Marriage as women's old age insurance : evidence from migration and land inheritance practices in rural Tanzania

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.

Offshore stereo measurements of gravity waves: classical epipolar and novel variational techniques

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.

Lesson from the habitat suitability models to evaluate the environmental of Pinus nigra Arnold and Pinus sylvesris L. in the Iberian Peninsula

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.

Balancing groundwater conservation and rural livelihoods under water and climate uncertainties: An integrated hydro-economic modeling framework

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.

Using quantitative descriptive analysis and temporal dominance of sensations analysis as complementary methods for profiling commercial blackcurrant squashes

Quantitative descriptive analysis (QDA) is used to describe the nature and the intensity of sensory properties from a single evaluation of a product, whereas temporal dominance of sensation (TDS) is primarily used to identify dominant sensory properties over time. Previous studies with TDS have focused on model systems, but this is the first study to use a sequential approach, i.e. QDA then TDS in measuring sensory properties of a commercial product category, using the same set of trained assessors (n = 11). The main objectives of this study were to: (1) investigate the benefits of using a sequential approach of QDA and TDS and (2) to explore the impact of the sample composition on taste and flavour perceptions in blackcurrant squashes. The present study has proposed an alternative way of determining the choice of attributes for TDS measurement based on data obtained from previous QDA studies, where available. Both methods indicated that the flavour profile was primarily influenced by the level of dilution and complexity of sample composition combined with blackcurrant juice content. In addition, artificial sweeteners were found to modify the quality of sweetness and could also contribute to bitter notes. Using QDA and TDS in tandem was shown to be more beneficial than each just on its own enabling a more complete sensory profile of the products.

Spatial and thematic assessment of object- based forest stands delineation using OFA-matrix

Validación de la cartografía generada del terreno a partir de una nuevo sistema de validación propuesto

Novel parameters for evaluating the Spatial and Thematic accuracy of land cover maps.

