Assessment of expected damage on buildings subjected to Lorca earthquake through an energy-based seismic index method and nonlinear dynamic response analyses

The city of Lorca (Spain) was hit on May 11th, 2011, by two consecutive earth-quakes of magnitudes 4.6 and 5.2 Mw, causing casualties and important damage in buildings. Many of the damaged structures were reinforced concrete frames with wide beams. This study quantifies the expected level of damage on this structural type in the case of the Lorca earth-quake by means of a seismic index Iv that compares the energy input by the earthquake with the energy absorption/dissipation capacity of the structure. The prototype frames investigated represent structures designed in two time periods (1994–2002 and 2003–2008), in which the applicable codes were different. The influence of the masonry infill walls and the proneness of the frames to concentrate damage in a given story were further investigated through nonlinear dynamic response analyses. It is found that (1) the seismic index method predicts levels of damage that range from moderate/severe to complete collapse; this prediction is consistent with the observed damage; (2) the presence of masonry infill walls makes the structure very prone to damage concentration and reduces the overall seismic capacity of the building; and (3) a proper hierarchy of strength between beams and columns that guarantees the formation of a strong column-weak beam mechanism (as prescribed by seismic codes), as well as the adoption of counter-measures to avoid the negative interaction between non-structural infill walls and the main frame, would have reduced the level of damage from Iv=1 (collapse) to about Iv=0.5 (moderate/severe damage)

Cartografía de QTL asociados a la tolerancia a estrés hídrico en frijol común (Phaseolus vulgaris L.)

