16 resultados para Spatial scale

em Universidad Politécnica de Madrid


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Emission inventories are databases that aim to describe the polluting activities that occur across a certain geographic domain. According to the spatial scale, the availability of information will vary as well as the applied assumptions, which will strongly influence its quality, accuracy and representativeness. This study compared and contrasted two emission inventories describing the Greater Madrid Region (GMR) under an air quality simulation approach. The chosen inventories were the National Emissions Inventory (NEI) and the Regional Emissions Inventory of the Greater Madrid Region (REI). Both of them were used to feed air quality simulations with the CMAQ modelling system, and the results were compared with observations from the air quality monitoring network in the modelled domain. Through the application of statistical tools, the analysis of emissions at cell level and cell – expansion procedures, it was observed that the National Inventory showed better results for describing on – road traffic activities and agriculture, SNAP07 and SNAP10. The accurate description of activities, the good characterization of the vehicle fleet and the correct use of traffic emission factors were the main causes of such a good correlation. On the other hand, the Regional Inventory showed better descriptions for non – industrial combustion (SNAP02) and industrial activities (SNAP03). It incorporated realistic emission factors, a reasonable fuel mix and it drew upon local information sources to describe these activities, while NEI relied on surrogation and national datasets which leaded to a poorer representation. Off – road transportation (SNAP08) was similarly described by both inventories, while the rest of the SNAP activities showed a marginal contribution to the overall emissions.

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A study supported by the European Space Agency (ESA), in the context of its General Studies Programme, performed an investigation of the possible use of space for studies in pure and applied plasma physics, in areas not traditionally covered by ‘space plasma physics’. A set of experiments have been identified that can potentially provide access to new phenomena and to allow advances in several fields of plasma science. These experiments concern phenomena on a spatial scale (101–104 m) intermediate between what is achievable on the ground and the usual solar system plasma observations. Detailed feasibility studies have been performed for three experiments: active magnetic experiments, largescale discharges and long tether–plasma interactions. The perspectives opened by these experiments are discussed for magnetic reconnection, instabilities, MHD turbulence, atomic excited states kinetics, weakly ionized plasmas,plasma diagnostics, artificial auroras and atmospheric studies. The discussion is also supported by results of numerical simulations and estimates.

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The European Space Agency has initiated, in the context of its General Studies Programme, a study of the possible use of space for studies in pure and applied plasma physics, in areas not traditionally covered by “space plasma physics”. A team of experts has been set-up to review a broad range of area including industrial plasma physics and pure plasma physics, astrophysical and solar-terrestrial areas. A set of experiments have been identified that can potentially provide access to new phenomena and to allow advances in several fields of plasma science. These experiments concern phenomena on spatial scale (102 to104 m) intermediate between what is achievable on ground experiment and usual solar system plasma observations.

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1. The spatial distribution of individual plants within a population and the population’s genetic structure are determined by several factors, like dispersal, reproduction mode or biotic interactions. The role of interspecific interactions in shaping the spatial genetic structure of plant populations remains largely unknown. 2. Species with a common evolutionary history are known to interact more closely with each other than unrelated species due to the greater number of traits they share. We hypothesize that plant interactions may shape the fine genetic structure of closely related congeners. 3. We used spatial statistics (georeferenced design) and molecular techniques (ISSR markers) to understand how two closely related congeners, Thymus vulgaris (widespread species) and T. loscosii (narrow endemic) interact at the local scale. Specific cover, number of individuals of both study species and several community attributes were measured in a 10 × 10 m plot. 4. Both species showed similar levels of genetic variation, but differed in their spatial genetic structure. Thymus vulgaris showed spatial aggregation but no spatial genetic structure, while T. loscosii showed spatial genetic structure (positive genetic autocorrelation) at short distances. The spatial pattern of T. vulgaris’ cover showed significant dissociation with that of T. loscosii. The same was true between the spatial patterns of the cover of T. vulgaris and the abundance of T. loscosii and between the abundance of each species. Most importantly, we found a correlation between the genetic structure of T. loscosii and the abundance of T. vulgaris: T. loscosii plants were genetically more similar when they were surrounded by a similar number of T. vulgaris plants. 5. Synthesis. Our results reveal spatially complex genetic structures of both congeners at small spatial scales. The negative association among the spatial patterns of the two species and the genetic structure found for T. loscosii in relation to the abundance of T. vulgaris indicate that competition between the two species may account for the presence of adapted ecotypes of T. loscosii to the abundance of a competing congeneric species. This suggests that the presence and abundance of close congeners can influence the genetic spatial structure of plant species at fine scales.