Se proponen novedosas fórmulas para evaluar la certeza de la cartografía

Integración de la calidad del aire en la planificación física

En esta tesis se presenta una nueva aproximación para la realización de mapas de calidad del aire, con objeto de que esta variable del medio físico pueda ser tenida en cuenta en los procesos de planificación física o territorial. La calidad del aire no se considera normalmente en estos procesos debido a su composición y a la complejidad de su comportamiento, así como a la dificultad de contar con información fiable y contrastada. Además, la variabilidad espacial y temporal de las medidas de calidad del aire hace que sea difícil su consideración territorial y exige la georeferenciación de la información. Ello implica la predicción de medidas para lugares del territorio donde no existen datos. Esta tesis desarrolla un modelo geoestadístico para la predicción de valores de calidad del aire en un territorio. El modelo propuesto se basa en la interpolación de las medidas de concentración de contaminantes registradas en las estaciones de monitorización, mediante kriging ordinario, previa homogeneización de estos datos para eliminar su carácter local. Con el proceso de eliminación del carácter local, desaparecen las tendencias de las series muestrales de datos debidas a las variaciones temporales y espaciales de la calidad del aire. La transformación de los valores de calidad del aire en cantidades independientes del lugar de muestreo, se realiza a través de parámetros de uso del suelo y de otras variables características de la escala local. Como resultado, se obtienen unos datos de entrada espacialmente homogéneos, que es un requisito fundamental para la utilización de cualquier algoritmo de interpolación, en concreto, del kriging ordinario. Después de la interpolación, se aplica una retransformación de los datos para devolver el carácter local al mapa final. Para el desarrollo del modelo, se ha elegido como área de estudio la Comunidad de Madrid, por la disponibilidad de datos reales. Estos datos, valores de calidad del aire y variables territoriales, se utilizan en dos momentos. Un momento inicial, donde se optimiza la selección de los parámetros más adecuados para la eliminación del carácter local de las medidas y se desarrolla cada una de las etapas del modelo. Y un segundo momento, en el que se aplica en su totalidad el modelo desarrollado y se contrasta su eficacia predictiva. El modelo se aplica para la estimación de los valores medios y máximos de NO2 del territorio de estudio. Con la implementación del modelo propuesto se acomete la territorialización de los datos de calidad del aire con la reducción de tres factores clave para su efectiva integración en la planificación territorial o en el proceso de toma de decisiones asociado: incertidumbre, tiempo empleado para generar la predicción y recursos (datos y costes) asociados. El modelo permite obtener una predicción de valores del contaminante objeto de análisis en unas horas, frente a los periodos de modelización o análisis requeridos por otras metodologías. Los recursos necesarios son mínimos, únicamente contar con los datos de las estaciones de monitorización del territorio que, normalmente, están disponibles en las páginas web viii institucionales de los organismos gestores de las redes de medida de la calidad del aire. Por lo que respecta a las incertidumbres de la predicción, puede decirse que los resultados del modelo propuesto en esta tesis son estadísticamente muy correctos y que los errores medios son, en general, similares o menores que los encontrados con la aplicación de las metodologías existentes. ABSTRACT This thesis presents a new approach for mapping air quality, so that this variable of physical environment can be taken into account in physical or territorial planning. Ambient air quality is not normally considered in territorial planning mainly due to the complexity of its composition and behavior and the difficulty of counting with reliable and contrasted information. In addition, the wide spatial and temporal variability of the measurements of air quality makes his territorial consideration difficult and requires georeferenced information. This involves predicting measurements in the places of the territory where there are no data. This thesis develops a geostatistical model for predicting air quality values in a territory. The proposed model is based on the interpolation of measurements of pollutants from the monitoring stations, using ordinary kriging, after a detrending or removal of the local character of sampling values process. With the detrending process, the local character of the time series of sampling data, due to temporal and spatial variations of air quality, is removed. The transformation of the air quality values into site-independent quantities is performed using land use parameters and other characteristic parameters of local scale. This detrending of the monitoring data process results in a spatial homogeneous input set which is a prerequisite for a correct use of any interpolation algorithm, particularly, ordinary kriging. After the interpolation step, a retrending or retransformation is applied in order to incorporate the local character in the final map at places where no monitoring data is available. For the development of this model, the Community of Madrid is chosen as study area, because of the availability of actual data. These data, air quality values and local parameters, are used in two moments. A starting point, to optimize the selection of the most suitable indicators for the detrending process and to develop each one of the model stages. And a second moment, to fully implement the developed model and to evaluate its predictive power. The model is applied to estimate the average and maximum values of NO2 in the study territory. With the implementation of the proposed model, the territorialization of air quality data is undertaken with the reduction in three key factors for the effective integration of this parameter in territorial planning or in the associated decision making process: uncertainty, time taken to generate the prediction and associated resources (data and costs). This model allows the prediction of pollutant values in hours, compared to the implementation time periods required for other modeling or analysis methodologies. The required resources are also minimal, only having data from monitoring stations in the territory, that are normally available on institutional websites of the authorities responsible for air quality networks control and management. With regard to the prediction uncertainties, it can be concluded that the results of the proposed model are statistically very accurate and the mean errors are generally similar to or lower than those found with the application of existing methodologies.

Gas monitoring methodology and application to CCS projects as defined by atmospheric and remote sensing survey in the natural analogue of Campo de Calatrava

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.