Phaseolus vulgaris L. (frijol común o judía) es una leguminosa de gran demanda para la nutrición humana y un producto agrícola muy importante. Sin embargo, la producción de frijol se ve limitada por presiones ambientales como la sequía. En México, el 85% de la cosecha de frijol se produce en la temporada de primavera-verano, principalmente en las regiones del altiplano semiárido con una precipitación anual entre 250 y 400 mm. A pesar del implemento de tecnología en el campo, los factores naturales impiden al agricultor llegar a los rendimientos deseados. El Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), como instituto de investigación gubernamental en México, tiene como objetivo la mejora de cultivos estratégicos, uno de ellos, P. vulgaris. Los estudios en relación a la sequía se enfocan especialmente en la selección de genotipos tolerantes, los cuales son sometidos en condiciones de estrés y monitoreando parámetros como el rendimiento y peso de semilla, además de algunos indicadores tales como índice de cosecha. El resultado de estos trabajos ha sido la obtención de variedades con mayor tolerancia a la sequía, tales como Pinto Villa y Pinto Saltillo. En los últimos años se ha avanzado notablemente en el conocimiento de las bases moleculares en las respuestas de las plantas al estrés. De acuerdo a diversos estudios se ha demostrado que las plantas bajo estrés por sequía experimentan cambios en la expresión de genes involucrados en la señalización, regulación de la transcripción y la traducción, transporte de agua y la función directa en la protección celular. También se ha observado que el déficit de agua es causado por las temperaturas extremas y la alta concentración de sales, por lo que al nivel molecular, las respuestas al estrés tienen puntos de especificidad y puntos de entrecruzamiento. La sequía puede generar estreses secundarios, tales como el nutricional, oxidativo y osmótico. Sin embargo, es necesario identificar y caracterizar muchos de los componentes involucrados en las respuestas al déficit hídrico, la caracterización de estos genes permitirá tener una mejor comprensión de los mecanismos bioquímicos y fisiológicos involucrados en la tolerancia al estrés. Actualmente, con el apoyo de la biología molecular se han identificado algunos genes que otorgan ventajas para la adaptación a ambientes desfavorables. Por lo que el objetivo del presente trabajo es identificar marcadores genéticos asociados a rasgos fenotípicos con énfasis a la tolerancia a estrés hídrico en P. vulgaris. Una vez establecidos los marcadores asociados al estrés hídrico, es factible considerar su uso para la selección asistida por marcadores en líneas o variedades de frijol de interés para los mejoradores. Se evaluaron 282 familias F3:5 derivadas de la cruza entre los cultivares Pinto Villa y Pinto Saltillo. Las familias se sembraron bajo un diseño simple de látice 17x17, el experimento se llevo acabo en el ciclo primavera-verano del 2010 y 2011, y otoñoinvierno de 2010 en el Campo Experimental Bajío del INIFAP con dos repeticiones para cada tratamiento de humedad (riego completo y sequía terminal). En todos los genotipos se realizó el fenotipado (variables fenotípicas) y el genotipado a través de marcadores moleculares. Los análisis estadísticos se basaron en el análisis de componentes principales (Eigen Analysis Selection Index Method, ESIM), la asociación entre marcadores SNP y el fenotipado (paquete SNPassoc para R) y el análisis de varianza (ANOVA). Los valores ESIM mostraron que las variables de Rendimiento, Días a floración, Días a madurez fisiológica e Índice de cosecha fueron sobresalientes en sequía terminal, por lo que se sugieren tomarse en consideración para los estudios de sequía en P. vulgaris como monitores de evaluación a la resistencia. Se identificaron nueve familias sobresalieron por sus valores ESIM (PV/PS6, 22, 131, 137, 149, 154, 201, 236 y 273), además de presentar valores superiores para el rendimiento en comparación con los parentales. Estos genotipos son candidatos interesantes para realizar estudios de identificación de loci asociados con la respuesta al estrés, y como potenciales parentales en el desarrollo de nuevas variedades de frijol. En los análisis de asociación SNPassoc se identificaron 83 SNPs significativos (p<0,0003) asociados a los rasgos fenotípicos, obteniendo un total de 222 asociaciones, de las cuales predomina el modelo genético de codominancia para las variables Días a floración, Periodo reproductivo y Biomasa total. Treinta y siete SNPs se identificaron a diferentes funciones biológicas a través del análisis de anotación funcional, de los cuales 12 SNPs (9, 18, 28, 39, 61, 69, 80, 106, 115, 128, 136 y 142) sobresalen por su asociación al fenotipado, y cuya anotación funcional indica que se encuentran en genes relacionados a la tolerancia a la sequía, tales como la actividad kinasa, actividad metabólica del almidón, carbohidratos y prolina, respuesta al estrés oxidativo, así como en los genes LEA y posibles factores de transcripción. En el caso de los análisis ANOVA, se identificaron 72 asociaciones entre los SNPs y las variables fenotípicas (F< 3,94E-04). Las 72 asociaciones corresponden a 30 SNPs y 7 variables fenotípicas, de las que predomina Peso de 100 semillas y Periodo reproductivo. Para los rasgos de Rendimiento, Índice de cosecha y Días a madurez fisiológica se presentaron asociaciones con seis SNPs (17, 34, 37, 50, 93 y 107), de los cuales, a los SNP37 y SNP107 fueron identificados a la anotación biológica de protein binding. Por otro lado, los SNP106 y SNP128 asociados al Periodo reproductivo, son genes con actividad kinasa y actividad metabólica del almidón, respectivamente. Para los marcadores tipo AFLP, se identificaron 271 asociaciones (F<2,34E-04). Las asociaciones corresponden a 86 AFLPs con todas las variables fenotípicas evaluadas, de las que predomina peso de 100 semillas, Días a floración y Periodo reproductivo. Debido a que los en los AFLPs no es posible determinar su anotación biológica, se proponen como marcadores potenciales relacionados a la resistencia a la sequía en frijol. Los AFLPs candidatos requieren más estudios tales como la secuenciación de los alelos respectivos, así como la identificación de éstas secuencias en el genoma de referencia y su anotación biológica, entre otros análisis, de esta manera