21 resultados para Recreation areas--Pennsylvania--Planning--Maps.


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Toxocariasis is a worldwide public-health problem that poses major risks to children who may accidentally ingest embryonated eggs of Toxocara. The objectives of this study were to investigate the occurrence of anti-Toxocara spp. antibodies in children and adolescents and the variables that may be involved, as well as environmental contamination by Toxocara spp. eggs, in urban recreation areas of north central mesoregion, Paraná State, Brazil. From June 2005 to March 2007. a total of 376 blood samples were collected by the Public Health Service from children and adolescents one to 12 years old, of both genders. Samples were analyzed by the indirect ELISA method for detection of anti-Toxocara antibodies. Serum samples were previously absorbed with Ascaris suum antigens, and considered positive with a reagent reactivity index >1. Soil samples from all of the public squares and schools located in the four evaluated municipalities that had sand surfaces (n = 19) or lawns (n = 15) were analyzed. Of the 376 serum samples, 194 (51.6%) were positive. The seroprevalence rate was substantially higher among children aging one to five years (p = 0.001) and six to eight years (p = 0.022). The clinical signs and symptoms investigated did not show a statistical difference between seropositive and seronegative individuals (p > 0.05). In 76.5% of the investigated recreation places, eggs of Toxocara were detected in at least one of the five collected samples. Recreation areas from public schools were 2.8 times more contaminated than from public squares. It is important to institute educational programs to inform families and educators, as well as to improve sanitary control of animals and cleaning of the areas intended for recreation in order to prevent toxocariasis.

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Introduction Leprosy remains a relevant public health issue in Brazil. The objective of this study was to analyze the spatial distribution of new cases of leprosy and to detect areas with higher risks of disease in the City of Vitória. Methods The study was ecologically based on the spatial distribution of leprosy in the City of Vitória, State of Espírito Santo between 2005 and 2009. The data sources used came from the available records of the State Health Secretary of Espírito Santo. A global and local empirical Bayesian method was used in the spatial analysis to produce a leprosy risk estimation, and the fluctuation effect was smoothed from the detection coefficients. Results The study used thematic maps to illustrate that leprosy is distributed heterogeneously between the neighborhoods and that it is possible to identify areas with high risk of disease. The Pearson correlation coefficient of 0.926 (p = 0.001) for the Local Method indicated highly correlated coefficients. The Moran index was calculated to evaluate correlations between the incidences of adjoining districts. Conclusions We identified the spatial contexts in which there were the highest incidence rates of leprosy in Vitória during the studied period. The results contribute to the knowledge of the spatial distribution of leprosy in the City of Vitória, which can help establish more cost-effective control strategies because they indicate specific regions and priority planning activities that can interfere with the transmission chain.

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Medium-resolution satellite images have been widely used for the identification and quantification of irrigated areas by center pivot. These areas, which present predominantly circular forms, can be easily identified by visual analyses of these images. In addition to identifying and quantifying areas irrigated by center pivot, other information that is associated to these areas is fundamental for producing cadastral maps. The goal of this work was to generate cadastral mapping of areas irrigated by center pivots in the State of Minas Gerais, Brazil, with the purpose of supplying information on irrigated agriculture. Using the satellite CBERS2B/CCD, images were used to identify and quantify irrigated areas and then associate these areas with a database containing information about: irrigated area, perimeter, municipality, path row, basin in which the pivot is located, and the date of image acquisition.3,781 center pivots systems were identified. The smallest area irrigated was 4.6 hectares and the largest one was 192.6 hectares. The total estimated value of irrigated area was 254,875 hectares. The largest number of center pivots appeared in the municipalities of Unaí and Paracatu, with 495 and 459 systems, respectively. Cadastral mapping is a very useful tool to assist and enhance information on irrigated agriculture in the State of Minas Gerais.

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A brief description of the main features of the health planning technique developed by the "Centro de Estudios del Desarrollo" (CENDES) in Venezuela, and proposed by the Pan-American Health Organization for use in Latin America, is presented. This presentation is followed by an appraisal of the planning method which includes comments both upon its positive aspects and upon its negative points. Comments are also made referring to other recent publications of the WHO/PAHO on health planning. In conclusion, the CENDES technique is considered a health planning method of great potential for use especially in underdeveloped areas, the success of its application depending upon the hability of the health planners to introduce the necessary modifications to adapt to the local circunstamces.