Carbon allocation in north-western Amazon forests (Colombia)

Los estudios sobre la asignación del carbono en los ecosistemas forestales proporcionan información esencial para la comprensión de las diferencias espaciales y temporales en el ciclo del carbono de tal forma que pueden aportar información a los modelos y, así predecir las posibles respuestas de los bosques a los cambios en el clima. Dentro de este contexto, los bosques Amazónicos desempeñan un papel particularmente importante en el balance global del carbono; no obstante, existen grandes incertidumbres en cuanto a los controles abióticos en las tasas de la producción primaria neta (PPN), la asignación de los productos de la fotosíntesis a los diferentes componentes o compartimentos del ecosistema (aéreo y subterráneo) y, cómo estos componentes de la asignación del carbono responden a eventos climáticos extremos. El objetivo general de esta tesis es analizar los componentes de la asignación del carbono en bosques tropicales maduros sobre suelos contrastantes, que crecen bajo condiciones climáticas similares en dos sitios ubicados en la Amazonia noroccidental (Colombia): el Parque Natural Nacional Amacayacu y la Estación Biológica Zafire. Con este objetivo, realicé mediciones de los componentes de la asignación del carbono (biomasa, productividad primaria neta, y su fraccionamiento) a nivel ecosistémico y de la dinámica forestal (tasas anuales de mortalidad y reclutamiento), a lo largo de ocho años (20042012) en seis parcelas permanentes de 1 hectárea establecidas en cinco tipos de bosques sobre suelos diferentes (arcilloso, franco-arcilloso, franco-arcilloso-arenoso, franco-arenoso y arena-francosa). Toda esta información me permitió abordar preguntas específicas que detallo a continuación. En el Capítulo 2 evalúe la hipótesis de que a medida que aumenta la fertilidad del suelo disminuye la cantidad del carbono asignado a la producción subterránea (raíces finas con diámetro <2 mm). Y para esto, realicé mediciones de la masa y la producción de raíces finas usando dos métodos: (1) el de los cilindros de crecimiento y, (2) el de los cilindros de extracción secuencial. El monitoreo se realizó durante 2.2 años en los bosques con suelos más contrastantes: arcilla y arena-francosa. Encontré diferencias significativas en la masa de raíces finas y su producción entre los bosques y, también con respecto a la profundidad del suelo (010 y 1020 cm). El bosque sobre arena-francosa asignó más carbono a las raíces finas que el bosque sobre arcillas. La producción de raíces finas en el bosque sobre arena-francosa fue dos veces más alta (media ± error estándar = 2.98 ± 0.36 y 3.33 ± 0.69 Mg C ha1 año1, con el método 1 y 2, respectivamente), que para el bosque sobre arcillas, el suelo más fértil (1.51 ± 0.14, método 1, y desde 1.03 ± 0.31 a 1.36 ± 0.23 Mg C ha1 año1, método 2). Del mismo modo, el promedio de la masa de raíces finas fue tres veces mayor en el bosque sobre arena-francosa (5.47 ± 0.17 Mg C ha1) que en el suelo más fértil (de 1.52 ± 0.08 a 1.82 ± 0.09 Mg C ha1). La masa de las raíces finas también mostró un patrón temporal relacionado con la lluvia, mostrando que la producción de raíces finas disminuyó sustancialmente en el período seco del año 2005. Estos resultados sugieren que los recursos del suelo pueden desempeñar un papel importante en los patrones de la asignación del carbono entre los componentes aéreo y subterráneo de los bosques tropicales; y que el suelo no sólo influye en las diferencias en la masa de raíces finas y su producción, sino que también, en conjunto con la lluvia, sobre la estacionalidad de la producción. En el Capítulo 3 estimé y analicé los tres componentes de la asignación del carbono a nivel del ecosistema: la biomasa, la productividad primaria neta PPN, y su fraccionamiento, en los mismos bosques del Capítulo 2 (el bosque sobre arcillas y el bosque sobre arena-francosa). Encontré diferencias significativas en los patrones de la asignación del carbono entre los bosques; el bosque sobre arcillas presentó una mayor biomasa total y aérea, así como una PPN, que el bosque sobre arena-francosa. Sin embargo, la diferencia entre los dos bosques en términos de la productividad primaria neta total fue menor en comparación con las diferencias entre la biomasa total de los bosques, como consecuencia de las diferentes estrategias en la asignación del carbono a los componentes aéreo y subterráneo del bosque. La proporción o fracción de la PPN asignada a la nueva producción de follaje fue relativamente similar entre los dos bosques. Nuestros resultados de los incrementos de la biomasa aérea sugieren una posible compensación entre la asignación del carbono al crecimiento de las raíces finas versus el de la madera, a diferencia de la compensación comúnmente asumida entre la parte aérea y la subterránea en general. A pesar de estas diferencias entre los bosques en términos de los componentes de la asignación del carbono, el índice de área foliar fue relativamente similar entre ellos, lo que sugiere que el índice de área foliar es más un indicador de la PPN total que de la asignación de carbono entre componentes. En el Capítulo 4 evalué la variación espacial y temporal de los componentes de la asignación del carbono y la dinámica forestal de cinco tipos e bosques amazónicos y sus respuestas a fluctuaciones