podríamos establecer aquellos marcadores candidatos a la validación para la selección asistida. El presente trabajo propone tanto genotipos como marcadores genéticos, que deben ser validados para ser utilizados en el programa de mejoramiento de P. vulgaris, con el objetivo de desarrollar nuevas líneas o variedades tolerantes a la sequía. ABSTRACT Phaseolus vulgaris L. (common bean or judia) is a legume of great demand for human consumption and an important agricultural product. However, the common bean production is limited by environmental stresses, such as drought. In Mexico, 85% of the common bean crop is produced in the spring-summer season mainly in semiarid highland regions with a rainfall between 250 and 400 mm per year. In spite of the improvement of crop technology, the natural factors hamper getting an optimal yield. The National Institute for Forestry, Agriculture and Livestock (INIFAP) is a government research institute from Mexico, whose main objective is the genetic breeding of strategic crops, like P. vulgaris L. The drought tolerance studies particularly focus on the selection of bean tolerant genotypes, which are subjected to stress conditions, by means of monitoring parameters such as yield and seed weight, plus some agronomic indicators such as harvest index. The results of these works have led to obtain cultivars with higher drought tolerance such as Pinto Villa and Pinto Saltillo. Significant achievements have been recently made in understanding the molecular basis of stress plant responses. Several studies have shown that plants under drought stress present changes in gene expression related to cell signalling, transcriptional and translational regulation, water transport and cell protection. In addition, it has been observed that the extreme temperatures and high salt concentrations can cause a water deficiency so, at the molecular level, stress responses have specific and crossover points. The drought can cause secondary stresses, such as nutritional, oxidative and osmotic stress. It is required the identification of more components involved in the response to water deficit, the characterization of these genes will allow a better understanding of the biochemical and physiological mechanisms involved in stress tolerance. Currently, with the support of molecular biology techniques, some genes that confer an advantage for the crop adaptation to unfavourable environments have been identified. The objective of this study is to identify genetic markers associated with phenotypic traits with emphasis on water stress tolerance in P. vulgaris. The establishment of molecular markers linked to drought tolerance would make possible their use for marker-assisted selection in bean breeding programs. Two hundred and eighty two F3:5 families derived from a cross between the drought resistant cultivars Pinto Villa and Pinto Saltillo were evaluated. The families were sowed under a 17x17 simple lattice design. The experiment was conducted between spring-summer seasons in 2010 and 2011, and autumn-winter seasons in 2010 at the Bajio Experimental Station of INIFAP with two treatments (full irrigation and terminal drought). All families were phenotyped and genotyped using molecular markers. Statistical analysis was based on principal component analysis (Eigen Analysis Selection Index Method, ESIM), association analysis between SNP markers and phenotype (SNPassoc package R) and analysis of variance (ANOVA). The ESIM values showed that seed yield, days to flowering, days to physiological maturity and harvest index were outstanding traits in terminal drought treatment, so they could be considered as suitable parameters for drought-tolerance evaluation in P. vulgaris. Nine outstanding families for the ESIM values were identified (PV/PS6, 22, 131, 137, 149, 154, 201, 236 and 273), in addition, these families showed higher values for seed yield compared to the parental cultivars. These families are promising candidates for studies focused on the identification of loci associated to the stress response, and as potential parental cultivars for the development of new varieties of common bean. In the SNPassoc analysis, 83 SNPs were found significantly associated (p<0.0003) with phenotypic traits, obtaining a total of 222 associations, most of which involved the traits days to flowering, reproductive period and total biomass under a codominant genetic model. The functional annotation analysis showed 37 SNPs with different biological functions, 12 of them (9, 18, 28, 39, 61, 69, 80, 106, 115, 128, 136 and 142) stand out by their association to phenotype. The functional annotation suggested a connection with genes related to drought tolerance, such as kinase activity, starch, carbohydrates and proline metabolic processes, responses to oxidative stress, as well as LEA genes and putative transcription factors. In the ANOVA analysis, 72 associations between SNPs and phenotypic traits (F<3.94E- 04) were identified. All of these associations corresponded to 30 SNPs markers and seven phenotypic traits. Weight of 100 seeds and reproductive period were the traits with more associations. Seed yield, harvest index and days to physiological maturity were associated to six SNPs (17, 34, 37, 50, 93 and 107), the SNP37 and SNP107 were identified as located in protein binding genes. The SNP106 and SNP128 were associated with the reproductive period and belonged to genes with kinase activity and genes related to starch metabolic process, respectively. In the case of AFLP markers, 271 associations (F<2.34E-04) were identified. The associations involved 86 AFLPs and all phenotypic traits, being the most frequently associated weight of 100 seeds, days to flowering and reproductive period. Even though it is not possible to perform a functional annotation for AFLP markers, they are proposed as potential markers related to drought resistance in common bean. AFLPs candidates require additional studies such as the sequencing of the respective alleles, identification of these sequences in the reference genome and gene annotation, before their use in marker assisted selection. This work, although requires further validation, proposes both genotypes and genetic markers that could be used in breeding programs of P. vulgaris in order to develop new lines or cultivars with enhanced drought-tolerance.