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INTRODUCTION: The prevalence and intensity of geohelminth infections and schistosomiasis remain high in the rural areas of Zona da Mata, Pernambuco (ZMP), Brazil, where these parasites still represent a significant public health problem. The present study aimed to spatially assess the occurrences of schistosomiasis and geohelminthiasis in the ZMP. METHODS: The ZMP has a population of 1,132,544 inhabitants, formed by 43 municipalities. An ecological study was conducted, using secondary data relating to positive human cases and parasite loads of schistosomiasis and positive human cases of geohelminthiasis that were worked up in Excel 2007. We used the coordinates of the municipal headquarters to represent the cities which served as the unit of analysis of this study. The Kernel estimator was used to spatially analyze the data and identify distribution patterns and case densities, with analysis done in ArcGIS software. RESULTS: Spatial analysis from the Kernel intensity estimator made it possible to construct density maps showing that the northern ZMP was the region with the greatest number of children infected with parasites and the populations most intensely infected by Schistosoma mansoni. In relation to geohelminths, there was higher spatial distribution of cases of Ascaris lumbricoides and Trichuris trichiura in the southern ZMP, and greater occurrence of hookworms in the northern/central ZMP. CONCLUSIONS: Despite several surveys and studies showing occurrences of schistosomiasis and geohelminthiasis in the ZMP, no preventive measures that are known to have been effective in decreasing these health hazards have yet been implemented in the endemic area.

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INTRODUCTION: Visceral leishmaniasis (VL) is a zoonosis of great importance to public health and is considered a neglected disease by the World Health Organization. The disease has expanded and become more prevalent in urban areas in Brazil. METHODS: Geospatial analyses were performed and thematic maps of the triad of the disease were produced for the study period (2003-2012) in the urban area of the municipality of Rondonópolis in the midwestern State of Mato Grosso (MT), Brazil, TerraView 4.2.2 software was used for the analyses. RESULTS: A total of 87.9% of the 186 confirmed human cases of VL were cured. Children between the ages of 1 and 4 were the most affected. Registered deaths were predominant among adults aged 60 years or older. The urban area of the municipality consists of eight strata and 12 census districts include 237 neighborhoods. All sectors had confirmed cases of VL. During the study period, human cases of the disease were recorded in 90 neighborhoods. The 23 deaths from the disease were distributed in 21 neighborhoods. Sandflies carrying the parasite were captured in 192 out of 200 neighborhoods evaluated for the presence of the VL vector. The presence of dogs carrying the parasite was confirmed in, 140 out of 154 surveyed neighborhoods. CONCLUSIONS: The data demonstrated the endemic nature of VL, with a high percentage of infected children, a high distribution of canine infection, and a wide adaptation and dispersal of the vectors in the urban environment. These results, illustrate the process of urbanization of VL in the municipality of Rondonópolis, MT, Brazil.

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Remote sensing and geographical information technologies were used to discriminate areas of high and low risk for contracting kala-azar or visceral leishmaniasis. Satellite data were digitally processed to generate maps of land cover and spectral indices, such as the normalised difference vegetation index and wetness index. To map estimated vector abundance and indoor climate data, local polynomial interpolations were used based on the weightage values. Attribute layers were prepared based on illiteracy and the unemployed proportion of the population and associated with village boundaries. Pearson's correlation coefficient was used to estimate the relationship between environmental variables and disease incidence across the study area. The cell values for each input raster in the analysis were assigned values from the evaluation scale. Simple weighting/ratings based on the degree of favourable conditions for kala-azar transmission were used for all the variables, leading to geo-environmental risk model. Variables such as, land use/land cover, vegetation conditions, surface dampness, the indoor climate, illiteracy rates and the size of the unemployed population were considered for inclusion in the geo-environmental kala-azar risk model. The risk model was stratified into areas of "risk"and "non-risk"for the disease, based on calculation of risk indices. The described approach constitutes a promising tool for microlevel kala-azar surveillance and aids in directing control efforts.

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Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. However, there are still many problems in model evaluation and application, and one of the solutions is to find a consensus solution among models derived from different mathematical and statistical models for niche modeling, climatic projections and variable combination, all of which are sources of uncertainty during niche modeling. In this paper, we discuss this approach of ensemble forecasting and propose that it can be divided into three phases with increasing levels of complexity. Phase I is the simple combination of maps to achieve a consensual and hopefully conservative solution. In Phase II, differences among the maps used are described by multivariate analyses, and Phase III consists of the quantitative evaluation of the relative magnitude of uncertainties from different sources and their mapping. To illustrate these developments, we analyzed the occurrence data of the tiger moth, Utetheisa ornatrix (Lepidoptera, Arctiidae), a Neotropical moth species, and modeled its geographic range in current and future climates.

