Search

Digital relations are deeply transforming our lives : from the nature of political participation to the relationship between digital and non-digital environments ; from the reorganization of the public sphere to the ethics of responsibility, transparency or inclusiveness. We are witnessing fundamental changes in the infrastructures of democracy and the emergence of new forms of digital citizenship.

Challenge 9.-- Coordinators: José Pintado Valverde (IIM, CSIC), Ana Crespo Solana (IH-CCHS, CSIC).-- 20 pages, 4 figures., The Ocean has shaped human societies, providing resources and ways of communication, trade, exploration and expansion. Understanding the interactions with Society in the past and the present, is essential to tackle the challenges that face the future of the Ocean. With that aim, this chapter develops the consilience between Ocean Science, Social Sciences and Humanities, leading to the integration of diverse methodologies in an interdisciplinary framework. This holistic approach will be used to increase the knowledge and understanding of the interactions of the Oceans with Society by integrating digital and historical data, and natural and cultural heritage management and protection; connecting Ocean and Cultural Heritage Literacy to promote social change and citizen participation in research; developing interdisciplinary knowledge to base Governance and Management and to foster Sustainable Blue Economy, bridging Local and Indigenous Knowledge with Science-based knowledge

Los usos del suelo y su relación con factores socio-económicos son un aspecto clave en la gestión de incendios forestales. Este estudio analiza la ocurrencia de incendios forestales en el período 2005-2010 utilizando como variables explicativas las zonas de contacto entre usos del suelo (interfaces: agrícola-forestal (IAF), urbano-forestal (IUF) y pasto-forestal (IPF)) por su relación con la ocurrencia de incendios en España, calculadas a partir de mapas de usos del suelo de Climate Change Initiative-Land Cover. Se utilizó MaxEnt para generar dos modelos predictivos (general y específico) en Zamora y Madrid. En el modelo general, la IAF contribuyó más en Zamora y la IUF en Madrid. El modelo específico mejoró los ajustes generales en ambas provincias, los porcentajes de acierto en Zamora y la discriminación espacial del riesgo, optimizando las potenciales actuaciones dirigidas a la prevención., El presente estudio se ha desarrollado en el marco del proyecto LUC4FIRE de la convocatoria de Jóvenes Investigadores (JIN) del MINECO (CSO2015-73407-JIN) y gracias al programa de Garantía Juvenil de la Comunidad de Madrid (CAMPD_MAD_CCHS_001).

[EN] In this article we study forest fires in the Autonomous Community of Madrid into two periods, 1989-1995 and 2007-2010, to characterize and compare the fire regime. We also analyse the selectivity action of fire in relation to the land uses of the region. Fire data was obtained from Landsat (TM / ETM +) while the land use information was obtained from CORINE Land Cover maps (1990 and 2006). Fire regime was defined through seven indicators. Results showed a clear decreasing of fire activity between the two periods, most important in the burned area (78%) than in the number of fires (16%). The analysis of the fire selectivity on land uses was based on the Manly´s selection ratio. In the period 1989-1995 a higher incidence in coniferous forests and, less important, in shrubs was observed. In the period 2007-2010 the incidence was higher in grassland areas. The analysis showed the important role that the artificial/forest interface plays in the fire occurrence, especially in 2007-2010, [ES] En este artículo se analizan los incendios forestales ocurridos en la Comunidad Autónoma de Madrid en dos períodos, 1989-1995 y 2007-2010, con el objetivo de caracterizar y comparar el régimen de incendios en cada uno de ellos, así como la acción selectiva del fuego en relación con los usos del suelo. Los datos de incendios se generaron a partir de imágenes Landsat (TM/ETM+) mientras que la información sobre usos del suelo se obtuvo de los mapas CORINE Land Cover (1990 y 2006). El régimen de incendios fue definido a través de siete indicadores. Los resultados mostraron una clara reducción de la incidencia de incendios con un 16% menos de incendios y un 78% menos de superficie quemada en el segundo período respecto al primero. El análisis del carácter selectivo del fuego sobre los usos del suelo se basó en el cociente de selección de Manly. En el período 1989-1995 destacó una mayor incidencia en bosques de coníferas y, en menor medida, en matorrales. En el período 2007-2010, la incidencia fue mayor en las zonas de pastos. El análisis mostró el importante papel de la interfaz entre usos artificiales y forestales en la ocurrencia de incendios, especialmente en el período 2007-2010., Este trabajo ha sido desarrollado en el contexto del proyecto FUME “Forest fires under climate, social and economic changes in Europe, the Mediterranean and other fire-affected areas of the World” (grant agreement n°243888) financiado por el 7º Programa Marco de la Unión Europea. Agradecemos al United States Geological Survey la posibilidad de acceder de forma gratuita a la serie histórica de imágenes Landsat. También queremos expresar nuestra gratitud al Ministerio de Agricultura, Alimentación y Medio Ambiente por el acceso a la información de su base de datos sobre los incendios forestales en España, así como, al Instituto de Estadística de la Comunidad Autónoma de Madrid y a su banco de datos “ALMUDENA”