An Alternative Method to Achieve Metrological Confirmation in Measurement Processes

Metrological confirmation process must be designed and implemented to ensure that metrological characteristics of the measurement system meet metrological requirements of the measurement process. The aim of this paper is to present an alternative method to the traditional metrological requirements about the relationship between tolerance and measurement uncertainty, to develop such confirmation processes. The proposed way to metrological confirmation considers a given inspection task of the measurement process into the manufacturing system, and it is based on the Index of Contamination of the Capability, ICC. Metrological confirmation process is then developed taking into account the producer risks and economic considerations on this index. As a consequence, depending on the capability of the manufacturing process, the measurement system will be or will not be in adequate state of metrological confirmation for the measurement process.

Sensitivity of a distributed temperature-radiation index melt model based on AWS observations and surface energy balance fluxes, Hurd Peninsula glaciers, Livingston Island, Antarctica

We use an automatic weather station and surface mass balance dataset spanning four melt seasons collected on Hurd Peninsula Glaciers, South Shetland Islands, to investigate the point surface energy balance, to determine the absolute and relative contribution of the various energy fluxes acting on the glacier surface and to estimate the sensitivity of melt to ambient temperature changes. Long-wave incoming radiation is the main energy source for melt, while short-wave radiation is the most important flux controlling the variation of both seasonal and daily mean surface energy balance. Short-wave and long-wave radiation fluxes do, in general, balance each other, resulting in a high correspondence between daily mean net radiation flux and available melt energy flux. We calibrate a distributed melt model driven by air temperature and an expression for the incoming short-wave radiation. The model is calibrated with the data from one of the melt seasons and validated with the data of the three remaining seasons. The model results deviate at most 140 mm w.e. from the corresponding observations using the glaciological method. The model is very sensitive to changes in ambient temperature: a 0.5 ◦ C increase results in 56 % higher melt rates.

A new method for the identification of old-growth trees in National Forest Inventories: Application to Pinus halepensis Mill. stands in Spain

Old-growth trees play a very important role in the maintenance of biodiversity in forests. However, no clear definition is yet available to help identify them since tree age is usually not recorded in National Forest Inventories. To develop and test a new method to identify old-growth trees using a species-specific threshold for tree diameter in National Forest Inventories. Different nonlinear mixed models for diameter ? age were generated using data from the Spanish Forest Inventory in order to identify the most appropriate one for Aleppo pine in its South-western distribution area. The asymptote of the optimal model indicates the threshold diameter for defining an old-growth tree. Additionally, five site index curves were examined to analyze the influence of site quality on these models.

Calculus of the uncertainty in acoustic field measurements: comparative study between the uncertainty propagation method and the distribution propagation method

The new Spanish Regulation in Building Acoustic establishes values and limits for the different acoustic magnitudes whose fulfillment can be verify by means field measurements. In this sense, an essential aspect of a field measurement is to give the measured magnitude and the uncertainty associated to such a magnitude. In the calculus of the uncertainty it is very usual to follow the uncertainty propagation method as described in the Guide to the expression of Uncertainty in Measurements (GUM). Other option is the numerical calculus based on the distribution propagation method by means of Monte Carlo simulation. In fact, at this stage, it is possible to find several publications developing this last method by using different software programs. In the present work, we used Excel for the Monte Carlo simulation for the calculus of the uncertainty associated to the different magnitudes derived from the field measurements following ISO 140-4, 140-5 and 140-7. We compare the results with the ones obtained by the uncertainty propagation method. Although both methods give similar values, some small differences have been observed. Some arguments to explain such differences are the asymmetry of the probability distributions associated to the entry magnitudes,the overestimation of the uncertainty following the GUM

On the design of spherical gradient index lenses

Classical spherical gradient index (GRIN) lenses (such as Maxwell Fish Eye lens, Eaton lens, Luneburg lens, etc.) design procedure using the Abel integral equation is reviewed and reorganized. Each lens is fully defined by a function called the angle of flight which describes the ray deflection through the lens. The radial refractive index distribution is obtained by applying a linear integral transformation to the angle of flight. The interest of this formulation is in the linearity of the integral transformation which allows us to derive new solutions from linear combinations of known lenses. Beside the review of the classical GRIN designs, we present a numerical method for GRIN lenses defined by the Abel integral equation with fixed limits, which is an ill-posed problem.