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Spatial variability of Vertisol properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns. The objectives of the present work were (i) to quantify the spatial structure of different physical properties collected from a Vertisol, (ii) to search for potential correlations between different spatial patterns and (iii) to identify relevant components through multivariate spatial analysis. The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years. We used six soil properties collected from a squared grid (225 points) (penetrometer resistance (PR), total porosity, fragmentation dimension (Df), vertical electrical conductivity (ECv), horizontal electrical conductivity (ECh) and soil water content (WC)). All the original data sets were z-transformed before geostatistical analysis. Three different types of semivariogram models were necessary for fitting individual experimental semivariograms. This suggests the different natures of spatial variability patterns. Soil water content rendered the largest nugget effect (C0 = 0.933) while soil total porosity showed the largest range of spatial correlation (A = 43.92 m). The bivariate geostatistical analysis also rendered significant cross-semivariance between different paired soil properties. However, four different semivariogram models were required in that case. This indicates an underlying co-regionalization between different soil properties, which is of interest for delineating management zones within sugarcane fields. Cross-semivariograms showed larger correlation ranges than individual, univariate, semivariograms (A ≥ 29 m). All the findings were supported by multivariate spatial analysis, which showed the influence of soil tillage operations, harvesting machinery and irrigation water distribution on the status of the investigated area.

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The Fractal Image Informatics toolbox (Oleschko et al., 2008 a; Torres-Argüelles et al., 2010) was applied to extract, classify and model the topological structure and dynamics of surface roughness in two highly eroded catchments of Mexico. Both areas are affected by gully erosion (Sidorchuk, 2005) and characterized by avalanche-like matter transport. Five contrasting morphological patterns were distinguished across the slope of the bare eroded surface of Faeozem (Queretaro State) while only one (apparently independent on the slope) roughness pattern was documented for Andosol (Michoacan State). We called these patterns ?the roughness clusters? and compared them in terms of metrizability, continuity, compactness, topological connectedness (global and local) and invariance, separability, and degree of ramification (Weyl, 1937). All mentioned topological measurands were correlated with the variance, skewness and kurtosis of the gray-level distribution of digital images. The morphology0 spatial dynamics of roughness clusters was measured and mapped with high precision in terms of fractal descriptors. The Hurst exponent was especially suitable to distinguish between the structure of ?turtle shell? and ?ramification? patterns (sediment producing zone A of the slope); as well as ?honeycomb? (sediment transport zone B) and ?dinosaur steps? and ?corals? (sediment deposition zone C) roughness clusters. Some other structural attributes of studied patterns were also statistically different and correlated with the variance, skewness and kurtosis of gray distribution of multiscale digital images. The scale invariance of classified roughness patterns was documented inside the range of five image resolutions. We conjectured that the geometrization of erosion patterns in terms of roughness clustering might benefit the most semi-quantitative models developed for erosion and sediment yield assessments (de Vente and Poesen, 2005).

