of methods to detect and describe the aquatic mine impacts in each specific case, to evaluate recovery and to differentiate between the effects of different anthropogenic and natural environmental factors. It was also suggested that aquatic mine impacts can be significantly mitigated by careful design and after-care of the waste facilities, especially by reducing and preventing AMD. The case-specific approach is nevertheless necessary because of the unique characteristics of each mine and variations in the environmental background conditions.