A new approach to change detection in multispectral images by means of ERGAS index

In this letter, we propose a novel method for unsupervised change detection (CD) in multitemporal Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) satellite images by using the relative dimensionless global error in synthesis index locally. In order to obtain the change image, the index is calculated around a pixel neighborhood (3x3 window) processing simultaneously all the spectral bands available. With the objective of finding the binary change masks, six thresholding methods are selected. A comparison between the proposed method and the change vector analysis method is reported. The accuracy CD showed in the experimental results demonstrates the effectiveness of the proposed method.

An interactive method of fuzzy probability elicitation in risk analysis

Expert knowledge is used to assign probabilities to events in many risk analysis models. However, experts sometimes find it hard to provide specific values for these probabilities, preferring to express vague or imprecise terms that are mapped using a previously defined fuzzy number scale. The rigidity of these scales generates bias in the probability elicitation process and does not allow experts to adequately express their probabilistic judgments. We present an interactive method for extracting a fuzzy number from experts that represents their probabilistic judgments for a given event, along with a quality measure of the probabilistic judgments, useful in a final information filtering and analysis sensitivity process.

Montecarlo method applied to comparison of tenders in construction projects.

La comparación de las diferentes ofertas presentadas en la licitación de un proyecto,con el sistema de contratación tradicional de medición abierta y precio unitario cerrado, requiere herramientas de análisis que sean capaces de discriminar propuestas que teniendo un importe global parecido pueden presentar un impacto económico muy diferente durante la ejecución. Una de las situaciones que no se detecta fácilmente con los métodos tradicionales es el comportamiento del coste real frente a las variaciones de las cantidades realmente ejecutadas en obra respecto de las estimadas en el proyecto. Este texto propone abordar esta situación mediante un sistema de análisis cuantitativo del riesgo como el método de Montecarlo. Este procedimiento, como es sabido, consiste en permitir que los datos de entrada que definen el problema varíen unas funciones de probabilidad definidas, generar un gran número de casos de prueba y tratar los resultados estadísticamente para obtener los valores finales más probables,con los parámetros necesarios para medir la fiabilidad de la estimación. Se presenta un modelo para la comparación de ofertas, desarrollado de manera que puede aplicarse en casos reales aplicando a los datos conocidos unas condiciones de variación que sean fáciles de establecer por los profesionales que realizan estas tareas. ABSTRACT: The comparison of the different bids in the tender for a project, with the traditional contract system based on unit rates open to and re-measurement, requires analysis tools that are able to discriminate proposals having a similar overall economic impact, but that might show a very different behaviour during the execution of the works. One situation not easily detected by traditional methods is the reaction of the actual cost to the changes in the exact quantity of works finally executed respect of the work estimated in the project. This paper intends to address this situation through the Monte Carlo method, a system of quantitative risk analysis. This procedure, as is known, is allows the input data defining the problem to vary some within well defined probability functions, generating a large number of test cases, the results being statistically treated to obtain the most probable final values, with the rest of the parameters needed to measure the reliability of the estimate. We present a model for the comparison of bids, designed in a way that it can be applied in real cases, based on data and assumptions that are easy to understand and set up by professionals who wish to perform these tasks.

Oxygen extended sooting index of FAME blends with aviation kerosene

The use of biofuels in the aviation sector has economic and environmental benefits. Among the options for the production of renewable jet fuels, hydroprocessed esters and fatty acids (HEFA) have received predominant attention in comparison with fatty acid methyl esters (FAME), which are not approved as additives for jet fuels. However, the presence of oxygen in methyl esters tends to reduce soot emissions and therefore particulate matter emissions. This sooting tendency is quantified in this work with an oxygen-extended sooting index, based on smoke point measurements. Results have shown considerable reduction in the sooting tendency for all biokerosenes (produced by transesterification and eventually distillation) with respect to fossil kerosenes. Among the tested biokerosenes, that made from palm kernel oil was the most effective one, and nondistilled methyl esters (from camelina and linseed oils) showed lower effectiveness than distilled biokerosenes to reduce the sooting tendency. These results may constitute an additional argument for the use of FAME’s as blend components of jet fuels. Other arguments were pointed out in previous publications, but some controversy has aroused over the use of these components. Some of the criticism was based on the fact that the methods used in our previous work are not approved for jet fuels in the standard methods and concluded that the use of FAME in any amount is, thus, inappropriate. However, some of the standard methods are not updated for considering oxygenated components (like the method for obtaining the lower heating value), and others are not precise enough (like the methods for measuring the freezing point), whereas some alternative methods may provide better reproducibility for oxygenated fuels.