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Abstract The cloud forest is a special type of forest ecosystem that depends on suitable conditions of humidity and temperature to exist; hence, it is a very fragile ecosystem. The cloud forest is also one of the richest ecosystems in terms of species diversity and rate of endemism. However, today, it is one of the most threatened ecosystems in the world. Little is known about tree species distribution and coexistence among cloud forest trees. Trees are essential to understanding ecosystem functioning and maintenance because they support the ecosystem in important ways. For this dissertation, an analysis of woody plant species distribution at a small scale in a north-Peruvian Andean cloud forest was performed, and some of the factors implicated in the observed patterns were identified. Towards that end, different natural factors acting on species distribution within the forest were investigated: (i) intra-specific arrangements, (ii) heterospecific spatial relationships and (iii) relationships with external environmental factors. These analyses were conducted first on standing woody plants and then on seedlings. The woody plants were found to be clumped in the forest, either considering all the species together or each species separately. However, each species presented a specific pattern and specific spatial relationship among different-age individuals. Dispersal mode, growth form and shade tolerance played roles in the final distribution of the species. Furthermore, spatial associations among species, either positive or negative, were observed. These associations were more numerous when considering individuals of the interacting species at different developmental stages, i.e., younger individuals from one species and older individuals from another. Accordingly, competition and facilitation are asymmetric processes and vary throughout the life of an individual. Moreover, some species appear to prefer certain habitat conditions and avoid other habitats. The habitat definition that best explains species distribution is that which includes both environmental and stand characteristics; thus, a combination of these factors is necessary to understanding species' niche preferences. Seedling distribution was also associated with habitat conditions, but these conditions explained less than the 30% of the spatial variation. The position of conspecific adult individuals also affected seedling distribution; although the seedlings of many tree species avoid the vicinity of conspecifics, a few species appeared to prefer the formation of cohorts around their parent trees. The importance of habitat conditions and distance dependence with conspecifics varied among regions within the forest as well as on the developmental stage of the stand. The results from this thesis suggest that different species can coexist within a given space, forming a “puzzle” of species as a result of the intra- and interspecific spatial relationships along with niche preferences and adaptations that operate at different scales. These factors not only affect each species in a different way, but specific preferences also vary throughout species' lifespans. Resumen Resumen El bosque de niebla es uno de los ecosistemas más amenazados del mundo además de ser uno de los más frágiles. Son formaciones azonales que dependen de la existencia de unas condiciones de humedad y temperatura que permitan la formación de nubes que cubran el bosque; lo que dificulta en gran medida su conservación. También es uno de los ecosistemas con mayor riqueza de especies además de tener uno de los mayores porcentajes de endemismos. Uno de los aspectos más importantes para entender el ecosistema, es identificar y entender los elementos que lo componen y los mecanismos que regulan las relaciones entre ellos. Los árboles son el soporte del ecosistema. Sin embargo, apenas hay información sobre la distribución y coexistencia de los árboles en los bosques de niebla. Esta tesis presenta un análisis de la distribución a pequeña escala de las plantas leñosas en un bosque de niebla situado en la cordillera andina del norte de Perú; así como el análisis de algunos de los factores que pueden estar implicados en que se origine la distribución observada. Para este propósito se estudia cómo influyen factores de diferente naturaleza en la distribución de las especies (i) organización intra-específica (ii) relaciones espaciales heterospecíficas y (iii) relación con factores ambientales externos. En estos análisis se estudiaron primero las plantas jóvenes y las adultas, y después las plántulas. Los árboles aparecieron agregados en el bosque, tanto considerando todos a la vez como cuando se estudió cada especie por separado. Sin embargo, cada especie mostró un patrón distinto así como una particular relación espacial entre individuos jóvenes y adultos. El modo de dispersión, la forma de vida y la tolerancia de la especies estuvieron relacionados con el patrón general observado. Se vio también que ciertas especies aparecían relacionadas con otras, tanto de forma positiva (compartiendo zonas) como negativa (apareciendo en áreas distintas). Las asociaciones fueron mucho más numerosas cuando se consideraron los pares de especies en diferente estado de desarrollo, es decir, individuos jóvenes de una especie e individuos mayores de la otra. Eso indicaría que los procesos de competencia y facilitación son asimétricos y además varían durante la vida de la planta. Por otro lado, algunas especies aparecen preferentemente bajo ciertas condiciones de hábitat y evitan otras. La definición de hábitat a la que mejor responden las especies es cuando se incluyen tanto variables ambientales como de masa; así que ambos tipos de variables son necesarias para entender la preferencia de las especies por ciertos nichos. La distribución de las plántulas también estuvo relacionada con condiciones de hábitat, pero eso sólo llegaba a explicar hasta un 30% de la variabilidad espacial. La posición de los adultos de la misma especie también afectó a la distribución de las plántulas. En bastantes especies las plántulas evitan la cercanía de adultos de su misma especie, padres potenciales, aunque algunas especies aisladas mostraron el patrón contrario y aparecieron preferentemente en las mismas áreas que sus padres. La importancia de las condiciones de hábitat y posición de los adultos en la disposición de las plántulas varía de una zona a otra del bosque y además también varía según el estado de desarrollo de la masa.

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A comprehensive assessment of nitrogen (N) flows at the landscape scale is fundamental to understand spatial interactions in the N cascade and to inform the development of locally optimised N management strategies. To explore these interactions, complete N budgets were estimated for two contrasting hydrological catchments (dominated by agricultural grassland vs. semi-natural peat-dominated moorland), forming part of an intensively studied landscape in southern Scotland. Local scale atmospheric dispersion modelling and detailed farm and field inventories provided high resolution estimations of input fluxes. Direct agricultural inputs (i.e. grazing excreta, N2 fixation, organic and synthetic fertiliser) accounted for most of the catchment N inputs, representing 82% in the grassland and 62% in the moorland catchment, while atmospheric deposition made a significant contribution, particularly in the moorland catchment, contributing 38% of the N inputs. The estimated catchment N budgets highlighted areas of key uncertainty, particularly N2 exchange and stream N export. The resulting N balances suggest that the study catchments have a limited capacity to store N within soils, vegetation and groundwater. The "catchment N retention", i.e. the amount of N which is either stored within the catchment or lost through atmospheric emissions, was estimated to be 13% of the net anthropogenic input in the moorland and 61% in the grassland catchment. These values contrast with regional scale estimates: Catchment retentions of net anthropogenic input estimated within Europe at the regional scale range from 50% to 90%, with an average of 82% (Billen et al., 2011). This study emphasises the need for detailed budget analyses to identify the N status of European landscapes.

