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The future success of rice farming will lie in developing productive, sustainable, and resilient farming systems in relation to coexistent ecosystems. Thus, accurate information on agricultural practices and grain yield at optimum temporal and spatial scales is crucial. This study evaluates the potential application of Sentinel-2 (S2) to monitor the dynamics of rice fields in two consecutive seasons (2018 and 2019) in the Ebro Delta growing area. For this purpose, time series of four different spectral indices (NDVI, NDWIMF, NDWIGAO, and BSI), derived from smoothed S2 data at 20 m spatial resolution, were generated. Then, a combination of the first and second derivative analysis on the temporal profiles of spectral indices was used to automatically identify key phenology and management features from regional to field scale; and for estimating crop yield at fields. Features extracted from NDVI and NDWIGAO were used for identifying significant phenological stage dates (i.e. Tillering, Heading Date, and Maturity), and field status (i.e. hydroperiod), although the performance of the proposed method at field-scale was limited by S2 data gaps. The absolute minimum of NDWIMF showed great potential for estimating rice yield, including different cultivars (r = - 0.8), and less sensibility to the number of valid images. Sentinel-2 alone cannot assure a consistent phenology monitoring at all fields but demonstrated strong capabilities for studying the performance of rice fields, thus must be considered in the development of new strategies for the management of rice-growing areas. info:eu-repo/semantics/acceptedVersion

Shellfish aquaculture has a major socioeconomic impact on coastal areas, thus it is necessary to develop support tools for its management. In this sense, phytoplankton monitoring is crucial, as it is the main source of food for shellfish farming. The aim of this study was to assess the applicability of Sentinel 2 multispectral imagery (MSI) to monitor the phytoplankton biomass at Ebro Delta bays and to assess its potential as a tool for shellfish management. In situ chlorophyll-a data from Ebro Delta bays (NE Spain) were coupled with several band combination and band ratio spectral indices derived from Sentinel 2A levels 1C and 2A for time-series mapping. The best results (AIC = 72.17, APD < 10%, and MAE < 0.7 mg/m3) were obtained with a simple blue-to-green ratio applied over Rayleigh from Sentinel 2A levels 1C and 2A for time-series mapping. The best results (AIC = 72.17, APD < 10%, and MAE < 0.7 mg/m3) were obtained with a simple blue-to-green ratio applied over Rayleigh corrected images. Sentinel 2–derived maps provided coverage of the farm sites at both bays allowing relating the spatiotemporal distribution of phytoplankton with the environmental forcing under different states of the bays. The applied methodology will be further improved but the results show the potential of using Sentinel 2 MSI imagery as a tool for assessing phytoplankton spatiotemporal dynamics and to encourage better future practices in the management of the aquaculture in Ebro

[EN] Beaches are natural environments of great interest for our society. They go through remarkable changes run by key factors that are interconnected according to the literature. A better understanding of these parameters, such as sediment texture and shoreline variability, would be of a great interest for coastal monitoring and planning. Shorelines of all Landsat 8 (OLI) images available over the course of one year have been obtained for determining the variability that has occurred in different Valencian beaches. Likewise, the relation between shoreline variability and sediment texture has been evaluated, showing that beaches with higher variability over the year have smaller sediment texture, which is also related with gentle slopes, and vice versa. The methodology allows obtaining the shoreline variability, a key parameter of beach morphodynamics, in a semiautomatic way. The variability allows developing a gross estimate of beach texture., [ES] Las playas son entornos naturales de enorme interés para nuestra sociedad. Estos espacios están sometidos a grandes cambios regidos por factores clave fuertemente interrelacionados según la literatura. Un mayor conocimiento de estos parámetros, como la textura del sedimento o la variabilidad de la línea de costa de las playas resultaría de gran interés para la monitorización y gestión de la costa. Se han obtenido las líneas de costa de todas las escenas Landsat 8 (OLI) disponibles a lo largo de un año para, a partir de ellas, determinar la variabilidad de diferentes playas valencianas. Asimismo, se ha evaluado la relación existente entre dicha variabilidad y la textura del sedimento de las playas, mostrando que las playas con mayores cambios en la línea de costa a lo largo del año son aquellas con un tamaño de grano menor, asociado a pendientes más suaves y viceversa. La metodología seguida incluye la obtención de forma semiautomática de la variabilidad de la línea de costa, un parámetro clave de la morfodinámica costera, y a partir de ella la estimación a grandes rasgos de la textura del sedimento de las playas., Este proyecto ha sido realizado con la ayuda de la beca FPU15/04501 concedida por el MECD a C. Cabezas, así como con el proyecto RESETOCOAST (CGL2015- 69906-R) del programa Retos del MINECO. Los autores agradecen el apoyo de la Oficina Técnica DevesaAlbufera.