Se analizan los efectos de la agregación espacial de variables espectrales y temporal de flujos de carbono sobre la estimación de la productividad primaria bruta en un ecosistema de dehesa. Para ello se hace uso de una serie temporal de imágenes hiperespectrales de alta resolución espacial sobre el área de influencia de varias torres de flujo. Los diferentes modelos empleados revelan diferencias relacionadas con la agregación temporal de los datos de flujos, mientras que las relacionadas con la agregación espacial de los datos espectrales son menos relevantes., Este trabajo ha sido financiado por los proyectos BIOSPEC (CGL2008-02301/CLI, Ministerio de Ciencia en Innovación) y FLUXPEC (CGL2012-34383, Ministerio de Economía y Competitividad). Agradecemos a la COST Action ES1309 OPTIMISE la financiación de una STMS. Agradecemos también la colaboración del personal de SpecLab-CSIC, CEAM, Universidad de Alcalá, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Universidad de Zaragoza, Universidad de Milano- Bicocca y Max Planck Institute for Biogeochemistry.

[EN] In this study we analyzed the potential of airborne hyperspectral images acquired by the CASI sensor (Compact Airborne Spectrographic Imager) to estimate water content in the grass layer of a dehesa ecosystem. It was estimated by means of biophysical variables as Canopy Water Content (CWC), Fuel Moisture Content (FMC) and Equivalent Water Thickness (EWT) calculated from vegetation samples collected simultaneously to image acquisition. Two different field sampling strategies have been tested. First method collects all plants in 25x25cm quadrants and selects a fraction of the sample to be processed in the laboratory. In the second method the worker selects a small sample in the field. This subsample should be representative of the main one and will be completely processed in the laboratory. Afterwards linear relationships between the biophysical variables and twenty spectral indices from literature and from Normalized Difference Indices (NDIs-combination all sensor bands) are analyzed. The results show that the combination of specific bands in the form of NDI performs better than the spectral indices proposed in the literature. The regression models showed maximum correlation values (R2max) of 0.78 in the estimation of water content from NDIs. This value decrease to 0.53 for indices proposed in the literature. Clear differences were found in the correlation values when comparing the different sampling strategies. In general, lower correlation values were found when sampling methods require subjective decision on the selection in the field of plants that composes the sample. Despite of the limited outreach of the method used, the results suggest that this could be successfully applied in circumstances when information is limited and variables are not physically related., [ES] En este trabajo se analiza el potencial del sensor aeroportado CASI (Compact Airborne Spectrographic Imager) para estimar el contenido en humedad de la cubierta herbácea de un área de dehesa. Éste fue cuantificado mediante las variables Canopy Water Content (CWC), Fuel Moisture Content (FMC) y Equivalent Water Thickness (EWT), calculadas a partir de muestras de vegetación recolectadas en campo de forma simultánea a la adquisición de datos por parte del sensor. Se comparan dos protocolos diferentes para la estimación de estas variables mediante muestreos destructivos: en el primero se muestrea toda la vegetación en un cuadrante de 25x25 cm y posteriormente se selecciona una parte de la muestra para su procesado en laboratorio; en el segundo el operador selecciona en campo una muestra más pequeña que considera representativa de la muestra anterior y que es procesada en su totalidad. Posteriormente se analizan las relaciones lineales entre estas variables y veinte índices espectrales extraídos de la literatura así como todos los índices de diferencia normalizados (NDIs) posibles resultantes de combinar pares de bandas del sensor CASI. Los resultados indican que la exploración de todas las posibles combinaciones de bandas en forma de NDI permite obtener coeficientes de correlación más elevados con las variables biofísicas medidas en terreno (R2máx= 0.78) que los índices extraídos de la literatura (R2máx= 0.53). Los valores de ajuste obtenidos fueron diferentes en función del tipo de muestreo realizado; siendo por lo general inferiores cuando el muestreo incluye decisiones subjetivas por parte del operador respecto a la selección en campo de los individuos que integran la muestra. A pesar de la limitación del enfoque empleado, los resultados sugieren su aplicabilidad a estudios con información limitada y no relacionada mediante procesos físicos.

