994 resultados para Soil mapping


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Photointerpretative and multivariate statistical techniques were applied to variants of soil use measured in 4 hydrological basins of third order ramification, belonging to Tiete basin municipal district of Botucatu, Sao Paulo State. The aim was the grouping of basins of second degree of similarity, as well as to infer spatial distribution representativeness. The hydrological basins were located in 3 physiographic regions, with peripheric depression, cuesta front and cuesta backslope, embracing the following soil units: Regosol intergrade to Red Yellow Podzolic and intergrade to Red Yellow Latosol, Red Yellow Latosol-sandy phase, Litosol basaltic substract phase and Purple Latosol. The results obtained allow the conclusion that soil use not always reflects its fertility. -after English summary

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The objective of this work was to evaluate the magnetic susceptibility efficiency for estimating the support capacity of areas for vinasse application. Two hundred forty-one soil samples were collected from a 380-ha area, on which soil chemical properties, clay content, and magnetic susceptibility were determined. Vinasse requirement was calculated for each sample. Data were subjected to descriptive statistical analysis, and regression models were developed between magnetic susceptibility and the other evaluated attributes. The analysis of data spatial dependence was performed using geostatistics. Kriging maps and cross variograms were built in order to investigate the spatial correlation between soil magnetic susceptibility and studied attributes. Based on the map of vinasse requirement, on the soil classes, and on the kriging map, calculations were done for average vinasse dose and average soil support capacity, weighted by the area. Magnetic susceptibility has significant linear spatial correlation with recommended vinasse doses and soil support capacity for the application of this effluent, and it can be used as a pedotransfer function for indirect quantification of soil support capacity.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Agronomia (Produção Vegetal) - FCAV

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The correct spatial intervention in the administration of the plantation, arising from specific areas of soil mapping, can increase your productivity as well as profitability and yields in agriculture. The spatial and Pearson's relationships between sugarcane attributes and chemical attributes of a Typic Tropustalf were studied in the growing season of 2010, in Suzanapolis, State of Sao Paulo, Brazil (20 degrees 27'33 '' S lat.; 51 degrees 08'05 '' W long.), in order to obtain the attributes that had the best sugarcane productivity relationship. To this end, a geostatistical grid containing 118 sample points was installed for soil and plant data collection in an area of 10.5 ha with the third crop cut. The productivity of sugarcane (PRO) represented the attribute of the plant, while the attributes of the soil were: K+, Ca+2, Mg+2 and organic matter at depths of 0-0.20 m and 0.20-0.40 m. Relationships were calculated between the PRO and the attributes of the soil. Semivariograms were adjusted for all attributes, obtaining the respective krigings and the cross-validations. It was also made the cokrigings between the PRO and the soil attributes. The levels of the soil organic matter, for their evident substantial correlations, Sperman's Rho and spatial, with the productivity of sugarcane, are indicators of two specific areas of soil management strongly associated with the productivity of sugarcane. In such zones this productivity varies between 75.8-94.7 t ha(-1) and 101.0-119.9 t ha(-1), when the levels of organic matter respectively are 12.7-14.5 g dm(-3) (0-0.20 m) and 11.8-12.8 g dm(-3) (0.20-0.40 m).

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Pós-graduação em Agronomia (Produção Vegetal) - FCAV

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Detailed environmental land characterization is essential for technical and financial planning, for both the scientific point of view and technological application. This work aimed at the physiographic and pedological characterization and eucalyptus productivity mapping at Itatinga Forest Sciences Experimental Station (southeastern Brazil), using geographic information systems in order to identify possible cause-effect relationships between forest productivity and soil attributes. The digital cartographic dataset was structured as follows: as primary source of data, aerial photograph and field survey were used and, as a secondary source, topographical, geological and land use occupation maps were used. For mapping wood productivity at age six (MAI6, Mean Annual Increment), inventory data of permanent plots (same species, provenance and age) were used, which were obtained from Eucalyptus grandis plantations. Using simple linear correlation and backward stepwise multiple regression analysis, the dependent variable (MAI) was related with physical and chemical characteristics of the soils. Two standards of contour curves were identified, one with close curves, narrow and surrounding the drainage network, in the steeper and lower altitude areas; the other, with spaced contour lines, in the areas of higher altitude and with plane relief. Six types of soils were characterized as being highly related to the physiographic patterns of the area: loamy sandy to sandy clayey Typic Hapludox (LVAd, 47.5%), clayey Rhodic Hapludox (LVd1, 33.4%), sandy clay Rhodic Hapludox (LVd2, 6%), clayey Rhodic Hapludox (LVdf, 9.1%), Entisols (G, 3.4%) and Fluvents soil (RY, 0.6%). There were large variations in wood productivity in the Eucalyptus grandis plantations, characterized in six classes, ranging from 26 to 52 m(3) ha(-1) yr(-1). These productivity changes were strictly related to soil mapping units. Through multiple regression analysis, we found that clay and organic matter contents were the attributes which most strongly explained the productivity differences.

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Abstract: BRIGUICHE. H, ZIDANE. L. Floristic And Ethnobotanical Studies Of Medicinal Plants Of The City Of El -Jadida (MOROCCO). In the framework of the ethnobotanical studies on medicinal plants undertaken by the Laboratory of Biodiversity and Natural Resources of the Faculty of Sciences of Kenitra (Morocco), we are interested in the area of El Jadida which presents a rather important floristic richness thanks to changes in its ecological conditions By using 204 questionnaire, the ethnobotanical surveys were conducted in the field during the years 2012-2013. The location of the different sampling sites was determined by the stratified sampling method. The analysis of the results obtained from the questionnaires and forms using statistical processing allowed us to identify 70 plant species distributed in 69 genera and 37 families. These results also show that most of these species are mainly used in the care of the digestive system and respiratory system. The seed is the most used part in local traditional medicines and the decoction is the most frequent mode with a rate of 31%. The species Origanum compactum is the most used by the population of the city of El Jadida 47 quotes.  

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Background In order to increase the efficient allocation of soil-transmitted helminth (STH) disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection. Methodology/Principal Findings Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1) Luzon and the Visayas and 2) Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies) as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao. Conclusions/Significance This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon.

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Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

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The effect of climate change on the shallow expansive foundation conditions of resident dwellings is costing several hundred billion dollars worldwide. The design and costs of constructing or repairing residential footings is greatly influenced by the degree of ground movement, which is driven by the magnitude of change in soil moisture. The impacts of climate change on urban infrastructure are expected to include accelerated degradation of materials and foundations of buildings and facilities, increased ground movement, changes in ground water affecting the chemical structure of foundations, and fatigue of structures from extreme storm events. Previous research found that residential houses that were built less than five years ago have suffered major cracks and other damage caused by slab movement after record rainfall. The Thornthwaite Moisture Index (TMI) categorises climate on the basis of rainfall, temperature, potential evapotranspiration and the water holding capacity of the soil. Originally TMI was mainly used to map soil moisture conditions for agriculture but soon became a method to predict pavement and foundation changes. Few researchers have developed TMI maps for Australia, but generally, their accuracy is low or unknown, and their use is limited. The aims of this paper are: (1) To produce accurate maps of TMI for the state of Victoria for 100 years (1913 to 2012) in 20 year periods using long-term historical climatic data and advanced spatial statistics methods in GIS, and (2) Analyse the spatial and temporal changes of TMI in Victoria. Preliminary results suggest that a better understanding of climate change through long-term TMI mapping can assist urban planning and guide construction regulations towards the development of cities which are more resilient.