0000000000082325
AUTHOR
Beatriz Martínez
showing 41 related works from this author
Assessment of MODIS imagery to track light-use efficiency in a water-limited Mediterranean pine forest
2012
Abstract Daily values of gross primary production ( GPP ) derived from an eddy-covariance flux tower have been used to analyze the information content of the MODIS Photochemical Reflectance Index ( PRI ) on the light-use efficiency ( e ). The study has been conducted in a Mediterranean Pinus pinaster forest showing summer water stress. Advanced processing techniques have been used to analyze the effect of various external factors on e and PRI temporal variations. The intra-annual correlation between these two variables has been found to be mostly attributable to concurrent variations in sun and view zenith angles. The PRI has been normalized from these angular effects ( NPRI ), and its abil…
Vegetation dynamics from NDVI time series analysis using the wavelet transform
2009
A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to th…
Deep Learning Models Performance For NDVI Time Series Prediction: A Case Study On North West Tunisia
2020
The main goal of this paper is to analyze the performance of two deep learning models Long Short-Term Memory (LSTM) and bidirectional LSTM (BiLSTM) network for non-stationary Normalized Difference Vegetation Index (NDVI) time-series prediction. Both methods have provided good performances in the different time series. The BiLSTM has shown the best agreement with the lowest root mean square error (RMSE) and the highest Pearson correlation coefficient (R) of 0.034 and 0.93, respectively.
Use of Logistic Regression for Prediction of the Fate of Staphylococcus aureus in Pasteurized Milk in the Presence of Two Lytic Phages
2010
The use of bacteriophages provides an attractive approach to the fight against food-borne pathogenic bacteria, since they can be found in different environments and are unable to infect humans, both characteristics of which support their use as biocontrol agents. Two lytic bacteriophages, vB_SauS-phiIPLA35 (phiIPLA35) and vB_SauS-phiIPLA88 (phiIPLA88), previously isolated from the dairy environment inhibited the growth of Staphylococcus aureus. To facilitate the successful application of both bacteriophages as biocontrol agents, probabilistic models for predicting S. aureus inactivation by the phages in pasteurized milk were developed. A linear logistic regression procedure was used to desc…
Intercomparison of instruments for measuring leaf area index over rice
2015
Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. LAI estimates can be classified as direct or indirect methods. Direct methods are destructive, time consuming, and difficult to apply over large fields. Indirect methods are non-destructive and cost-effective due to its portability, accuracy and repeatability. In this study, we compare indirect LAI estimates acquired from two classical instruments such as LAI-2000 and digital cameras for hemispherical photography, with LAI estimates acquired with a smart app (PocketLAI) installed on a mobile smartphone. In this work it is shown that LAI…
Capability assessment of the SEVIRI/MSG GPP product for the detection of areas affected by water stress
2020
[ES] Se presenta el nuevo producto de producción primaria bruta (GPP) de EUMETSAT derivado a partir de datos del satélite geoestacionario SEVIRI/MSG (MGPP LSA-411) y se evalúa su potencial para detectar zonas afectadas por estrés hídrico (hot spots). El producto GPP se basa en la aproximación de Monteith, que modela la GPP de la vegetación como el producto de la radiación fotosintéticamente activa (PAR) incidente, la fracción de PAR absorbida (fAPAR) y un factor de eficiencia de uso de la radiación (ε). El potencial del producto MGPP para detectar hot spots se evalúa, utilizando un periodo corto de tres años, a escala local y regional, comparando con datos in situ derivados de medidas en to…
An Improved Forecasting Model from Satellite Imagery Based on Optimum Wavelet Bases and Adam Optimized LSTM Methods
2021
This paper proposes a new hybrid approach I-WT-LSTM (i.e., Improved Wavelet Long Short-Term Memory (LSTM) Model) for forecasting non-stationary time series (TS) from satellite imagery. The proposed approach consists of two steps: The first step aims at decomposing TS using Multi-Resolution Analysis wavelet (MRA-WT) into inter-and intra-annual components using 18 different mother wavelets (MW). Then, the energy to Shannon entropy ratio criterion is calculated to select the best MW. The second step is based on the LSTM model using Adam optimizer to predict the future. The proposed approach is tested using TS derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2001 t…
Trend Analysis Using Discrete Wavelet Transform (DWT) for Non-stationary NDVI Time Series in Tunisia
2021
