A New Algorithm for the Retrieval of Sun Induced Chlorophyll Fluorescence of Water Bodies Exploiting the Detailed Spectral Shape of Water-Leaving Radiance

Sun induced chlorophyll fluorescence (SICF) emitted by phytoplankton provides considerable insights into the vital role of the carbon productivity of the earth's aquatic ecosystems. However, the SICF signal leaving a water body is highly affected by the high spectral variability of its optically active constituents. To disentangle the SICF emission from the water-leaving radiance, a new high spectral resolution retrieval algorithm is presented, which significantly improves the fluorescence line height (FLH) method commonly used so far. The proposed algorithm retrieves the reflectance without SICF contribution by the extrapolation of the reflectance from the adjacent regions. Then, the SICF emission curve is obtained as the difference of the reflectance with SICF, the one actually obtained by any remote sensor (apparent reflectance), and the reflectance without SICF, the one estimated by the algorithm (true reflectance). The algorithm first normalizes the reflectance spectrum at 780 nm, following the similarity index approximation, to minimize the variability due to other optically active constituents different from chlorophyll. Then, the true reflectance is estimated empirically from the normalized reflectance at three wavelengths using a machine learning regression algorithm (MLRA) and a cubic spline fitting adjustment. Two large reflectance databases, representing a wide range of coastal and ocean water components and scattering conditions, were independently simulated with the radiative transfer model HydroLight and used for training and validation of the MLRA fitting strategy. The best results for the high spectral resolution SICF retrieval were obtained using support vector regression, with relative errors lower than 2% for the SICF peak value in 81% of the samples. This represents a significant improvement with respect to the classic FLH algorithm, applied for OLCI bands, for which the relative errors were higher than 40% in 59% of the samples

Determinación de componentes ópticamente activos en aguas continentales a partir de imágenes Landsat-8

 Para investigar las nuevas posibilidades que abre la misión Landsat-8 en los estudios calidad de las aguas, se generó, mediante el modelo de transferencia radiativa HydroLight, una extensa base de datos de reflectividades, simuladas a partir de un amplio rango de concentraciones de constituyentes ópticamente activos de los cuerpos de agua. Con los datos simulados se calcularon índices de bandas espectrales de Landsat-8, a partir de los cuales se obtuvieron modelos de regresión para la estimación de la transparencia del agua y la concentración de clorofila-a. Para mejorar la capacidad predictiva de los modelos se realizó una clasificación previa de los espectros basada en su forma espectral. Los modelos fueron validados utilizando datos medidos en varios lagos de España, destacando que, incluso en aguas claras con baja concentración de clorofila-a, fue posible estimar las variables consideradas con un error aceptable para la mayoría de las posibles aplicaciones de los mapas de calidad. La aplicación de estos modelos supone un avance en el estudio de la calidad de las aguas continentales, ya que la resolución espacial de Landsat-8 (<30 m) permite estudiar cuerpos de agua de poca superficie, con un tiempo de revisita mínimo de 16 días

Assessment of possibilities for demand response resources identification in small and medium customer segments

The objective of this research is to show the capacity of Self-Organizing Maps to classify customer and their response potential from electrical demand databases with the help of Non-Parametric Estimation and Physically Load Based modelling as support tools. The searching of customer suitability is focussed to real time products, whose interest is growing in developed countries. In this way customer demand and response have been tested and compared with energy price curves extracting patterns from these curves. Results show the capability of this approach to improve data management and select coherent policies to accomplish cleared demand offers amongst different prices scenarios in an easy way.This work was supported by Ministerio de Educación y Ciencia (Spain) and by EU Sixth Framework Program (research project EU-DEEP SES6-CT-2003-503516)

Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and demand Response

[EN] The objectives of improving the efficiency, and integration, of renewable sources by 2030-2050 are complex in practice and should be linked to an increase of demand-side flexibility. The main challenges to achieving this flexibility are the lack of incentives and an adequate framework. For instance, customers' revenue is usually low, the volatility of prices is high and there is not any practical feedback to customers from smart meters. The possibility of increasing customer revenue could reduce the uncertainty with respect to economic concerns, improving investments in efficiency, enabling technology and thus, engaging more customers in these policies. This objective could be achieved by the participation of customers in several markets. Moreover, Demand Response and Energy Efficiency can share ICT technologies but this participation needs to perform an aggregation of demand. The idea of this paper is to present some methodologies for facilitating the definition and evaluation of energy versus cost curves; and subsequently to estimate potential revenues due to Demand Response. This can be accomplished by models that estimate: demand and energy aggregation; economic opportunities and benefits; impacts on customer convenience; customer feedback and price analysis. By doing so, we would have comprehensive information that can help customers and aggregators to define energy packages and their monetary value with the objective of fostering their market participation.This work was supported by the Ministerio de Economia, Industria y Competitividad (Spanish Government) under research projects ENE2015-70032-REDT, ENE-2016-78509-C3-1-P&2-P and EU FEDER funds. Authors have also received funds from these grants for covering the costs to publish in open access.Gabaldón, A.; Álvarez, C.; Ruiz-Abellón, M.; Guillamón, A.; Valero-Verdú, S.; Molina, R.; Garcia-Garre, A. (2018). Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and demand Response. Sustainability. 10(2):1-27. https://doi.org/10.3390/su10020483S12710

