Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: II. quality of soil maps

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.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

Inferring transport characteristics in a fractured rock aquifer by combining single-hole ground-penetrating radar reflection monitoring and tracer test data

Investigations of solute transport in fractured rock aquifers often rely on tracer test data acquired at a limited number of observation points. Such data do not, by themselves, allow detailed assessments of the spreading of the injected tracer plume. To better understand the transport behavior in a granitic aquifer, we combine tracer test data with single-hole ground-penetrating radar (GPR) reflection monitoring data. Five successful tracer tests were performed under various experimental conditions between two boreholes 6 m apart. For each experiment, saline tracer was injected into a previously identified packed-off transmissive fracture while repeatedly acquiring single-hole GPR reflection profiles together with electrical conductivity logs in the pumping borehole. By analyzing depth-migrated GPR difference images together with tracer breakthrough curves and associated simplified flow and transport modeling, we estimate (1) the number, the connectivity, and the geometry of fractures that contribute to tracer transport, (2) the velocity and the mass of tracer that was carried along each flow path, and (3) the effective transport parameters of the identified flow paths. We find a qualitative agreement when comparing the time evolution of GPR reflectivity strengths at strategic locations in the formation with those arising from simulated transport. The discrepancies are on the same order as those between observed and simulated breakthrough curves at the outflow locations. The rather subtle and repeatable GPR signals provide useful and complementary information to tracer test data acquired at the outflow locations and may help us to characterize transport phenomena in fractured rock aquifers.

Extensions of maps defined on many fibres

Let S be a fibred surface. We prove that the existence of morphisms from non countably many fibres to curves implies, up to base change, the existence of a rational map from S to another surface fibred over the same base reflecting the properties of the original morphisms. Under some conditions of unicity base change is not needed and one recovers exactly the initial maps.

Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

Integration of ground-penetrating radar and microgravimetric methods to map shallow caves

Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Uso de sistema GPR (Ground Penetring Radar) na avaliação de atributos de um solo sob plantio de cana-de-açúcar

O GPR utiliza técnica indireta para investigação das estruturas de subsuperfície, sendo caracterizado como método não-invasivo, o qual permite extrair informações ao longo do perfil de solo sem perfurar, sondar ou escavar. Este trabalho teve o objetivo de avaliar a utilização do GPR no estabelecimento de atributos físicos do solo em área de cultivo com cana-de-açúcar, além de estabelecer sua correlação com o método do cilindro volumétrico. A área de estudo está localizada no município de Bom Sucesso - PR, sendo utilizada com cultura da cana há mais de 20 anos. Foram obtidas amostras de solos indeformadas com cilindro volumétrico nas profundidades de 0-0,1, 0,1-0,2, 0,2-0,3, 0,3-0,4 e 0,4-0,5 m, ao longo de três transeptos paralelos, sendo o central referente à linha de plantio (transepto 2) e os outros dois correspondentes às entrelinhas laterais (transeptos 1 e 3). Os valores de densidade e porosidade total, obtidos por meio das amostras físicas, foram inicialmente interpretados para verificar o estado do solo nas linhas e nas entrelinhas de cana, nas cinco profundidades. Posteriormente, foram correlacionados com os valores das constantes dielétricas (K) adquiridos pelo georradar, porém apenas para a camada de 0,4-0,5 m, uma vez que as camadas superficiais até a profundidade de 0,4 m não puderam ser avaliadas devido às limitações técnicas do equipamento, aliadas às condições físicas e químicas do solo, que acabaram por prejudicar as reflexões. A densidade mostrou-se menor nas linhas, quando comparada às entrelinhas, para as camadas de 0-0,1 e 0,2-0,3 m. A porosidade total foi menor nas entrelinhas do que nas linhas na camada de 0-0,1 m. Os valores de K foram maiores nas linhas, onde a umidade e a porosidade total foram maiores, e menores nas entrelinhas, onde as densidades encontravam se próximas ao limite crítico. A correlação de K com a densidade e porosidade total não foi significativa. Pequenas modificações na porosidade do solo em função do aumento da densidade foram suficientes para diminuir o valor de K nas entrelinhas, devido à redução na quantidade de água nos poros. Esse fato pode ser confirmado pela correlação de K com a umidade. Assim, pode-se dizer que o georradar foi extremamente sensível à variação de umidade no solo, apresentando melhores resultados para esta variável do que para a densidade e porosidade total determinada por meio do cilindro volumétrico.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

New vineyard cultivation practices create patchy ground vegetation, favouring Woodlarks

Intensive agriculture, in which detrimental farming practices lessen food abundance and/or reduce food accessibility for many animal species, has led to a widespread collapse of farmland biodiversity. Vineyards in central and southern Europe are intensively cultivated; though they may still harbour several rare plant and animal species, they remain little studied. Over the past decades, there has been a considerable reduction in the application of insecticides in wine production, with a progressive shift to biological control (integrated production) and, to a lesser extent, organic production. Spraying of herbicides has also diminished, which has led to more vegetation cover on the ground, although most vineyards remain bare, especially in southern Europe. The effects of these potentially positive environmental trends upon biodiversity remain mostly unknown as regards vertebrates. The Woodlark (Lullula arborea) is an endangered, short-distance migratory bird that forages and breeds on the ground. In southern Switzerland (Valais), it occurs mostly in vineyards. We used radiotracking and mixed effects logistic regression models to assess Woodlark response to modern vineyard farming practices, study factors driving foraging micro-habitat selection, and determine optimal habitat profile to inform management. The presence of ground vegetation cover was the main factor dictating the selection of foraging locations, with an optimum around 55% at the foraging patch scale. These conditions are met in integrated production vineyards, but only when grass is tolerated on part of the ground surface, which is the case on ca. 5% of the total Valais vineyard area. In contrast, conventionally managed vineyards covering a parts per thousand yen95% of the vineyard area are too bare because of systematic application of herbicides all over the ground, whilst the rare organic vineyards usually have a too-dense sward. The optimal mosaic with ca. 50% ground vegetation cover is currently achieved in integrated production vineyards where herbicide is applied every second row. In organic production, ca. 50% ground vegetation cover should be promoted, which requires regular mechanical removal of ground vegetation. These measures are likely to benefit general biodiversity in vineyards.

Ground-state self-consistent calculation of quantum dots under magnetic fields: Addition spectrum

A density-functional self-consistent calculation of the ground-state electronic density of quantum dots under an arbitrary magnetic field is performed. We consider a parabolic lateral confining potential. The addition energy, E(N+1)-E(N), where N is the number of electrons, is compared with experimental data and the different contributions to the energy are analyzed. The Hamiltonian is modeled by a density functional, which includes the exchange and correlation interactions and the local formation of Landau levels for different equilibrium spin populations. We obtain an analytical expression for the critical density under which spontaneous polarization, induced by the exchange interaction, takes place.