In this paper, the trends in non-stationary Normalized Difference Vegetation Index (NDVI) Time Series (TS) over different areas in Tunisia are analyzed by applying wavelet transform and statistical tests. In the first step, the Discrete Wavelet Transform (DWT) was applied on three different time series in order to detect changes. Therefore, the different parameters of DWT were tested. In fact, the level of decomposition was calculated. The Maximum Energy to Shannon Entropy Ratio Criterion (MEER) was then investigated to choose the more suitable mother wavelet. Finally, the Mann-Kendall test (MK) was calculated for the last approximation of components to identify the variation in trend. In f…
Generation of global vegetation products from EUMETSAT AVHRR/METOP satellites
2020
We describe the methodology applied for the retrieval of global LAI, FAPAR and FVC from Advanced Very High Resolution Radiometer (AVHRR) onboard the Meteorological-Operational (MetOp) polar orbiting satellites also known as EUMETSAT Polar System (EPS). A novel approach has been developed for the joint retrieval of three parameters (LAI, FVC, and FAPAR) instead of training one model per parameter. The method relies on multi-output Gaussian Processes Regression (GPR) trained over PROSAIL EPS simulations. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. We describe the ma…
Tracking seasonal drought effects on ecosystem light use efficiency in a mediterranean forest using climatic and remote sensing data
2012
Daily values of light use efficiency (LUE) of a Mediterranean forest throughout five years have been analyzed in terms of different spectral indices obtained from MODIS products and which are informative on the water stress conditions. Although correlations between LUE and the different indices are rather high, the inter-annual variation of LUE due to the summer water stress is not well identified in most of them. In particular, the PRI (photochemical reflectance index) inter-annual variation has been found to be mostly attributable to concurrent variations in sun and view zenith angles. For the study area and at MODIS spatial resolution, the different indices are informative on changes in …
A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUM…
2018
Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach f…
Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment
2010
This paper evaluates the performance of spatial methods to estimate leaf area index (LAI) fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK), the collocated cokriging (CKC) and kriging with an external drift (KED) are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction pur…
Development of an earth observation processing chain for crop bio-physical parameters at local scale
2015
This paper proposes a full Earth observation processing chaing for biophysical parameter estimation at local scales. In particular, we focus on the Leaf Area Index (LAI) as an essential climate variable required for the monitoring and modeling of land surfaces at local scale. The main goal of this study is tied to the use of optical satellite images to retrieve Earth Observation (EO) biophysical parameters able to describe the spatio-temporal changes in agro-ecosystems at local scale. The objective of this work is two-fold: (i) to set up and update the EO products processing chain at high resolution (local) scale; and (ii) derive multitemporal LAI maps at 30 m resolution to be fed into a cr…
A global Canopy Water Content product from AVHRR/Metop
2020
Abstract Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational CWC product available to users. In the context of the Satellite Application Facility for Land Surface Analysis (LSA-SAF), we have developed an algorithm to produce a global dataset of CWC based on data from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board Meteorological–Operational (MetOp) satellites forming the EUMETSAT Polar System (EPS). CWC reflects the water conditions at the leaf level and information related …
Multitemporal Monitoring of Plant Area Index in the Valencia Rice District with PocketLAI
2016
Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies in order to assess crop yield. Frequently, plant canopy analyzers (LAI-2000) and digital cameras for hemispherical photography (DHP) are used for indirect effective plant area index (PAI(eff)) estimates. Nevertheless, these instruments are expensive and have the disadvantages of low portability and maintenance. Recently, a smartphone app called PocketLAI was presented and tested for acquiring PAI(eff) measurements. It was used during an entire rice season for indirect PAI(eff) estimations and for deriving reference high-resolution PAI(eff) maps. Ground PAI(eff) value…
Understanding deep learning in land use classification based on Sentinel-2 time series
2020
AbstractThe use of deep learning (DL) approaches for the analysis of remote sensing (RS) data is rapidly increasing. DL techniques have provided excellent results in applications ranging from parameter estimation to image classification and anomaly detection. Although the vast majority of studies report precision indicators, there is a lack of studies dealing with the interpretability of the predictions. This shortcoming hampers a wider adoption of DL approaches by a wider users community, as model’s decisions are not accountable. In applications that involve the management of public budgets or policy compliance, a better interpretability of predictions is strictly required. This work aims …