Towards the Combination of C2RCC Processors for Improving Water Quality Retrieval in Inland and Coastal Areas

Sentinel-2 offers great potential for monitoring water quality in inland and coastal waters. However, atmospheric correction in these waters is challenging, and there is no standardized approach yet, but different methods coexist under constant development. The atmospheric correction Case 2 Regional Coast Colour (C2RCC) processor has been recently updated with the C2X-COMPLEX (C2XC). This study is one of the first attempts at exploring its performance, in comparison with C2RCC and C2X, in inland and coastal waters in the east of the Iberian Peninsula, in retrieving water surface reflectance and estimating chlorophyll-a ([Chl-a]), total suspended matter ([TSM]), and Secchi disk depth (ZSD). The relationship between in situ ZSD and Kd_z90max product (i.e., the depth of the water column from which 90% of the water-leaving irradiance is derived) of the C2RCC processors demonstrated the potential of this product for estimating water clarity (r > 0.75). However, [TSM] and [Chl-a] derived from the different processors with default calibration factors were not suitable within the targeted scenarios, requiring recalibration based on optical water types or a shift to dynamic algorithm blending approaches. This would benefit from switching between C2RCC and C2XC, which extends the potential for improving surface reflectance estimates to a wide range of scenarios and suggests a promising future for C2-Nets in operational monitoring of water quality.info:eu-repo/semantics/publishedVersio

La Cueva del Ángel (Lucena, Córdoba), a site of the middle and early pleistocene in the south of the Iberian Peninsula

En este artículo presentamos un avance de los trabajos realizados en un nuevo yacimiento paleolítico del sur de la Península Ibérica: la Cueva del Ángel (Lucena, Córdoba). Desde el descubrimiento en 1995 de su potencial arqueológico, se ha excavado durante cuatro campañas y, hasta el momento, presenta un corte estratigráfico de unos 5 metros de potencia. Paralelamente se analiza la tecnología y tipología, la fauna, la geología de la cavidad y su relleno sedimentario. La fauna, la industria lítica y las dataciones absolutas sitúan el yacimiento en el Pleistoceno medio y el Pleistoceno superior antiguo; lo que hace que esta cueva sea excepcional en la Península Ibérica.In this paper we offer a preview of the excavations of a Palaeolithic site in the southern Iberian Peninsula: the Cueva del Ángel (Lucena, Cordoba). Since 1995, year in which its archaeological potential was discovered, there have been four excavation campaigns and there is now a 5-meter deep stratigraphic sequence. Together with the on-site excavations, there is also the technological and typological analysis of the lithic industry, on-going zoological study, as well as a geological approach, both of the cavity and the sedimentary deposit that filled it. The fauna and lithic industry recovered, together with the absolute dating offered by the stratigraphie sequence, allow us to conclude that we are studying a Middle and Old Upper Pleistocene, which makes this cave an exceptional site in the Iberian Peninsula

Proyecto Jous. Temperaturas mínimas absolutas en la cordillera cantábrica y su relación con las piscinas de aire frío

Ponencia presentada en: XXXV Jornadas Científicas de la AME y el XIX Encuentro Hispano Luso de Meteorología celebrado en León, del 5 al 7 de marzo de 2018.Una piscina de aire frío o CAP (Cold-Air Pool en la bibliografía inglesa) es una acumulación de aire frío en una depresión del terreno. Las CAPs están generalmente asociadas a tiempo estable, predominio de altas presiones, vientos flojos y cielos despejados. Suelen ocurrir durante la noche, por enfriamiento radiativo de la capa de aire en contacto con el suelo, que fluye entonces a favor de la pendiente acumulándose en el fondo de depresiones glaciokársticas ciegas, como las dolinas típicas de los Picos de Europa, produciéndose los llamados vientos catabáticos o corrientes de drenaje o gravedad. En este trabajo se presentan los resultados de 5 años de medidas de la temperatura en 3 dolinas y 3 poljés en el entorno de Picos de Europa y sus cordilleras prelitorales, en las que se registran diferentes tipos de CAPs

“Viceversos Socio-arquitectónicos”. Tentativas metodológicas para ampliar márgenes disciplinares en Arquitectura y Sociología

El Trabajo de la Red reflexiona acerca de modos de retro-alimentar las prácticas docentes arquitectónicas y sociológicas con metodologías aparentemente exclusivas de cada una de ellas. La Red está formada por investigadores docentes y estudiantes de ambas ramas de conocimiento y acaba cristalizando en una serie de acciones para los cuales los miembros de la red son ponentes u observadores-narradores. Tras una serie de reuniones introductorias llevadas a cabo desde finales de 2013, la escenificación de los acuerdos se realizó el 6 de marzo de 2014 entorno a una mesa tapizada con la cartografía de Alicante y Murcia en el aula 4 del Politécnico IV de la UA. En ella, los ponentes fueron explicando sus propuestas mientras colocaban unos indicadores en el mapa de la región de Murcia y Alicante a la espera de adhesiones para formar grupos. Coincidiendo con el final del curso académico, las propuestas de análisis tuvieron lugar y son expuestas, resumidamente, en esta memoria de Red

Impact of Spectral Resolution on Quantifying Cyanobacteria in Lakes and Reservoirs: A Machine-Learning Assessment

Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large ( N=905 ) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( Rrs ) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to Rrs spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ∼73 % and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach