Evolución de la cubierta forestal de la cuenca del Duero: análisis multitemporal mediante teledetección

Se presenta un estudio de la evolución de la cubierta forestal en cuatro sub-cuencas de la cuenca del Duero mediante el uso de imágenes Landsat desde mediados de los años 70 hasta la actualidad. El estudio se basa en el análisis multitemporal en las cuencas del Esla, el Carrión, el Tormes y el Alto Duero, todas ellas representativas de las diferentes vertientes hidrográficas. A diferencia de lo que se observa en la mayoría de los estudios realizados sobre la evolución de la superficie de bosque, que utilizan como punto de partida la foto aérea de 1956 y que, como máximo, aportan mapas de la distribución de los usos/coberturas de suelo en dos o tres fechas durante la década de los 90 o en la actualidad, en este trabajo se han utilizado todas las imágenes disponibles (entre 10 y 13 por cuenca). De esta forma se consiguió una serie homogénea en el tiempo y con un número de mapas suficiente para realizar un análisis de tendencias y determinar de manera rigurosa la existencia o no de una evolución clara. En una fase preliminar se empleó cartografía base del Mapa de Cultivos y Aprovechamientos y del Mapa Forestal de España, mapas de los Inventarios Forestales Nacionales y ortofotos aéreas como datos auxiliares para definir las clases de cubierta, seleccionar las zonas de entrenamiento y validar los resultados. Para la caracterización espectral de las distintas clases se utilizaron para cada escena y fecha el NDVI (Normalized Difference Vegetation Index) y las reflectividades de superficie de las bandas visible, infrarrojo cercano e infrarrojo de onda corta, tras los procesos de calibración y corrección geométrica, radiométrica y atmosférica. El método elegido para la discriminación de cubiertas boscosas ha sido el de clasificación supervisada por máxima probabilidad y el posterior refinado de resultados mediante filtrado y criterios condicionales. Finalmente, los resultados se evaluaron mediante matrices de confusión generadas a partir del Mapa Forestal de España (2002-2004), y también se compararon las superficies obtenidas por el proceso de clasificación con las de la cartografía base de los IFN y del programa CORINE. Los resultados muestran que, a diferencia de lo que ha ocurrido en las principales zonas forestales de España, en la cuenca del Duero la superficie de bosque no ha aumentado en los últimos 40 años. Dicha cubierta muestra una tendencia claramente negativa en tres de las cuencas estudiadas.Este trabajo ha sido posible gracias a la financiación del Proyecto SA212A11-2 de la Junta de Castilla y León. Los autores también agradecen al United States Geological Survey (USGS) y a la Agencia Europea del Espacio (ESA) las imágenes Landsat

A New Soil Moisture Agricultural Drought Index (SMADI) Integrating MODIS and SMOS Products: A Case of Study over the Iberian Peninsula

25 pages, 9 figures, 4 tablesA new index for agricultural drought monitoring is presented based on the integration of different soil/vegetation remote sensing observations. The synergistic fusion of the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission, with the Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface temperature (LST), and water/vegetation indices for agricultural drought monitoring was tested. The rationale of the approach is based on the inverse relationship between LST, vegetation condition and soil moisture content. Thus, the proposed Soil Moisture Agricultural Drought Index (SMADI) combines the soil and temperature conditions while including the lagged response of vegetation. SMADI was retrieved every eight days at 500 m spatial resolution for the whole Iberian Peninsula (IP) from 2010 to 2014, and a time lag of eight days was used to account for the plant response to the varying soil/climatic conditions. The results of SMADI compared well with other agricultural indices in a semiarid area in the Duero basin, in Spain, and also with a climatic index in areas of the Iberian Peninsula under contrasted climatic conditions. Based on a standard classification of drought severity, the proposed index allowed for a coherent description of the drought conditions of the IP during the study periodThis study was supported by the Spanish Ministry of Economy and Competitiveness, MINECO (Projects AYA2012-39356-C05 and ESP2015-67549-C3-3) and the European Regional Development Fund, FEDER. Partial funding was also received from the BBVA FoundationPeer Reviewe

Multi-temporal evaluation of soil moisture and land surface temperature dynamics using in situ and satellite observations

Soil moisture (SM) is an important component of the Earth’s surface water balance and by extension the energy balance, regulating the land surface temperature (LST) and evapotranspiration (ET). Nowadays, there are two missions dedicated to monitoring the Earth’s surface SM using L-band radiometers: ESA’s Soil Moisture and Ocean Salinity (SMOS) and NASA’s Soil Moisture Active Passive (SMAP). LST is remotely sensed using thermal infrared (TIR) sensors on-board satellites, such as NASA’s Terra/Aqua MODIS or ESA & EUMETSAT’s MSG SEVIRI. This study provides an assessment of SM and LST dynamics at daily and seasonal scales, using 4 years (2011–2014) of in situ and satellite observations over the central part of the river Duero basin in Spain. Specifically, the agreement of instantaneous SM with a variety of LST-derived parameters is analyzed to better understand the fundamental link of the SM–LST relationship through ET and thermal inertia. Ground-based SM and LST measurements from the REMEDHUS network are compared to SMOS SM and MODIS LST spaceborne observations. ET is obtained from the HidroMORE regional hydrological model. At the daily scale, a strong anticorrelation is observed between in situ SM and maximum LST (R ˜ -0.6 to -0.8), and between SMOS SM and MODIS LST Terra/Aqua day (R ˜ - 0.7). At the seasonal scale, results show a stronger anticorrelation in autumn, spring and summer (in situ R ˜ -0.5 to -0.7; satellite R ˜ -0.4 to -0.7) indicating SM–LST coupling, than in winter (in situ R ˜ +0.3; satellite R ˜ -0.3) indicating SM–LST decoupling. These different behaviors evidence changes from water-limited to energy-limited moisture flux across seasons, which are confirmed by the observed ET evolution. In water-limited periods, SM is extracted from the soil through ET until critical SM is reached. A method to estimate the soil critical SM is proposed. For REMEDHUS, the critical SM is estimated to be ~0.12 m3/m3 , stable over the study period and consistent between in situ and satellite observations. A better understanding of the SM–LST link could not only help improving the representation of LST in current hydrological and climate prediction models, but also refining SM retrieval or microwave-optical disaggregation algorithms, related to ET and vegetation status.Peer ReviewedPostprint (published version

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 1 pageSoil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA’s Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth’s surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona’s fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide ’memory’ in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to droughtPeer Reviewe

SIGPAC y series multitemporales LANSAT 15 TM como estrategia híbrida de clasificación de usos de suelo para aplicaciones hidrológicas

El objetivo de este trabajo consiste en la obtención de un mapa de usos y coberturas de suelo para su integración en un modelo hidrológico de balance de agua a lo largo de 2009. Los resultados de dicha aplicación (evapotranspiración, humedad de suelo, necesidades de riego) se obtienen a escala de parcela, con escala temporal diaria y contemplando los usos y coberturas más frecuentes en la zona. La herramienta diseñada para aplicar el modelo (HidroMORE, Modelo Hidrológico de Estimación de Recarga y Evapotranspiración) proporciona los resultados en forma de mapa imagen. Con este fin, se presenta una alternativa híbrida de clasificación consistente en la combinación de la base de datos vectorial del Sistema de Información Geográfica de Parcelas Agrícolas (SIGPAC), junto con una serie multitemporal de imágenes Landsat 5 TM (Thematic Mapper) del año 2009. El primero aporta la definición parcelaria, mientras que la segunda provee la información suficiente para resolver clases poco definidas en el SIGPAC, especialmente la categoría ‘tierra arable’. Se utilizaron metodologías de teledetección como la clasificación, la segmentación multitemporal y el NDVI (Normalized Difference Vegetation Index), junto con herramientas SIG. El método propuesto supuso una mejora global de la precisión respecto a un método de clasificación supervisada convencional del 20% para la zona de estudio en 2009, y con un coste operacional muy bajo.The aim of this work consists on retrieving a land use-land cover map in order to integrate it in a water balance model along 2009. The results of this application, i.e., evapotranspiration, soil moisture, irrigation rates, are obtained at field scale, in a daily basis, and over the most representative agricultural uses. The model is implemented in a computerized tool, HidroMORE, which provides image maps of the results. A hybrid alternative of classification is presented for such hydrological application. It consisted in a combination of the vectorial database from the Spanish Geographic Information System for Agricultural Plots (SIGPAC) and a Landsat 5 TM multitemporal series of images for the year of study. The SIGPAC affords the spatial shape of the plots, whereas the images allow the segmentation of some ambiguous categories, i.e., ‘agricultural plots’. Remote sensing techniques (classification, segmentation, and NDVI, Normalized Difference Vegetation Index) were used, as well as GIS tools. The proposed method improved by 20% the global accuracy comparing to a typical supervised classification in the study area along 2009, while the computational cost is low

Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations

[EN]In this study, six satellite-based root zone soil moisture (RZSM) estimates from March 2015 to December 2016 were evaluated both temporally and spatially. The first two were the Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) L4 RZSM products. The other four were obtained through the Soil Water Index (SWI) approach, which embedded surface soil moisture (SSM). The SMOS-Barcelona Expert Center (BEC) L4 SSM product and the apparent thermal inertia (ATI)-derived SSM from the Moderate Resolution Imaging Spectroradiometer (MODIS) data were used as SSM datasets. In the temporal analysis, the RZSM estimates were compared to in situ RZSM from 14 stations of the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS). Regarding the spatial assessment, the resulting RZSM maps of the Iberian Peninsula were compared between them. All RZSM values followed the temporal evolution of the ground-based measurements well, although SMOS and MODIS showed underestimation while SMAP displayed overestimation. The good results obtained from MODIS ATI are notable, notwithstanding they were not estimated through microwave radiometry. A very high agreement was found in terms of spatial patterns for the whole Iberian Peninsula except for the extreme north area, which is dominated by high mountains and dense forests

Assessment of SMADI and SWDI agricultural drought indices using remotely sensed root zone soil moisture

[EN]The increasing frequency of drought events has expanded the research interest in drought monitoring. In this regard, remote sensing is a useful tool to globally mapping the agricultural drought. While this type of drought is directly linked to the availability of root zone soil moisture (RZSM) for plants growth, current satellite soil moisture observations only characterize the water content of the surface soil layer (0–5 cm). In this study, two soil moisture-based agricultural drought indices were obtained at a weekly rate from June 2010 to December 2016, using RZSM estimations at 1 km from the Soil Moisture and Ocean Salinity (SMOS) satellite, instead of surface soil moisture (SSM). The RZSM was estimated by applying the Soil Water Index (SWI) model to the SMOS SSM. The Soil Moisture Agricultural Drought Index (SMADI) and the Soil Water Deficit Index (SWDI) were assessed over the Castilla y León region (Spain) at 1 km spatial resolution. They were compared with the Atmospheric Water Deficit (AWD) and the Crop Moisture Index (CMI), both computed at different weather stations distributed over the study area. The level of agreement was analyzed through statistical correlation. Results showed that the use of RZSM does not influence the characterization of drought, both for SMADI and SWDI

Validation of SMOS L2 and L3 soil moisture products over the Duero Basin at different spatial scales

36th International Symposium on Remote Sensing of Environment, 11-15 May 2015, Berlin, Germany.-- 6 pages, 3 figures, 3 tablesAn increasing number of permanent soil moisture measurement networks are nowadays providing the means for validating new remotely sensed soil moisture estimates such as those provided by the ESA’s Soil Moisture and Ocean Salinity (SMOS) mission. Two types of in situ measurement networks can be found: small-scale (100–10000 km2), which provide multiple ground measurements within a single satellite footprint, and large-scale (>10000 km2), which contain a single point observation per satellite footprint. This work presents the results of a comprehensive spatial and temporal validation of a long-term (January, 2010 to June, 2014) dataset of SMOS-derived soil moisture estimates using two in situ networks within the Duero basin (Spain). The first one is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively applied for validation of soil moisture remote sensing observations, including SMOS. REMEDHUS can be considered within the small-scale network group (1300 km2). The other network started from an existing meteorological network from the Castilla y León region, where soil moisture probes were incorporated in 2012. This network can be considered within the large-scale group (65000 km2). Results from comparison to in situ show that the new reprocessed L2 product (v5.51) improves the accuracy of former soil moisture retrievals, making them suitable for developing new L3 products. Validation based on comparisons between dense/sparse networks showed that temporal patterns on soil moisture are well reproduced, whereas spatial patterns are difficult to depict given the different spatial representativeness of ground and satellite observationsThis work was supported by the Spanish Ministry of Economy and Competitiveness (Project AYA2012-39356-C05). Ángela Gumuzzio acknowledges support from the FPI grant BES-2011-050439Peer Reviewe

Impact of day/night time land surface temperature in soil moisture disaggregation algorithms