Vegetation vulnerability to drought in Spain
2014
[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…
Drought Monitoring In The Mediterranean Basin Using The Seviri/Msg Gpp Product (Mgpp)
2020
Recently, the Satellite Application Facility for Land Surface Analysis (LSA-SAF) has just released a new product that helps to characterize ecosystem processes, the 10-day LSA SAF GPP product from SEVIRI/MSG data (MGPP LSA-411). The GPP product is based on Monteith's concept, which models GPP as the product of the incoming photosynthetically active radiation (PAR), the fractional absorption of that flux $(\mathrm{f}_{APAR})$ and a light-use efficiency factor $(\varepsilon)$. Preliminary results on the use of the MGPP product in the assessment of ecosystem response to drought events are presented in this work for a short period of three years. A few sites located in the Mediterranean basin a…
Anatomy of Risk Premium in UK Natural Gas Futures
2015
In many futures markets, trading is concentrated in the front contract and positions are rolled-over until the strategy horizon is attained. In this paper, a pair-wise comparison between the conventional risk premium and the accrued risk premium in rolled-over positions in the front contract is carried out for UK natural gas futures. Several novel results are obtained. Firstly, and most importantly, the accrued risk premium in rollover strategies is significatively larger than conventional risk premiums and increases with the time to delivery. Specifically, for strategy horizons between three and six months, this difference increases from 1% to 10%. Secondly, it is the first time that risk …
Mapping Leaf Area Index with a Smartphone and Gaussian Processes
2020
Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies. Smartphones are nowadays ubiquitous sensor devices with high computational power, moderate cost, and high-quality sensors. A smartphone app, which is called PocketLAI, was recently presented and tested for acquiring ground LAI estimates. In this letter, we explore the use of state-of-the-art nonlinear Gaussian process regression (GPR) to derive spatially explicit LAI estimates over rice using ground data from PocketLAI and Landsat 8 imagery. GPR has gained popularity in recent years because of its solid Bayesian foundations that offer not only high accuracy but also…
Deep learning for agricultural land use classification from Sentinel-2
2020
[ES] En el campo de la teledetección se ha producido recientemente un incremento del uso de técnicas de aprendizaje profundo (deep learning). Estos algoritmos se utilizan con éxito principalmente en la estimación de parámetros y en la clasificación de imágenes. Sin embargo, se han realizado pocos esfuerzos encaminados a su comprensión, lo que lleva a ejecutarlos como si fueran “cajas negras”. Este trabajo pretende evaluar el rendimiento y acercarnos al entendimiento de un algoritmo de aprendizaje profundo, basado en una red recurrente bidireccional de memoria corta a largo plazo (2-BiLSTM), a través de un ejemplo de clasificación de usos de suelo agrícola de la Comunidad Valenciana dentro d…
European Natural Gas Seasonal Effects on Futures Hedging
2015
Abstract This paper is the first to discuss the design of futures hedging strategies in European natural gas markets (NBP, TTF and Zeebrugge). A common feature of energy prices is that conditional mean and volatility are driven by seasonal trends due to weather, demand, and storage level seasonalities. This paper follows and extends the Ederington and Salas (2008) framework and considers seasonalities in mean and volatility when minimum variance hedge ratios are computed. Our results show that hedging effectiveness is much higher when the seasonal pattern in spot price changes is approximated with lagged values of the basis (futures price minus spot price). This fact remains true for short …
Derivation of high-resolution leaf area index maps in support of validation activities: Application to the cropland Barrax site
2009
The validation of coarse satellite-derived products from field measurements generally relies on up-scaling the field data to the corresponding satellite products. This question is commonly addressed through the generation of a reference high-resolution map of an area covering several moderate resolution pixels. This paper describes a method by which reference leaf area index (LAI) maps can be generated from ground-truth LAI measurements. The method is based on a multivariate ordinary least squares (OLS) algorithm which uses an iteratively re-weighted least squares (IRLS) algorithm. It provides an empirical relationship (i.e. a transfer function) between in situ measurements and concomitant …
Accuracy assessment of fraction of vegetation cover and leaf area index estimates from pragmatic methods in a cropland area
2009
