121 research outputs found

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

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    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

    Funcionalidad familiar y el nivel de autoestima en los estudiantes del nivel primaria. Chao – Virú, 2017

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    Este trabajo de investigación tiene como objetivo general determinar la correlación existente entre funcionalidad familiar y el nivel de autoestima en los estudiantes del nivel primaria, habiéndose realizado para ello un estudio correlacional, empleando en esta investigación el diseño correlacional. Contando con una población estudiantil de 154 y con una muestra de 125 estudiantes. Para la recolección de datos se aplicó la encuesta como técnica y como instrumento se empleó el cuestionario, los mismos que recogieron los siguientes resultados: Como resultado general se obtuvo que la correlación existente entre ambas variables es 0.686 significativa (p<0.01), aplicándose la prueba no paramétrica de Rho de Spearman; en tal sentido se acepta la hipótesis alterna en la que se afirma la existencia de la correlación entre la funcionalidad Familiar y el nivel de autoestima en los Estudiantes del Nivel Primaria de la Institución Educativa “San Francisco de Asís”, Chao -Virú, 2017. En conclusión la funcionalidad familiar está altamente correlacionada con el nivel de autoestima. Por tanto a mejor funcionamiento mayor es el nivel de la autoestima

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

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    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

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

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    Since 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 m3 /m3 ) than LST night (R˜0.45 to 0.80; ubRMSD˜0.04 to 0.07 m3 /m3 ) 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 m3 /m3 ) with a coverage improvement of ~10-20 %.Peer ReviewedPostprint (published version

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

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    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

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

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    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

    Amaranth’s response to two planting distances and population density

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    El objetivo de este estudio fue evaluar el comportamiento de tres genotipos de amaranto, Amaranthus sp.; con la fina­lidad­de utilizarlos en cosecha mecánica. Estos fueron­ sembrados en la Facultad de Agronomía, Universidad Nacional La Pampa en surcos separados a 0,25 y 0,50 m y densidades de 100 x 10 3 , 200 x 10 3 y 400 x 10 3 plantas ha-1. Se midió la altura de las plantas y la radiación fotosinté- ticamente activa a los 30 días después de la siembra (DDS) en la antesis y madurez­fisiológica, así como, el índice de cosecha (IC) y rendimiento de semilla. Estadísti­camente el diseño fue de bloques al azar con 4 réplicas x 3 genotipos x 3 densidades x 2 distancias. No hubo diferencias significativas (P= 0,01) en el IC y rendimiento­en grano (kg ha-1) en los tres genotipos, entre distancias en surcos y densidades­. La inter­cepción solar (IS) a los 30 DDS (51,2%) solo difirió significa­tivamente (P= 0,01) en A. cruentus var. Don Guiem, para la distancia de 0,25 m y 100.000 plantas ha -1 . Las plantas en la madurez no presentaron diferencias para los distintos tratamientos. Las densidades a campo oscilaron entre 50-90 x 10 3 , 90-150 x 10 3 y 150-270 x 10 3 plantas ha -1 , explicando la falta de significancia entre tratamientos.Field studies were conducted to evaluate the behavior of amaranths, Amaranthus sp.; with the purpose of being able to use them in the mechanical crop. Three amaranths were sowed in the Facultad de Agronomía, Universidad Nacional La Pampa in furrows separated to 0,25 and 0,50 m and densities of 100 x 103 ; 200 x 103 and 400 x 103 plants ha-1. The height of plants, photosyntetically active radiation (30 days of the sowing, anthesis and physiological maturity),), harvest index of crop and seed yield were measured. Experimental design was totally randomized blocks: 4 replications x 3 genotypes x 3 densities x 2 distances. There were no significant differences(P= 0,01) in the harvest index of crop and grain yield (expressed in kg ha-1), in the 3 genotypes between distances in furrows and densities. The solar interception at 30 days of the sowing (51,2%), only difered significantly (P= 0,01) in A. cruentus var. Don Guiem for the distance of 0,25 m and 100.000 plants ha-1. At maturity there were not significant different treatments. The densities in the field ranged between 50-90 x 103 , 90-150 x 103 and 150-270 x 103 plants ha-1 which would explain the lack ofsignificance between treatments.Fil: Repollo, Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiarida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiarida; Argentina. Universidad Nacional de La Pampa; ArgentinaFil: Martín de Troiani, Rosa. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Nollemeyer, Elke. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Sánchez, Teresa. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Reinaudi, Nilda. Universidad Nacional de la Pampa. Facultad de Agronomía; Argentin

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

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    [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

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    [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

    Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations

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    The final publication is available at Springer via http://dx.doi.org/10.1016/j.rse.2016.02.048Earth Observation (EO) technology is today at a maturity level that allows deriving operational estimates of Surface Soil Moisture (SSM) from a variety of sensors; yet, such products are provided at present at a coarse spatial and/or temporal resolution, which restricts their use in local or regional scale studies and practical applications. Herein, a methodology to derive SSM estimates from space at previously unattained spatio-temporal resolutions is proposed. The method is based on a variant of thePeer ReviewedPostprint (author's final draft
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