Las dehesas son sistemas agro-forestales en los que se producen complejos mecanismos de intercambio de carbono y agua debido a la presencia de estratos de vegetación diferenciados (pastizal, arbolado y matorral), en un marco climático caracterizado por periodos de sequía. Dichos componentes no se dan en las mismas proporciones constituyendo complejos mosaicos en función del tipo de manejo, la densidad del arbolado y el momento de año. En este contexto, una de las variables clave en la parametrización del balance energético entre el suelo y atmósfera es la temperatura de superficie (Ts). El análisis de sus patrones espacio-temporales es importante para valorar el papel de la dehesa como sumidero de carbono, por cuanto la Ts controla la velocidad de procesos metabólicos en la vegetación y la descomposición de la materia orgánica del suelo, influyendo de esta manera en la transferencia neta del carbono hacia la atmósfera. Este trabajo analiza la variación espacio-temporal de la Ts en función de la densidad y tipo de arbolado. Utilizando como referencia el SIOSE (PNOT) se analizan las diferencias espacio-temporales de los valores de Ts, calculados a partir de una serie multitemporal de imágenes Landsat-5 TM. En este trabajo se presentan los resultados cartográficos en 14 fechas a lo largo del período de 2009-2011. Se han detectado diferencias estadísticamente significativas en los valores de Ts en función de la densidad del arbolado, así que los valores de Ts más elevados se localizan en las dehesas con menor cubierta de Quercus ilex y de especies arbustivas. Debido a la mayor variabilidad eco-fisiológica del estrato herbáceo, las diferencias medias más acusadas se registran en las imágenes de verano., Este trabajo se ha realizado en el marco del proyecto FLUXPEC (CGL2012-34383) financiado por el Ministerio de Economía y Competitividad. Los autores también agradecen la financiación de la investigación predoctoral de Lidia Vlassova por parte de SENESCYT-Ecuador.

En el contexto de los proyectos BIOSPEC y FLUXPEC (http://www.lineas.cchs.csic.es/fluxpec/), se han realizado mediciones espectrales y de variables biofísicas a nivel de hoja en el dosel arbóreo de una dehesa de encina (Quercus ilex) durante cuatro períodos vegetativos. Se han llevado a cabo mediciones de reflectividad bi-cónica de hoja intacta, LMA, contenido de agua, nutrientes (N, P, K, Ca, Mg, Mn, Fe, y Zn) y pigmentos. Las mediciones espectrales se han relacionado con las variables biofísicas mediante análisis de regresión múltiple stepwise y regresión de mínimos cuadrados parciales. Estos análisis han permitido identificar las bandas espectrales que explican la evolución de las variables biofísicas y estimar los contenidos de nutrientes a lo largo del proceso de maduración de las hojas en la copa. Se han obtenido estimaciones significativas para la mayoría de las variables foliares estudiadas. Las longitudes de onda con mayor contribución aparecen en la zona del eje rojo, el SWIR y la región verde del visible.

