Physical quality of an Oxisol cultivated with maize submited to cover crops in the pre-cropping period

The intensive use of land alters the distribution of the pore size which imparts consequences on the soil physical quality. The Least Limiting Water Range (LLWR) allows for the visualization of the effects of management systems upon either the improvement or the degradation of the soil physical quality. The objective of this study was to evaluate the physical quality of a Red Latosol (Oxisol) submited to cover crops in the period prior to the maize crop in a no-tillage and conventional tillage system, using porosity, soil bulk density and the LLWR as attributes. The treatments were: conventional tillage (CT) and a no-tillage system with the following cover crops: sunn hemp (Crotalaria juncea L.) (NS), pearl millet (Pennisetum americanum (L.) Leeke) (NP) and lablab (Dolichos lablab L.) (NL). The experimental design was randomized blocks in subdivided plots with six replications, with the plots being constituted by the treatments and the subplots by the layers analyzed. The no-tillage systems showed higher total porosity and soil organic matter at the 0-0.5 m layer for the CT. The CT did not differ from the NL or NS in relation to macroporosity. The NP showed the greater porosity, while CT and NS presented lower soil bulk density. No < 10 % airing porosity was found for the treatments evaluated, and value for water content where soil aeration is critical (θPA) was found above estimated water content at field capacity (θFC) for all densities. Critical soil bulk density was of 1.36 and 1.43 Mg m-3 for NP and CT, respectively. The LLWR in the no-tillage systems was limited in the upper part by the θFC, and in the bottom part, by the water content from which soil resistance to penetration is limiting (θPR). By means of LLWR it was observed that the soil presented good physical quality.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Structural quality of soils cultivated with coffee and pasture in an environmental protection area

Studies of soils in Environmental Protection Areas (EPAs) are of great importance, because they are an essential component of ecosystems, directly interfering in environmental sustainability. The objective of this study was to evaluate the structural quality of soil cultivated with coffee and used as pasture in the Capituva's River microbasin, which is located in the Environmental Protection Area in Coqueiral, south of the state of Minas Gerais. Uniaxial compression test (preconsolidation test) and soil resistance to penetration were used. Undisturbed samples were taken from the surface layer (0-5 cm) of the soils in the area: a typic dystrophic Red Latosol (LVd - Oxisol), a typic eutrophic Red Argisol (PVe - Ultisol), and a typic dystrophic Haplic Cambisol (CXbd - Inceptisol). A significant linear positive correlation was observed between the results of the preconsolidation test and soil resistance to penetration. Load bearing capacity of soil could be estimated accordingly by means of penetration resistance for LVd, PVe, and CXbd. Cambisol - CXbd showed lower loading support capacity and resistance to penetration than LVd and PVe, due to the better crop management in this soil that resulted in higher physical quality which accounts for higher production and environmental sustainability.

Physical quality of a yellow latossol under integrated crop-livestock system

Soil physical quality is essential to global sustainability of agroecosystems, once it is related to processes that are essential to agricultural crop development. This study aimed to evaluate physical attributes of a Yellow Latossol under different management systems in the savanna area in the state of Piaui. This study was developed in Uruçuí southwest of the state of Piauí. Three systems of soil management were studied: an area under conventional tillage (CT) with disk plowi and heavy harrow and soybean crop; an area under no-tillage with soybean-maize rotation and millet as cover crop (NT + M); two areas under Integrated Crop-Livestock System, with five-month pasture grazing and soybean cultivation and then continuous pasture grazing (ICL + S and ICL + P, respectively). Also, an area under Native Forest (NF) was studied. The soil depths studied were 0.00-0.05, 0.05-0.10 and 0.10-0.20 m. Soil bulk density, as well as porosity and stability of soil aggregates were analyzed as physical attributes. Anthropic action has changed the soil physical attributes, in depth, in most systems studied, in comparison to NF. In the 0.00 to 0.05 m depth, ICL + P showed higher soil bulk density value. As to macroporosity, there was no difference between the management systems studied and NF. The management systems studied changed the soil structure, having, as a result, a small proportion of soil in great aggregate classes (MWD). Converting native forest into agricultural production systems changes the soil physical quality. The Integrated Crop-Livestock System did not promote the improvement in soil physical quality.