The fraction of vegetation cover (FVC) and the leaf area index (LAI) are important parameters for many agronomic, ecological and meteorological applications. Several in-situ and remote sensing techniques for estimating FVC and LAI have been developed in recent years. In this paper, the uncertainty of in-situ FVC and LAI measurements was evaluated by comparing estimates from LAI-2000 and digital hemispherical photography (DHP). The accuracy achieved with a spectral mixture analysis algorithm and two vegetation indices-based methods was assessed using atmospherically corrected Landsat Thematic Mapper (TM) data over the Barrax cropland area where the European Space Agency (ESA) SENtinel-2 and …
Comparative study of three satellite image time-series decomposition methods for vegetation change detection
2018
International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…
Patterns Comparison Between Gome-2 Sun-Induced Fluorescence and Msg Gross Primary Production
2018
A comparison between maximum monthly MSG gross primary production (GPP) estimates with the sun-induced chlorophyll fluorescence (SIF) product from the Global Ozone Monitoring Experiment-2 (GOME-2) over Europe and Africa is presented as an indirect validation of MSG GPP estimates. The maximum daily GPP value for each month is derived from daily MSG GPP, which takes full advantage of the SEVIRI/MSG products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) delivered by the Satellite Application Facility for Land Surface Analysis (LSA SAF). A linear relationship found between both products over savanna, grasslands and forests at high latitudes evidence…
Characterizing land condition variability in Ferlo, Senegal (2001–2009) using multi-temporal 1-km Apparent Green Cover (AGC) SPOT Vegetation data
2011
Abstract The ecosystem state or ‘land condition’ can be characterized by a set of attributes, which show variations at different temporal scales. A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to examine the land condition of a dryland region in Ferlo (Senegal) over the period 2001–2009. This methodology has proven to be useful for smoothing time series while considering those temporal resolutions that incorporate information about the vegetation dynamics. For this purpose, time series of the 1-km Apparent Green Cover (AGC) from the 10-day composites SPOT Vegetation (VGT) data are analyzed. Two relevant outputs from the MRA, A 1 (de-noised) and th…
Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula
2013
Abstract The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences ar…
Mapping daily global solar irradiation over Spain: A comparative study of selected approaches
2011
Abstract Three methods to estimate the daily global solar irradiation are compared: the Bristow–Campbell (BC), Artificial Neural Network (ANN) and Kernel Ridge Regression (KRR). BC is an empirical approach based on air maximum and minimum temperature. ANN and KRR are non-linear approaches that use temperature and precipitation data (which have been selected as the best combination of input data from a gamma test). The experimental dataset includes 4 years (2005–2008) of daily irradiation collected at 40 stations and temperature and precipitation data collected at 400 stations over Spain. Results show that the ANN method produces the best global solar irradiation estimates, with a mean absol…
Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter
2014
Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), sm…
Validation of daily global solar irradiation images from MSG over Spain
2013
Abstract Daily irradiation images over Spain – area that embraces a highly heterogeneous landscape, climatic conditions and relief – are calculated from the down-welling surface short-wave radiation flux (DSSF) product derived from the MSG SEVIRI images. Their analysis and validation is carried out using two different station networks along the year 2008. The first network covers the peninsular Spain and Balearic islands. A denser one, covering the Catalonian territory and including many stations located in rugged terrain, is found useful to assess the elevation correction to be applied to the images. The statistics from the validation using the first network shows a relative mean bias of a…
Daily GPP estimates in Mediterranean ecosystems by combining remote sensing and meteorological data
2015
The accurate representation of terrestrial CO2 uptake (GPP) using Monteith's approach requires a frequent and site-specific parameterization of the model inputs. In this work, an optimization of this approach has been carried out by adjusting the inputs (f(APAR), PAR and epsilon) for the study area, peninsular Spain, a typical Mediterranean region. The daily GPP images have been calculated for 2008 and 2011 with a 1-km spatial resolution and validated by comparison with in situ GPP estimates from the eddy covariance data (direct validation) and by inter-comparison with the MODIS GPP product. The direct validation has evidenced an excellent agreement with correlations up to 0.98 in 2008 and …
Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products
2018
The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperatur…
Hedging spark spread risk with futures
2018