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Geobiota are defined by taxic assemblages (i.e., biota) and their defining abiotic breaks, which are mapped in cross-section to reveal past and future biotic boundaries. We term this conceptual approach Temporal Geobiotic Mapping (TGM) and offer it as a conceptual approach for biogeography. TGM is based on geological cross-sectioning, which creates maps based on the distribution of biota and known abiotic factors that drive their distribution, such as climate, topography, soil chemistry and underlying geology. However, the availability of abiotic data is limited for many areas. Unlike other approaches, TGM can be used when there is minimal data available. In order to demonstrate TGM, we use the well-known area in the Blue Mountains, New South Wales (NSW), south-eastern Australia and show how surface processes such as weathering and erosion affect the future distribution of a Moist Basalt Forest taxic assemblage. Biotic areas are best represented visually as maps, which can show transgressions and regressions of biota and abiota over time. Using such maps, a biogeographer can directly compare animal and plant distributions with features in the abiotic environment and may identify significant geographical barriers or pathways that explain biotic distributions.

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The quality of semi-detailed (scale 1:100.000) soil maps and the utility of a taxonomically based legend were assessed by studying 33 apparently homogeneous fields with strongly weathered soils in two regions in São Paulo State: Araras and Assis. An independent data set of 395 auger sites was used to determine purity of soil mapping units and analysis of variance within and between mapping units and soil classification units. Twenty three soil profiles were studied in detail. The studied soil maps have a high purity for some legend criteria, such as B horizon type (> 90%) and soil texture class (> 80%). The purity for the "trophic character" (eutrophic, dystrophic, allic) was only 55% in Assis. It was 88% in Araras, where many soil units had been mapped as associations. In both regions, the base status of clay-textured soils was generally better than suggested by the maps. Analysis of variance showed that mapping was successful for "durable" soil characteristics such as clay content (> 80% of variance explained) and cation exchange capacity (≥ 50% of variance explained) of 0-20 and 60-80 cm layers. For soil characteristics that are easily modified by management, such as base saturation of the 0-20 cm layer, the maps had explained very little (< 15%) of the total variance in the study areas. Intermediate results were obtained for base saturation of the 60-80 cm layer (56% in Assis; 42% in Araras). Variance explained by taxonomic groupings that formed the basis for the legend of the soil maps was similar to, often even smaller than, variance explained by mapping units. The conclusion is that map boundaries have been very carefully located, but descriptions of mapping units could be improved. In future mappings, this could possibly be done at low cost by (a) bulk sampling to remove short range variation and enhance visualization of spatial patterns at distances > 100 m; (b) taking advantage of correlations between easily measured soil characteristics and chemical soil properties and, (c) unbending the link between legend criteria and a taxonomic system. The maps are well suited to obtain an impression of land suitability for high-input farming. Additional field work and data on former land use/management are necessary for the evaluation of chemical properties of surface horizons.

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Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.

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The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

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Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

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There is a great lack of information from soil surveys in the southern part of the State of Amazonas, Brazil. The use of tools such as geostatistics may improve environmental planning, use and management. In this study, we aimed to use scaled semivariograms in sample design of soil physical properties of some environments in Amazonas. We selected five areas located in the south of the state of Amazonas, Brazil, with varied soil uses, such as forest, archaeological dark earth (ADE), pasture, sugarcane cropping, and agroforestry. Regular mesh grids were set up in these areas with 64 sample points spaced at 10 m from each other. At these points, we determined the particle size composition, soil resistance to penetration, moisture, soil bulk density and particle density, macroporosity, microporosity, total porosity, and aggregate stability in water at a depth of 0.00-0.20 m. Descriptive and geostatistical analyses were performed. The sample density requirements were lower in the pasture area but higher in the forest. We concluded that managed-environments had differences in their soil physical properties compared to the natural forest; notably, the soil in the ADE environment is physically improved in relation to the others. The physical properties evaluated showed a structure of spatial dependence with a slight variability of the forest compared to the others. The use of the range parameter of the semivariogram analysis proved to be effective in determining an ideal sample density.

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The lack of information concerning the variability of soil properties has been a major concern of researchers in the Amazon region. Thus, the aim of this study was to evaluate the spatial variability of soil chemical properties and determine minimal sampling density to characterize the variability of these properties in five environments located in the south of the State of Amazonas, Brazil. The five environments were archaeological dark earth (ADE), forest, pasture land, agroforestry operation, and sugarcane crop. Regular 70 × 70 m mesh grids were set up in these areas, with 64 sample points spaced at 10 m distance. Soil samples were collected at the 0.0-0.1 m depth. The chemical properties of pH in water, OM, P, K, Ca, Mg, H+Al, SB, CEC, and V were determined at these points. Data were analyzed by descriptive and geostatistical analyses. A large part of the data analyzed showed spatial dependence. Chemical properties were best fitted to the spherical model in almost all the environments evaluated, except for the sugarcane field with a better fit to the exponential model. ADE and sugarcane areas had greater heterogeneity of soil chemical properties, showing a greater range and higher sampling density; however, forest and agroforestry areas had less variability of chemical properties.