Improving parameters selection of a seeded region growing method for multiband image segmentation

In the last decade, Object Based Image Analysis (OBIA) has been accepted as an effective method for processing high spatial resolution multiband images. This image analysis method is an approach that starts with the segmentation of the image. Image segmentation in general is a procedure to partition an image into homogenous groups (segments). In practice, visual interpretation is often used to assess the quality of segmentation and the analysis relies on the experience of an analyst. In an effort to address the issue, in this study, we evaluate several seed selection strategies for an automatic image segmentation methodology based on a seeded region growing-merging approach. In order to evaluate the segmentation quality, segments were subjected to spatial autocorrelation analysis using Moran's I index and intra-segment variance analysis. We apply the algorithm to image segmentation using an aerial multiband image.

Optimizing panchromatic image change detection based on change index multiband image analysis

This work proposes an optimization of a semi-supervised Change Detection methodology based on a combination of Change Indices (CI) derived from an image multitemporal data set. For this purpose, SPOT 5 Panchromatic images with 2.5 m spatial resolution have been used, from which three Change Indices have been calculated. Two of them are usually known indices; however the third one has been derived considering the Kullbak-Leibler divergence. Then, these three indices have been combined forming a multiband image that has been used in as input for a Support Vector Machine (SVM) classifier where four different discriminant functions have been tested in order to differentiate between change and no_change categories. The performance of the suggested procedure has been assessed applying different quality measures, reaching in each case highly satisfactory values. These results have demonstrated that the simultaneous combination of basic change indices with others more sophisticated like the Kullback-Leibler distance, and the application of non-parametric discriminant functions like those employees in the SVM method, allows solving efficiently a change detection problem.

Determination of a refractive index and an extinction coefficient of standard production of CVD-graphene

The refractive index and extinction coefficient of chemical vapour deposition grown graphene are determined by ellipsometry analysis. Graphene films were grown on copper substrates and transferred as both monolayers and bilayers onto SiO2/Si substrates by using standard manufacturing procedures. The chemical nature and thickness of residual debris formed after the transfer process were elucidated using photoelectron spectroscopy. The real layered structure so deduced has been used instead of the nominal one as the input in the ellipsometry analysis of monolayer and bilayer graphene, transferred onto both native and thermal silicon oxide. The effect of these contamination layers on the optical properties of the stacked structure is noticeable both in the visible and the ultraviolet spectral regions, thus masking the graphene optical response. Finally, the use of heat treatment under a nitrogen atmosphere of the graphene-based stacked structures, as a method to reduce the water content of the sample, and its effect on the optical response of both graphene and the residual debris layer are presented. The Lorentz-Drude model proposed for the optical response of graphene fits fairly well the experimental ellipsometric data for all the analysed graphene-based stacked structures.

Local optimal scale in a hierarchical segmentation method for satellite image: an OBIA approach for the agricultural landscape

Overrecentdecades,remotesensinghasemergedasaneffectivetoolforimprov- ing agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hierarchically structured, the determination of optimal study scales is mandatory in understanding these processes and their interactions. The concept of multi-scale/multi- resolution inherent to OBIA methodologies allows the scale problem to be dealt with. But for that multi-scale and hierarchical segmentation algorithms are required. The question that remains unsolved is to determine the suitable scale segmentation that allows different objects and phenomena to be characterized in a single image. In this work, an adaptation of the Simple Linear Iterative Clustering (SLIC) algorithm to perform a multi-scale hierarchi- cal segmentation of satellite images is proposed. The selection of the optimal multi-scale segmentation for different regions of the image is carried out by evaluating the intra- variability and inter-heterogeneity of the regions obtained on each scale with respect to the parent-regions defined by the coarsest scale. To achieve this goal, an objective function, that combines weighted variance and the global Moran index, has been used. Two different kinds of experiment have been carried out, generating the number of regions on each scale through linear and dyadic approaches. This methodology has allowed, on the one hand, the detection of objects on different scales and, on the other hand, to represent them all in a sin- gle image. Altogether, the procedure provides the user with a better comprehension of the land cover, the objects on it and the phenomena occurring.