Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

A Small Baseline DIFSAR Approach for Investigating Deformations on Full Resolution SAR Interferograms

This paper presents a differential synthetic apertureradar (SAR) interferometry (DIFSAR) approach for investigatingdeformation phenomena on full-resolution DIFSAR interferograms.In particular, our algorithm extends the capabilityof the small-baseline subset (SBAS) technique that relies onsmall-baseline DIFSAR interferograms only and is mainly focusedon investigating large-scale deformations with spatial resolutionsof about 100 100 m. The proposed technique is implemented byusing two different sets of data generated at low (multilook data)and full (single-look data) spatial resolution, respectively. Theformer is used to identify and estimate, via the conventional SBAStechnique, large spatial scale deformation patterns, topographicerrors in the available digital elevation model, and possibleatmospheric phase artifacts; the latter allows us to detect, onthe full-resolution residual phase components, structures highlycoherent over time (buildings, rocks, lava, structures, etc.), as wellas their height and displacements. In particular, the estimation ofthe temporal evolution of these local deformations is easily implementedby applying the singular value decomposition technique.The proposed algorithm has been tested with data acquired by theEuropean Remote Sensing satellites relative to the Campania area(Italy) and validated by using geodetic measurements.

Efecto de los usos del suelo en la emisión de dióxido de carbono del suelo a la atmósfera en un agroecosistema semiárido del Valle del Ebro

Los cambios en los usos del suelo han contribuido de manera importante al incremento de gases de efecto invernadero en la atmósfera, especialmente de dióxido de carbono, aumentando sus emisiones desde 1970 en un 80%. Estos cambios causan la alteración de los suelos provocando un impacto sobre el ciclo del carbono, aumentando las tasas de descomposición de la fracción orgánica creando así un flujo de CO2 a la atmosfera. Entre las recomendaciones del Panel Intergubernamental de expertos sobre el Cambio Climático (IPCC, en inglés), y contemplado en el Protocolo de Kyoto, se encuentra el proceso de secuestro de carbono en suelos, que implica la eliminación del CO2 atmosférico por parte de las plantas y su almacenamiento como materia orgánica del suelo. Para poder favorecer dicho proceso, en un determinado tipo de ecosistema, es fundamental conocer cuáles son los factores que gobiernan la respiración del suelo y el impacto que tienen los diferentes usos en la emisión de CO2. En el presente trabajo se han estudiado 4 usos del suelo representativos del secano aragonés: un monocultivo de cebada en siembra directa (NT), un suelo abandonado labrado (AC), un suelo abandonado no alterado (AU) y un suelo forestal (FR) con el objetivo de conocer sus tasas de respiración, la influencia de diferentes parámetros edáficos en ellas, y proponer cambios en el uso del suelo que ayuden a mitigar estas emisiones. Además, se ha dedicado un apartado para conocer cómo influyen diferentes técnicas de fertilización nitrogenada (mineral y orgánica) en la respiración de un monocultivo de cebada en siembra directa. En cuanto a los usos, los resultados obtenidos tanto in situ como en laboratorio muestran una mayor respiración en AC, siendo los valores más bajos los de NT y FR. Una de las principales conclusiones es que la supresión del laboreo y del periodo de barbecho largo, así como la conversión de tierras abandonadas y marginales a cultivos y zonas forestales se presentan en este tipo de ecosistemas como prácticas de secuestro de carbono. En el estudio de aplicación de fertilizantes, no se observó ningún cambio en la respiración del suelo después de la aplicación de nitrógeno mineral. En cambio, el suelo fertilizado con purín sí que mostró picos de emisión durante las siguientes horas a la incorporación de éste, debido fundamentalmente a su alto contenido de carbono lábil.

Declining labor force attachment and downward trends in unemployment and participation

The US labor market witnessed two apparently unrelated secular movements in thelast 30 years: a decline in unemployment between the early 1980s and the early 2000s,and a decline in participation since the early 2000s. Using CPS micro data and a stock-flow accounting framework, we show that a substantial, and hitherto unnoticed, factorbehind both trends is a decline in the share of nonparticipants who are at the margin ofparticipation. A lower share of marginal nonparticipants implies a lower unemploymentrate, because marginal nonparticipants enter the labor force mostly through unemployment,while other nonparticipants enter the labor force mostly through employment.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

A wavelet-based method for the determination of the relative resolution between remotely sensed images

Spatial resolution is a key parameter of all remote sensing satellites and platforms. The nominal spatial resolution of satellites is a well-known characteristic because it is directly related to the area in ground that represents a pixel in the detector. Nevertheless, in practice, the actual resolution of a specific image obtained from a satellite is difficult to know precisely because it depends on many other factors such as atmospheric conditions. However, if one has two or more images of the same region, it is possible to compare their relative resolutions. In this paper, a wavelet-decomposition-based method for the determination of the relative resolution between two remotely sensed images of the same area is proposed. The method can be applied to panchromatic, multispectral, and mixed (one panchromatic and one multispectral) images. As an example, the method was applied to compute the relative resolution between SPOT-3, Landsat-5, and Landsat-7 panchromatic and multispectral images taken under similar as well as under very different conditions. On the other hand, if the true absolute resolution of one of the images of the pair is known, the resolution of the other can be computed. Thus, in the last part of this paper, a spatial calibrator that is designed and constructed to help compute the absolute resolution of a single remotely sensed image is described, and an example of its use is presented.

The effect of substrate on high-temperature annealing of GaN epilayers: Si versus sapphire

We have studied the effects of rapid thermal annealing at 1300¿°C on GaN epilayers grown on AlN buffered Si(111) and on sapphire substrates. After annealing, the epilayers grown on Si display visible alterations with craterlike morphology scattered over the surface. The annealed GaN/Si layers were characterized by a range of experimental techniques: scanning electron microscopy, optical confocal imaging, energy dispersive x-ray microanalysis, Raman scattering, and cathodoluminescence. A substantial Si migration to the GaN epilayer was observed in the crater regions, where decomposition of GaN and formation of Si3N4 crystallites as well as metallic Ga droplets and Si nanocrystals have occurred. The average diameter of the Si nanocrystals was estimated from Raman scattering to be around 3¿nm. Such annealing effects, which are not observed in GaN grown on sapphire, are a significant issue for applications of GaN grown on Si(111) substrates when subsequent high-temperature processing is required.