931 resultados para spatial and amplitude tapering


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We present for the first time all 12 d18O records obtained from ice cores drilled in the framework of the North Greenland Traverse (NGT) between 1993 and 1995 in northern Greenland. The cores cover an area of 680 km × 317 km, 10 % of the Greenland ice sheet. Depending on core length (100-175 m) and accumulation rate (90-200 kg/m**2/a) the single records reflect an isotope-temperature history over the last 500-1100 years. Lowest d18O mean values occur north of the summit and east of the main divide as a consequence of Greenland's topography. In general, ice cores drilled on the main ice divide show different results than those drilled east of the main ice divide that might be influenced by secondary regional moisture sources. A stack of all NGT records and the NGRIP record is presented with improved signal-to-noise ratio. Compared to single records, this stack represents the mean d18O signal for northern Greenland that is interpreted as proxy for temperature. Our northern Greenland d18O stack indicates distinctly enriched d18O values during medieval times, about AD 1420 ± 20 and from AD 1870 onwards. The period between AD 1420 and AD 1850 has depleted d18O values compared to the average for the entire millennium and represents the Little Ice Age. The d18O values of the 20th century are comparable to the medieval period but are lower than that about AD 1420.

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In a traditional system of exogamous and patrilocal marriage prevalent in much of Sub-Saharan Africa, when she marries, a rural woman typically leaves her kin to reside with her husband living outside her natal village. Since a village that allows a widow to inherit her late husband's land can provide her with old age security, single females living outside the village are more likely to marry into the village. Using a natural experimental setting, provided by the longitudinal household panel data drawn from rural Tanzania for the period from 1991 to 2004, during which several villages that initially banned a widow's land inheritance removed this discrimination, this study provides evidence in support of this view, whereby altering a customary land inheritance rules in a village in favor of widows increased the probability of males marrying in that village. This finding suggests that providing rural women with old age protection (e.g., insurance, livelihood protection) has remarkable spatial and temporal welfare effects by influencing their decision to marry.

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Stereo video techniques are effective for estimating the space-time wave dynamics over an area of the ocean. Indeed, a stereo camera view allows retrieval of both spatial and temporal data whose statistical content is richer than that of time series data retrieved from point wave probes. Classical epipolar techniques and modern variational methods are reviewed to reconstruct the sea surface from the stereo pairs sequentially in time. Current improvements of the variational methods are presented.

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PREDICT POTENTIAL DISTRIBUTION. Spatial and temporal evolution of the species under different climate scenarios. Generation of habitat suitability models (HSM)  high degree of uncertainty and limitations. The importance of their validation has been stressed. In this work we discuss the present potential distribution of P. sylvestris and P. nigra in the Iberian Peninsula by using MaxEnt, and evaluate the influence of the different environmental variables. Our intention is to select a set of environmental variables that explains better their current distribution, to achieve the most accurate and reliable models. Then we project them to the past climatic conditions (21 to 0 kyrs BP), to evaluate the outputs with existing palaeo-ecological data.

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In arid countries worldwide, social conflicts between irrigation-based human development and the conservation of aquatic ecosystems are widespread and attract many public debates. This research focuses on the analysis of water and agricultural policies aimed at conserving groundwater resources and maintaining rurallivelihoods in a basin in Spain's central arid region. Intensive groundwater mining for irrigation has caused overexploitation of the basin's large aquifer, the degradation of reputed wetlands and has given rise to notable social conflicts over the years. With the aim of tackling the multifaceted socio-ecological interactions of complex water systems, the methodology used in this study consists in a novel integration into a common platform of an economic optimization model and a hydrology model WEAP (Water Evaluation And Planning system). This robust tool is used to analyze the spatial and temporal effects of different water and agricultural policies under different climate scenarios. It permits the prediction of different climate and policy outcomes across farm types (water stress impacts and adaptation), at basin's level (aquifer recovery), and along the policies’ implementation horizon (short and long run). Results show that the region's current quota-based water policies may contribute to reduce water consumption in the farms but will not be able to recover the aquifer and will inflict income losses to the rural communities. This situation would worsen in case of drought. Economies of scale and technology are evidenced as larger farms with cropping diversification and those equipped with modern irrigation will better adapt to water stress conditions. However, the long-term sustainability of the aquifer and the maintenance of rurallivelihoods will be attained only if additional policy measures are put in place such as the control of illegal abstractions and the establishing of a water bank. Within the policy domain, the research contributes to the new sustainable development strategy of the EU by concluding that, in water-scarce regions, effective integration of water and agricultural policies is essential for achieving the water protection objectives of the EU policies. Therefore, the design and enforcement of well-balanced region-specific polices is a major task faced by policy makers for achieving successful water management that will ensure nature protection and human development at tolerable social costs. From a methodological perspective, this research initiative contributes to better address hydrological questions as well as economic and social issues in complex water and human systems. Its integrated vision provides a valuable illustration to inform water policy and management decisions within contexts of water-related conflicts worldwide.

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Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

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The overall objective of this research project is to enrich geographic data with temporal and semantic components in order to significantly improve spatio-temporal analysis of geographic phenomena. To achieve this goal, we intend to establish and incorporate three new layers (structures) into the core of the Geographic Information by using mark-up languages as well as defining a set of methods and tools for enriching the system to make it able to retrieve and exploit such layers (semantic-temporal, geosemantic, and incremental spatio-temporal). Besides these layers, we also propose a set of models (temporal and spatial) and two semantic engines that make the most of the enriched geographic data. The roots of the project and its definition have been previously presented in Siabato & Manso-Callejo 2011. In this new position paper, we extend such work by delineating clearly the methodology and the foundations on which we will base to define the main components of this research: the spatial model, the temporal model, the semantic layers, and the semantic engines. By putting together the former paper and this new work we try to present a comprehensive description of the whole process, from pinpointing the basic problem to describing and assessing the solution. In this new article we just mention the methods and the background to describe how we intend to define the components and integrate them into the GI.

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CO2 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic CO2 into the atmosphere. CCS technologies are expected to account for the 20% of the CO2 reduction by 2050. Geophysical, ground deformation and geochemical monitoring have been carried out to detect potential leakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline) of the area affected by the CO2 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements. Therefore, the methodological approach is important because it can affect the spatial and temporal variability of this flux and even jeopardize the total value of CO2 in a given area. In this sense, measurements of CO2 flux were done using portable infrared analyzers (i.e., accumulation chambers) adapted to monitoring the geological storage of CO2, and other measurements of trace gases, e.g. radon isotopes and remote sensing imagery were tested in the natural analogue of Campo de Calatrava (Ciudad Real, Spain) with the aim to apply in CO2 leakage detection; thus, observing a high correlation between CO2 and radon (r=0,858) and detecting some vegetation indices that may be successfully applied for the leakage detection.

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Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.