Abstract This paper discusses the spark spread risk management using electricity and natural gas futures. We focus on three European markets in which the natural gas share in the fuel mix varies considerably: Germany, the United Kingdom, and the Netherlands. We find that spark spread returns are partially predictable, and consequently, the Ederington and Salas (2008) minimum variance hedging approach should be applied. Hedging the spark spread is more difficult than hedging electricity and natural gas price risks with individual futures contracts. Whereas spark spread risk reduction for monthly periods produces values of between 20.05% and 48.90%, electricity and natural gas individual hedg…
Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP)
2020
The objective of this study is to describe a completely new 10-day gross primary production (GPP) product (MGPP LSA-411) based on data from the geostationary SEVIRI/MSG satellite within the LSA SAF (Land Surface Analysis SAF) as part of the SAF (Satellite Application Facility) network of EUMETSAT. The methodology relies on the Monteith approach. It considers that GPP is proportional to the absorbed photosynthetically active radiation APAR and the proportionality factor is known as the light use efficiency ε. A parameterization of this factor is proposed as the product of a εmax, corresponding to the canopy functioning under optimal conditions, and a coefficient quantifying the reduction of …
Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications
2019
The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed …
Analysis of risk premium in UK natural gas futures
2018
Abstract In many futures markets, trading is concentrated on the front contract and positions are rolled-over until the strategy horizon is attained. In this paper, a pair-wise comparison between the conventional risk premium and the accrued risk premium in rolled-over positions on the front contract is carried out for UK natural gas futures. Several novel results are obtained. Firstly, and most importantly, the accrued risk premium in rollover strategies is significatively larger than conventional risk premiums and increases with the time to delivery. Specifically, for strategy horizons between three and six months, this difference increases from 1% to 10% (or from 4% to 20% in annualized …
Estimación de la fAPAR sobre la Península Ibérica a partir de la inversión del modelo de transferencia radiativa 4SAIL2
2014
El objetivo de este trabajo consiste en la estimación de la fAPAR en la Península Ibérica a partir de datos MODIS. En primer lugar, se ha simulado un conjunto de datos de reflectividades y de fAPAR a partir de los modelos de transferencia radiativa de hoja (PROSPECT) y de cubiertas heterogéneas (4SAIL2). En segundo lugar, se ha entrenado un conjunto de redes neuronales artificiales (RNAs) para obtener mediante inversión la relación entre la fAPAR y las reflectividades simuladas y así calcular, por último, la fAPAR de la Península Ibérica a partir de imágenes de reflectividad de MODIS. Además, se ha analizado la influencia de la configuración de observación e iluminación, nadir y oblicua. La…
Vareniclina. Un paso más en la lucha contra el tabaquismo
2007
Recientemente la Food and Drugs Administration ha aprobado Vareniclina, fármaco para la deshabituación tabáquica que presenta un novedoso mecanismo de acción, agonismo parcial de receptores nicotínicos de acetilcolina a4ß2.Hemos revisado la farmacología, eficacia y seguridad de Vareniclina y su utilidad en los procesos de deshabituación, usando como fuentes bibliográficas la base de datos MEDLINE , MD consults, American journal of Addictions y distintos manuales de referencia.De los tres ensayos clínicos publicados, dos de ellos, Jorenby y Gonzales comparan la eficacia y seguridad de Vareniclina 1mg/12h frente a Bupropion 150mg/12h y placebo, durante un periodo de 52 semanas, obteniéndose l…
DSM-5 ¿Qué modificaciones nos esperan?
2013
La Asociación Americana de Psiquiatría (APA), antes de la publicación definitiva del Manual DSM-5, abrió un periodo de participación donde investigadores, clínicos, pacientes y familias pudieron aportar comentarios sobre la futura clasificación. En este periodo se recibieron más de 15.000 comentarios que han sido tenidos en cuenta por los grupos de trabajo encargados de la elaboración del manual. En este artículo queremos exponer algunos de los cambios propuestos en la nueva versión del sistema de clasificación diagnóstico DSM-5 y que ciertamente van a afectar a nuestra práctica diaria. Nos centraremos principalmente en los trastornos que se inician en la infancia, los denominados trastorno…
Buprenorfina-naloxona en el tratamiento de la dependencia a opiáceos
2007
En los últimos diez años la buprenorfina ha aumentado su disponibilidad en Europa como alternativa a la metadona en el tratamiento de la dependencia a opiáceos. La buprenorfina es un opiáceo sintético con actividad agonista parcial utilizado en el tratamiento de sustitución de la dependencia a opiáceos. Diversos estudios han demostrado que posee una eficacia superior a placebo y similar a metadona.Con el fin de disminuir el uso inadecuado de la buprenorfina por vía intravenosa, en octubre de 2002 se aprobó en Estados Unidos la combinación sublingual de buprenorfina con una pequeña dosis del antagonista opiáceo naloxona. Sin embargo, no es hasta octubre de 2006 cuando la Comisión Europea apr…