en la precipitación, lo cual es completamente relevante en el ciclo global del carbono y los procesos biogeoquímicos en general. Estas variaciones son así mismo importantes para evaluar los efectos de la sequía o eventos extremos sobre la dinámica natural de los bosques amazónicos. Evalué la variación interanual y la estacionalidad de los componentes de la asignación del carbono y la dinámica forestal durante el periodo 2004−2012, en cinco bosques maduros sobre diferentes suelos (arcilloso, franco-arcilloso, franco-arcilloso-arenoso, franco-arenoso y arena-francosa), todos bajo el mismo régimen local de precipitación en la Amazonia noroccidental (Colombia). Quería examinar sí estos bosques responden de forma similar a las fluctuaciones en la precipitación, tal y como pronostican muchos modelos. Consideré las siguientes preguntas: (i) ¿Existe una correlación entre los componentes de la asignación del carbono y la dinámica forestal con la precipitación? (ii) ¿Existe correlación entre los bosques? (iii) ¿Es el índice de área foliar (LAI) un indicador de las variaciones en la producción aérea o es un reflejo de los cambios en los patrones de la asignación del carbono entre bosques?. En general, la correlación entre los componentes aéreo y subterráneo de la asignación del carbono con la precipitación sugiere que los suelos juegan un papel importante en las diferencias espaciales y temporales de las respuestas de estos bosques a las variaciones en la precipitación. Por un lado, la mayoría de los bosques mostraron que los componentes aéreos de la asignación del carbono son susceptibles a las fluctuaciones en la precipitación; sin embargo, el bosque sobre arena-francosa solamente presentó correlación con la lluvia con el componente subterráneo (raíces finas). Por otra parte, a pesar de que el noroeste Amazónico es considerado sin una estación seca propiamente (definida como <100 mm meses −1), la hojarasca y la masa de raíces finas mostraron una alta variabilidad y estacionalidad, especialmente marcada durante la sequía del 2005. Además, los bosques del grupo de suelos francos mostraron que la hojarasca responde a retrasos en la precipitación, al igual que la masa de raíces finas del bosque sobre arena-francosa. En cuanto a la dinámica forestal, sólo la tasa de mortalidad del bosque sobre arena-francosa estuvo correlacionada con la precipitación (ρ = 0.77, P <0.1). La variabilidad interanual en los incrementos en el tallo y la biomasa de los individuos resalta la importancia de la mortalidad en la variación de los incrementos en la biomasa aérea. Sin embargo, las tasas de mortalidad y las proporciones de individuos muertos por categoría de muerte (en pie, caído de raíz, partido y desaparecido), no mostraron tendencias claras relacionadas con la sequía. Curiosamente, la hojarasca, el incremento en la biomasa aérea y las tasas de reclutamiento mostraron una alta correlación entre los bosques, en particular dentro del grupo de los bosques con suelos francos. Sin embargo, el índice de área foliar estimado para los bosques con suelos más contrastantes (arcilla y arena-francosa), no presentó correlación significativa con la lluvia; no obstante, estuvo muy correlacionado entre bosques; índice de área foliar no reflejó las diferencias en la asignación de los componentes del carbono, y su respuesta a la precipitación en estos bosques. Por último, los bosques estudiados muestran que el noroeste amazónico es susceptible a fenómenos climáticos, contrario a lo propuesto anteriormente debido a la ausencia de una estación seca propiamente dicha. ABSTRACT Studies of carbon allocation in forests provide essential information for understanding spatial and temporal differences in carbon cycling that can inform models and predict possible responses to changes in climate. Amazon forests play a particularly significant role in the global carbon balance, but there are still large uncertainties regarding abiotic controls on the rates of net primary production (NPP) and the allocation of photosynthetic products to different ecosystem components; and how the carbon allocation components of Amazon forests respond to extreme climate events. The overall objective of this thesis is to examine the carbon allocation components in old-growth tropical forests on contrasting soils, and under similar climatic conditions in two sites at the Amacayacu National Natural Park and the Zafire Biological Station, located in the north-western Amazon (Colombia). Measurements of above- and below-ground carbon allocation components (biomass, net primary production, and its partitioning) at the ecosystem level, and dynamics of tree mortality and recruitment were done along eight years (20042012) in six 1-ha plots established in five Amazon forest types on different soils (clay, clay-loam, sandy-clay-loam, sandy-loam and loamy-sand) to address specific questions detailed in the next paragraphs. In Chapter 2, I evaluated the hypothesis that as soil fertility increases the amount of carbon allocated to below-ground production (fine-roots) should decrease. To address this hypothesis the standing crop mass and production of fine-roots (<2 mm) were estimated by two methods: (1) ingrowth cores and, (2) sequential soil coring, during 2.2 years in the most contrasting forests: the clay-soil forest and the loamy-sand forest. We