What trees tell us: dendrochronological and statistical analysis of the data

Trees are a great bank of data, named sometimes for this reason as the "silentwitnesses" of the past. Due to annual formation of rings, which is normally influenced directly by of climate parameters (generally changes in temperature and moisture or precipitation) and other environmental factors; these changes, occurred in the past, are"written" in the tree "archives" and can be "decoded" in order to interpret what hadhappened before, mainly applied for the past climate reconstruction.Using dendrochronological methods for obtaining samples of Pinus nigra fromthe Catalonian PrePirineous region, the cores of 15 trees with total time spine of about 100 - 250 years were analyzed for the tree ring width (TRW) patterns and had quite high correlation between them (0.71 ¿ 0.84), corresponding to a common behaviour for the environmental changes in their annual growth.After different trials with raw TRW data for standardization in order to take outthe negative exponential growth curve dependency, the best method of doubledetrending (power transformation and smoothing line of 32 years) were selected for obtaining the indexes for further analysis.Analyzing the cross-correlations between obtained tree ring width indexes andclimate data, significant correlations (p<0.05) were observed in some lags, as forexample, annual precipitation in lag -1 (previous year) had negative correlation with TRW growth in the Pallars region. Significant correlation coefficients are between 0.27- 0.51 (with positive or negative signs) for many cases; as for recent (but very short period) climate data of Seu d¿Urgell meteorological station, some significant correlation coefficients were observed, of the order of 0.9.These results confirm the hypothesis of using dendrochronological data as aclimate signal for further analysis, such as reconstruction of climate in the past orprediction in the future for the same locality.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Impacts of different management systems on the physical quality of an Amazonian Oxisol

The physical quality of Amazonian soils is relatively unexplored, due to the unique characteristics of these soils. The index of soil physical quality is a widely accepted measure of the structural quality of soils and has been used to specify the structural quality of some tropical soils, as for example of the Cerrado ecoregion of Brazil. The research objective was to evaluate the physical quality index of an Amazonian dystrophic Oxisol under different management systems. Soils under five managements were sampled in Paragominas, State of Pará: 1) a 20-year-old second-growth forest (Forest); 2) Brachiaria sp pasture; 3) four years of no-tillage (NT4.); 4) eight years of no-tillage (NT8); and 5) two years of conventional tillage (CT2). The soil samples were evaluated for bulk density, macro and microporosity and for soil water retention. The physical quality index of the samples was calculated and the resulting value correlated with soil organic matter, bulk density and porosity. The surface layers of all systems were more compacted than those of the forest. The physical quality of the soil was best represented by the relations of the S index to bulk density and soil organic matter.

Physical quality of an oxisol under different uses

The use of a soil induces changes in the physical properties according to the management, tillage intensity and type of crop. The objective of this work was to measure the alterations of some of the soil physical properties and evaluate the physical quality by the S index, an indicator proposed by Dexter (2004), comparing the land uses: eucalyptus plantations at different ages, grazing pasture, annual crops, and an area of preserved secondary vegetation with an area of preserved native forest (National Forest Araripe - NFA) as control. The study was carried out on an Oxisol on the Fazenda Redenção, in Jardim, State of Ceará, Brazil. The experiment was arranged in a completely randomized design with seven treatments and three replications in the layers 0-0.1 and 0.1-0.2 m. The soil was analyzed for the following physical properties: bulk density, particle density, total pore volume, micro and macroporosity, soil water retention curves and water availability. Based on the S index, the hypothesis that the use of a soil deteriorates the physical quality was accepted. Clearly, native forest (NFA) was the land use with the best conditions in all physical properties studied, followed closely by the area reforested with 20 year-old eucalyptus. The use as grazing pasture affected the soil physical conditions most, especially in the surface layer (0-0.1 m), as evidenced by increased bulk density and a substantial reduction in soil porosity, mainly in macroporosity. Microporosity was not influenced by any of the uses and in any layer studied.

A Confluence of Risks: Control and Compliance in the World of Unstructured Data, Big Data and the Cloud

The emergence of powerful new technologies, the existence of large quantities of data, and increasing demands for the extraction of added value from these technologies and data have created a number of significant challenges for those charged with both corporate and information technology management. The possibilities are great, the expectations high, and the risks significant. Organisations seeking to employ cloud technologies and exploit the value of the data to which they have access, be this in the form of "Big Data" available from different external sources or data held within the organisation, in structured or unstructured formats, need to understand the risks involved in such activities. Data owners have responsibilities towards the subjects of the data and must also, frequently, demonstrate that they are in compliance with current standards, laws and regulations. This thesis sets out to explore the nature of the technologies that organisations might utilise, identify the most pertinent constraints and risks, and propose a framework for the management of data from discovery to external hosting that will allow the most significant risks to be managed through the definition, implementation, and performance of appropriate internal control activities.