18 pages, 5 figures, 1 tableSince its launch in 2009, the ESA’s SMOS mission is providing global soil moisture (SM) maps at ~40 km, using the first L-band microwave radiometer on space. Its spatial resolution meets the needs of global applications, but prevents the use of the data in regional or local applications, which require higher spatial resolutions (~1-10 km). SM disaggregation algorithms based generally on the land surface temperature (LST) and vegetation indices have been developed to bridge this gap. This study analyzes the SM-LST relationship at a variety of LST acquisition times and its influence on SM disaggregation algorithms. Two years of in situ and satellite data over the central part of the river Duero basin and the Iberian Peninsula are used. In situ results show a strong anticorrelation of SM to daily maximum LST (R≈0.5 to -0.8). This is confirmed with SMOS SM and MODIS LST Terra/Aqua at day time-overpasses (R≈-0.4 to -0.7). Better statistics are obtained when using MODIS LST day (R≈0.55 to 0.85; ubRMSD≈0.04 to 0.06 m/m) than LST night (R≈0.45 to 0.80; ubRMSD≈0.04 to 0.07 m/m) in the SM disaggregation. An averaged ensemble of day and night MODIS LST Terra/Aqua disaggregated SM estimates also leads to robust statistics (R≈0.55 to 0.85; ubRMSD≈0.04 to 0.07 m/m) with a coverage improvement of~10-20 %This work was supported by the Spanish Ministry of Economy and Competitiveness, through a Formación Personal Investigador (FPI) grant BES-2011-043322, the project PROMISES: ESP2015-67549-C3, ERDF (European Regional Development Fund) and the BBVA foundationPeer Reviewe

Bibliometric analysis of communications presented at Congreso Nacional Bioquímico, between 1997 and 2005

Un congreso es una reunión científica multitudinaria, con cientos o miles de participantes, dirigida a profesionales de una disciplina o campo del conocimiento, para difundir, discutir e intercambiar información sobre avances recientes. El programa incluye tres subprogramas: actualización, educación y comunicaciones libres. La Bibliometría se ocupa de analizar estadísticamente la información registrada en publicaciones científicas, habiéndose propuesto tres tipos de indicadores bibliométricos para congresos: cuantitativos, cualitativos y de evidencia científica. El propósito del presente trabajo ha sido analizar, según indicadores cuantitativos, las comunicaciones del Congreso Nacional Bioquímico de la Confederación Unificada Bioquímica de la República Argentina (CUBRA). Se analizaron las comunicaciones presentadas en los congresos de Tucumán 1997, Huerta Grande 1999, Bariloche 2001, Posadas 2003 y San Juan 2005. El total de comunicaciones fue 388, todas en formato poster. La mediana fue de 4 autores por comunicación. Las principales áreas temáticas fueron Química Clínica, (incluyendo Endocrinología y Medio Interno, 45,4%) y Microbiología (incluyendo Bacteriología, Parasitología, Micología y Virología, 21,1%). El 34,3% provenía de universidades, 27,1% de hospitales y 23,7% por colaboración entre 2 instituciones, siendo el principal aporte de: Universidad de Buenos Aires (n=35, 9,0%), Fundación Bioquímica Argentina (n=30, 7,7%) y Universidad Nacional de Tucumán (n=26, 6,7%).A congress is a multitudinous scientific meeting, with hundreds or thousands of participantes, wich is addressed to professionals of a discipline or knowledge field, to disseminate, discuss and exchange information about recent advances. It includes three subprograms: updating, education and free communications. Bibliometrics sta- tistically analyzes the information recorded in scientific publications. Three bibliometric indica- tors have been proposed for congressess: quantitative, qualitative and scientific evidence ones. The aim of this work has been to analyze, through quantitative bibliometric indicators, the communications submitted at the Congreso Nacional Bioquímico of Confederación Unificada Bioquímica de la República Argentina (CUBRA). The analysis was done on the communications submitted at congresses held in Tucumán 1997, Huerta Grande 1999, Bariloche 2001, Posadas 2003 and San Juan 2005. A total of388 communications were presented, all of them as posters. Median was 4 authors per communication. The main topical areas were Clinical Chemistry (including Endocrinology and Acid Base/Blood Gases, 45.4%) and Microbiology (including Bacteriology Parasitology Mycology and Virology 21.1%). A total of 34.3% came from universities, 27.1% of hospitals and 23.7% in collaboration from 2 institutions, being the main participation of Universidad de Buenos Aires (n=35, 9.0%), Fundación Bioquímica Argentina (n=30, 7.7%) and Universidad Nacional de Tucumán (n=26, 6.7%).Facultad de Ciencias ExactasFacultad de Humanidades y Ciencias de la Educació