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We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

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Lacunarity as a means of quantifying textural properties of spatial distributions suggests a classification into three main classes of the most abundant soils that cover 92% of Europe. Soils with a well-defined self-similar structure of the linear class are related to widespread spatial patterns that are nondominant but ubiquitous at continental scale. Fractal techniques have been increasingly and successfully applied to identify and describe spatial patterns in natural sciences. However, objects with the same fractal dimension can show very different optical properties because of their spatial arrangement. This work focuses primary attention on the geometrical structure of the geographical patterns of soils in Europe. We made use of the European Soil Database to estimate lacunarity indexes of the most abundant soils that cover 92% of the surface of Europe and investigated textural properties of their spatial distribution. We observed three main classes corresponding to three different patterns that displayed the graphs of lacunarity functions, that is, linear, convex, and mixed. They correspond respectively to homogeneous or self-similar, heterogeneous or clustered and those in which behavior can change at different ranges of scales. Finally, we discuss the pedological implications of that classification.

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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.

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Aims of study: The goals of this paper are to summarize and to compare plant species richness and floristic similarity at two spatial scales; mesohabitat (normal, eutrophic, and oligotrophic dehesas) and dehesa habitat; and to establish guidelines for conserving species diversity in dehesas. Area of study: We considered four dehesa sites in the western Peninsular Spain, located along a climatic and biogeographic gradient from north to south. Main results: Average alpha richness for mesohabitats was 75.6 species, and average alpha richness for dehesa sites was 146.3. Gamma richness assessed for the overall dehesa habitat was 340.0 species. The species richness figures of normal dehesa mesohabitat were significantly lesser than of the eutrophic mesohabitat and lesser than the oligotrophic mesohabitat too. No significant differences were found for species richness among dehesa sites. We have found more dissimilarity at local scale (mesohabitat) than at regional scale (habitat). Finally, the results of the similarity assessment between dehesa sites reflected both climatic and biogeographic gradients. Research highlights: An effective conservation of dehesas must take into account local and regional conditions all along their distribution range for ensuring the conservation of the main vascular plant species assemblages as well as the associated fauna

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Spatial planning & energy. Young planners workshop. Final reports - conclusions

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This paper gives an overview of three recent studies by the authors on the topic of 3D video Quality of Experience (QoE). Two of studies [1,2] investigated different psychological dimension that may be needed for describing 3D video QoE and the third the visibility and annoyance of crosstalk[3]. The results shows that the video quality scale could be sufficient for evaluating S3D video experience for coding and spatial resolution reduction distortions. It was also confirmed that with a more complex mixture of degradations more than one scale should be used to capture the QoE in these cases. The study found a linear relationship between the perceived crosstalk and the amount of crosstalk.

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• Premise of the study: The presence of compatible fungi is necessary for epiphytic orchid recruitment. Thus, identifying associated mycorrhizal fungi at the population level is essential for orchid conservation. Recruitment patterns may also be conditioned by factors such as seed dispersal range and specific environmental characteristics. • Methods: In a forest plot, all trees with a diameter at breast height >1 cm and all individuals of the epiphytic orchid Epidendrum rhopalostele were identified and mapped. Additionally, one flowering individual of E. rhopalostele per each host tree was randomly selected for root sampling and DNA extraction. • Key results: A total of 239 E. rhopalostele individuals were located in 25 of the 714 potential host trees. Light microscopy of sampled roots showed mycorrhizal fungi in 22 of the 25 sampled orchids. Phylogenetic analysis of ITS1-5.8S-ITS2 sequences yielded two Tulasnella clades. In four cases, plants were found to be associated with both clades. The difference between univariate and bivariate K functions was consistent with the random labeling null model at all spatial scales, indicating that trees hosting clades A and B of Tulasnella are not spatially segregated. The analysis of the inhomogenous K function showed that host trees are not clustered, suggesting no limitations to population-scale dispersal. χ2 analysis of contingency tables showed that E. rhopalostele is more frequent on dead trees than expected. • Conclusions: Epidendrum rhopalostele establishes mycorrhizal associations with at least two different Tulasnella species. The analysis of the distribution patterns of this orchid suggests a microsite preference for dead trees and no seed dispersal limitation.