found that the standing crop fine-root mass and its production were significantly different between forests and also between soil depths (0–10 and 10–20 cm). The loamysand forest allocated more carbon to fine-roots than the clay-soil forest, with fine-root production in the loamy-sand forest twice (mean ± standard error = 2.98 ± 0.36 and 3.33 ± 0.69 Mg C ha −1 yr −1, method 1 and 2, respectively) as much as for the more fertile claysoil forest (1.51 ± 0.14, method 1, and from 1.03 ± 0.31 to 1.36 ± 0.23 Mg C ha −1 yr −1, method 2). Similarly, the average of standing crop fine-root mass was three times higher in the loamy-sand forest (5.47 ± 0.17 Mg C ha1) than in the more fertile soil (from 1.52 ± 0.08 a 1.82 ± 0.09 Mg C ha1). The standing crop fine-root mass also showed a temporal pattern related to rainfall, with the production of fine-roots decreasing substantially in the dry period of the year 2005. These results suggest that soil resources may play an important role in patterns of carbon allocation of below-ground components, not only driven the differences in the biomass and its production, but also in the time when it is produced. In Chapter 3, I assessed the three components of stand-level carbon allocation (biomass, NPP, and its partitioning) for the same forests evaluated in Chapter 2 (clay-soil forest and loamy-sand forest). We found differences in carbon allocation patterns between these two forests, showing that the forest on clay-soil had a higher aboveground and total biomass as well as a higher above-ground NPP than the loamy-sand forest. However, differences between the two types of forests in terms of stand-level NPP were smaller, as a consequence of different strategies in the carbon allocation of above- and below-ground components. The proportional allocation of NPP to new foliage production was relatively similar between the two forests. Our results of aboveground biomass increments and fine-root production suggest a possible trade-off between carbon allocation to fine-roots versus wood growth (as it has been reported by other authors), as opposed to the most commonly assumed trade-off between total above- and below-ground production. Despite these differences among forests in terms of carbon allocation components, the leaf area index showed differences between forests like total NPP, suggesting that the leaf area index is more indicative of total NPP than carbon allocation. In Chapter 4, I evaluated the spatial and temporal variation of carbon allocation components and forest dynamics of Amazon forests as well as their responses to climatic fluctuations. I evaluated the intra- and inter-annual variation of carbon allocation components and forest dynamics during the period 2004−2012 in five forests on different soils (clay, clay-loam, sandy-clay-loam, sandy-loam and loamy-sand), but growing under the same local precipitation regime in north-western Amazonia (Colombia). We were interested in examining if these forests respond similarly to rainfall fluctuations as many models predict, considering the following questions: (i) Is there a correlation in carbon allocation components and forest dynamics with precipitation? (ii) Is there a correlation among forests? (iii) Are temporal responses in leaf area index (LAI) indicative of variations of above-ground production or a reflection of changes in carbon allocation patterns among forests?. Overall, the correlation of above- and below-ground carbon allocation components with rainfall suggests that soils play an important role in the spatial and temporal differences of responses of these forests to rainfall fluctuations. On the one hand, most forests showed that the above-ground components are susceptible to rainfall fluctuations; however, there was a forest on loamy-sand that only showed a correlation with the below-ground component (fine-roots). On the other hand, despite the fact that north-western Amazonia is considered without a conspicuous dry season (defined as <100 mm month−1), litterfall and fine-root mass showed high seasonality and variability, particularly marked during the drought of 2005. Additionally, forests of the loam-soil group showed that litterfall respond to time-lags in rainfall as well as and the fine-root mass of the loamy-sand forest. With regard to forest dynamics, only the mortality rate of the loamy-sand forest was significantly correlated with rainfall (77%). The observed inter-annual variability of stem and biomass increments of individuals highlighted the importance of the mortality in the above-ground biomass increment. However, mortality rates and death type proportion did not show clear trends related to droughts. Interestingly, litterfall, above-ground biomass increment and recruitment rates of forests showed high correlation among forests, particularly within the loam-soil forests group. Nonetheless, LAI measured in the most contrasting forests (clay-soil and loamysand) was poorly correlated with rainfall but highly correlated between forests; LAI did not reflect the differences in the carbon allocation components, and their response to rainfall on these forests. Finally, the forests studied highlight that north-western Amazon forests are also susceptible to climate fluctuations, contrary to what has been proposed previously due to their lack of a pronounced dry season.