Presented at the General Assembly of the European Geosciences Union, Vienna 07-12 April 2013, Understanding the interaction between natural and socio-economic factors that determine fire regime is essential to make accurate projections and impact assessments. However, this requires having accurate historical, systematic, homogeneous and spatially explicit information on fire occurrence. Fire databases usually have serious limitations in this regard; therefore other sources of information, such as remote sensing, have emerged as alternatives to generate optimal fire maps on various spatial and temporal scales. Several national and international projects work in order to generate information to study the factors that determine the current fire regime and its future evolution. This work is included in the framework of the project "Forest fires under climate, social and economic Changes in Europe, the Mediterranean and other fire-affected areas of the World" (FUME http://www.fumeproject.eu), which aims to study the changes and factors related to fire regimes through time to determine the potential impacts on vegetation in Mediterranean regions and concrete steps to address future risk scenarios., We analyzed the changes in the fire regime in Madrid region (Spain) in the past three decades (1984-2010) and its relation to land use changes. We identified and mapped fires that have occurred in the region during those years using Landsat satellite images by combining digital techniques and visual analysis. The results show a clear cyclical behaviour of the fire, with years of high incidence (as 1985, 2000 and 2003, highlighted by the number of fires and the area concerned, over 2000 ha) followed by another with a clear occurrence decrease. At the same time, we analyzed the land use changes that have occurred in Madrid region between the early 80s and mid-2000s using as reference the CORINE Land-cover maps (1990, 2000 and 2006) and the Vegetation and Land Use map of the Community of Madrid, 1982., We studied the relationship between fire regimes and observed land-use and land-cover changes in the periods analyzed, it was determined that between years 1984 and 2006 most of the burned area remained pre-fire cover type (above 80% of the area). However, in areas that experienced change, the most important transitions were recorded in wooded areas, especially conifers, which became shrubs or sparsely vegetated areas, followed by non-irrigated crops, which were replaced by grasslands or industrial areas, and sparse vegetation which changed to shrubs. Finally, the analysis of land-use changes over burned areas situated shrubland as the most favored type of cover, either as a result of a vegetative degradation process after intense burning of wooded areas, especially conifers, or as stage of natural increase in areas previously covered by sparsely vegetation.

Mediterranean ecosystems constitute a potential “hot spot†for assessing impact of climate change; but they are also characterized for a large heterogeneity which complicates the use of remote sensing tools for monitoring carbon fluxes in these particular ecosystems. This is the case of the wooded grasslands or savannas, which combine vegetation types structurally and physiologically very different. We have simulated the estimation of Gross Primary Production (GPP) in a Mediterranean savanna (dehesa) through up-scaling spectral information from leaf/canopy to ecosystem level by using Radiative Transfer Models (RTM). Different predictive models have been tested by simulating Landsat 5 TM and Sentinel-2 spectral bands., Field works were carried out in Majadas del Tiétar, (Cáceres, Spain) between May 2009 and April 2011. In the study site grazed grasslands mix up with scattered Holm oaks (tree fraction cover about 20%). Daily GPP and meteorological variables have been measured using Eddy Covariance technique from a flux tower operated by CEAM; moreover, ground spectral data were taken during 20 field campaigns simultaneous to Landsat 5 TM over-passes. In each campaign, an ASD Fieldspec® spectroradiometer (ASD inc., Boulder, CO, USA) was used to measure canopy reflectance from 12 grassland plots of 25 m x 25 m and leaf reflectance from up to 10 trees surrounding the flux tower. Current and previous year Holm oak leaves (up to 12 of each type per tree and sampling date) were measured using a plant probe and a leaf clip of the same spectroradiometer. The coupled PROSPECT-5 and SAIL models were used to simulate ecosystem reflectance as a linear combination of the measured grassland and the simulated tree canopy reflectance’s fraction cover. Simulated reflectance was resampled to the Landsat 5TM and Sentinel-2 spectral bands and was validated using Landsat 5 TM images simultaneously acquired and radiometrically corrected using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) system. Eventually, three different models based on Vegetation Indices (VI) computed from each sensor´s bands and the Photosynthetically Active Radiation (PAR) measured in the flux tower were used to estimate GPP., Results show a high agreement between the simulated ecosystem reflectance and the Landsat 5 TM imagery (r2 ranged between 0.94 and 1.00 for the optical bands). GPP models exclusively based on VI showed the least predictive capabilities (r2 ≤ 0.36; RRMSE Є [65.00%, 74.29%]).whereas those models where GPP is a linear function of the product VI x PAR achieved larger correlation coefficients (r2 Є [0.74, 0.88] and lower errors (RMSE Є [36.40%, 58.79%]). The most accurate predictions were achieved by models where GPP is a linear combination of a VI that is multiplied by PAR (r2 Є [0.78, 0.88]; RMSE Є [34.83%, 57.30%]). When PAR was included, the model based in the green Normalized Difference Vegetation Index (NDVI) calculated from the Sentinel-2’s 4th and 10th bands casted the least reliable estimates (r2 = 0.80; RRMSE = 58.79%). On the contrary, the best predictions were achieved using the NDVI computed from the Sentinel-2’s 5th and 6th bands (r2 = 0.88; RRMSE = 34.83%)., We conclude that a wooded grassland ecosystem level reflectance can be simulated from ground hyperspectral measurements using RTM; at least when spectral resolution is degraded to the coarser features of multispectral remote sensors such as Landsat 5 TM. Moreover, daily GPP can be estimated with an acceptable accuracy (RRMSE ~35%) from Sentinel-2 imagery using vegetation spectral indices; however incident PAR must be taken into account. Since the revisit time of this Sentinel-2 over the Mediterranean basin would be lower than 5 or 10 days; Sentinel-2 could largely improve the estimation of GPP in Mediterranean ecosystems, providing acceptable information in terms of temporal and spatial resolution and uncertainty.