Offshore remote sensing of the ocean by stereo vision systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss future lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

MIA - a free and open source software for gray scale medical image analysis

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

Space-time ocean wave measurement using variational stereo vision systems

Remote sensing imaging systems for the measurement of oceanic sea states have recently attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss the improvement of their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters.

Efficient spatio-temporal hole filling strategy for Kinect depth maps

In this paper we present an efficient hole filling strategy that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach is based on a joint-bilateral filtering framework that includes spatial and temporal information. The missing depth values are obtained applying iteratively a joint-bilateral filter to their neighbor pixels. The filter weights are selected considering three different factors: visual data, depth information and a temporal-consistency map. Video and depth data are combined to improve depth map quality in presence of edges and homogeneous regions. Finally, the temporal-consistency map is generated in order to track the reliability of the depth measurements near the hole regions. The obtained depth values are included iteratively in the filtering process of the successive frames and the accuracy of the hole regions depth values increases while new samples are acquired and filtered

Generating descriptions that summarize geospatial and temporal data

Effective data summarization methods that use AI techniques can help humans understand large sets of data. In this paper, we describe a knowledge-based method for automatically generating summaries of geospatial and temporal data, i.e. data with geographical and temporal references. The method is useful for summarizing data streams, such as GPS traces and traffic information, that are becoming more prevalent with the increasing use of sensors in computing devices. The method presented here is an initial architecture for our ongoing research in this domain. In this paper we describe the data representations we have designed for our method, our implementations of components to perform data abstraction and natural language generation. We also discuss evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.