Hyperspectral sensors are increasingly being used to continuously collect optical data that can be related to carbon and water ecosystem exchanges. Automated proximal sensing can solve the temporal mismatch existing between the periodic remote observations and the continuous acquisition of the Eddy Covariance systems, and can provide also tools for the up-scaling. However, characterization of spectroradiometers used continuously outdoors is necessary to assure data quality; because environmental conditions can influence the instrumentation performance, but also are drivers of the vegetation physiology estimated through the optical measurements. We describe the laboratory characterization previous to field deployment of a Unispec-DC, a dual channel spectroradiometer integrated in an automated multi-angular system (AMSPEC-MED). The instrument operates in a savanna ecosystem in Majadas del Tiétar, Cáceres, Spain, under a wide range of temperatures, radiation levels, illumination angles and internal settings., Laboratory experiments were conducted in order to characterize several features of the spectroradiometer and to estimate correction models. Dark current, the signal produced by thermally generated electrons, was modelled as a function of the temperature and the integration time set. Thermal sensitivity, the sensor’s responsivity dependence on temperature, and spectral calibration were also modeled as a function of temperature. Moreover, non-linearities, deviations from a linear relationship between the input radiance and the output signal, were characterized as a function of the grey level and (innovatively) of the integration time. Since a cosine receptor is used to sample irradiance; we also modeled the diffuser directional response deviations from the ideal response, the cosine of the incident angle of illumination., Calibrated models are used to correct the Hemispherical-Conical Reflectance Factors (HCRF) measured in a continuous mode in the field, and the influence of each model is discussed. Results suggest that effects of thermal sensitivity and non-linearity partially cancel out when reflectance is computed using channel A (irradiance) and B (radiance) ratio, however, in the case of non-linearities, this may not occur when signals are very different in each channel. Dark measurements showed a bias inversely dependent on temperature that was added to dark current. Wavelength calibration showed a dependency on temperature; however, this was small considering the spectral features of the instrument (Full Width at Half Maximum~10nm, interval sampling ~3.3nm). Finally, the cosine directional response correction model produced the largest differences between he corrected and the non-corrected HCRF. This correction requires accounting for the diffuse-to-global radiation ratios. Differences between corrected and non-corrected reflectances were larger in the near infrared region than in the visible. We conclude that characterization of spectroradiometers installed outdoors in automated continuous systems is necessary to ensure comparability and quality of data. Thermal insulation of the instruments could reduce errors related with dark current, thermal sensitivity and wavelength calibration; however these still should have to be known in order to compare with data from other instruments. Moreover, non-linearities and directional response of the cosine receptors would have to still be corrected in order to achieve reliable measurements under different ranges of irradiance and sun elevation.

Tommaso Julitta’s Short Term Scientific Mission was funded by the Cost Action ES0903 – Eurospec. Javier Pacheco-Labrador’s stay was partially funded by the Biospec project “Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of Global Change” (CGL2008-02301/CLI, Ministry of Science and Innovation).