41 research outputs found

    Exploitation of SAR and optical Sentinel data to detect rice crop and estimate seasonal dynamics of leaf area index

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    This paper presents and evaluates multitemporal LAI estimates derived from Sentinel-2A data on rice cultivated area identified using time series of Sentinel-1A images over the main European rice districts for the 2016 crop season. This study combines the information conveyed by Sentinel-1A and Sentinel-2A into a high-resolution LAI retrieval chain. Rice crop was detected using an operational multi-temporal rule-based algorithm, and LAI estimates were obtained by inverting the PROSAIL radiative transfer model with Gaussian process regression. Direct validation was performed with in situ LAI measurements acquired in coordinated field campaigns in three countries (Italy, Spain and Greece). Results showed high consistency between estimates and ground measurements, revealing high correlations (R^2>0.93) and good accuracies (RMSE<0.83, rRMSE_m<23.6% and rRMSE_r<16.6%) in all cases. Sentinel-2A estimates were compared with Landsat-8 showing high spatial consistency between estimates over the three areas. The possibility to exploit seasonally-updated crop mask exploiting Sentinel-1A data and the temporal consistency between Sentinel-2A and Landsat-7/8 LAI time series demonstrates the feasibility of deriving operationally high spatial-temporal decametric multi-sensor LAI time series useful for crop monitoring

    Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale

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    The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice monitoring. The first is aimed at providing information concerning the behavior of the current season at regional/rice district scale, while the second is dedicated to provide farmers with field-scale data useful to support more efficient and environmentally friendly crop practices. In this contribution, we describe the main characteristics of the system, in terms of overall architecture, technological solutions adopted, characteristics of the developed products, and functionalities provided to end users. Peculiarities of the system reside in its ability to cope with the needs of different stakeholders within a common platform, and in a tight integration between EO data processing and information retrieval, crop modeling, in situ data collection, and information dissemination. The ERMES system has been operationally tested in three European rice-producing countries (Italy, Spain, and Greece) during growing seasons 2015 and 2016, providing a great amount of near-real-time information concerning rice crops. Highlights of significant results are provided, with particular focus on real-world applications of ERMES products and services. Although developed with focus on European rice cultivations, solutions implemented in the ERMES system can be, and are already being, adapted to other crops and/or areas of the world, thus making it a valuable testing bed for the development of advanced, integrated agricultural monitoring systems

    The commissioning of the CUORE experiment: the mini-tower run

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    CUORE is a ton-scale experiment approaching the data taking phase in Gran Sasso National Laboratory. Its primary goal is to search for the neutrinoless double-beta decay in 130Te using 988 crystals of tellurim dioxide. The crystals are operated as bolometers at about 10 mK taking advantage of one of the largest dilution cryostat ever built. Concluded in March 2016, the cryostat commissioning consisted in a sequence of cool down runs each one integrating new parts of the apparatus. The last run was performed with the fully configured cryostat and the thermal load at 4 K reached the impressive mass of about 14 tons. During that run the base temperature of 6.3 mK was reached and maintained for more than 70 days. An array of 8 crystals, called mini-tower, was used to check bolometers operation, readout electronics and DAQ. Results will be presented in terms of cooling power, electronic noise, energy resolution and preliminary background measurements

    Results from the Cuore Experiment

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    The Cryogenic Underground Observatory for Rare Events (CUORE) is the first bolometric experiment searching for neutrinoless double beta decay that has been able to reach the 1-ton scale. The detector consists of an array of 988 TeO2 crystals arranged in a cylindrical compact structure of 19 towers, each of them made of 52 crystals. The construction of the experiment was completed in August 2016 and the data taking started in spring 2017 after a period of commissioning and tests. In this work we present the neutrinoless double beta decay results of CUORE from examining a total TeO2 exposure of 86.3kg yr, characterized by an effective energy resolution of 7.7 keV FWHM and a background in the region of interest of 0.014 counts/ (keV kg yr). In this physics run, CUORE placed a lower limit on the decay half- life of neutrinoless double beta decay of 130Te > 1.3.1025 yr (90% C. L.). Moreover, an analysis of the background of the experiment is presented as well as the measurement of the 130Te 2vo3p decay with a resulting half- life of T2 2. [7.9 :- 0.1 (stat.) :- 0.2 (syst.)] x 10(20) yr which is the most precise measurement of the half- life and compatible with previous results

    A Weekly Indicator of Surface Moisture Status from Satellite Data for Operational Monitoring of Crop Conditions

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    The triangle method has been applied to derive a weekly indicator of evaporative fraction on vegetated areas in a temperate region in Northern Italy. Daily MODIS Aqua Land Surface Temperature (MYD11A1) data has been combined with air temperature maps and 8-day composite MODIS NDVI (MOD13Q1/MYD13Q1) data to estimate the Evaporative Fraction (EF) at 1 km resolution, on a daily basis. Measurements at two eddy covariance towers located within the study area have been exploited to assess the reliability of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator (EFw) were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EFw showed a temporal behavior consistent with growing cycles and agro-practices of the main crops cultivated in the study area (rice, forages and corn). Comparison with official regional corn yield data showed that variations in EFw cumulated over summer are related with crop production shortages induced by water scarcity. These results suggest that weekly-averaged EF estimated from MODIS data is sensible to water stress conditions and can be used as an indicator of crops’ moisture conditions at agronomical district level. Advantages and disadvantages of the proposed approach to provide information useful to issue operational near real time bulletins on crop conditions at regional scale are discussed

    Caratterizzazione di materiali plastici: misure locali di deformazione per la simulazione a elementi finiti di problemi di impatto

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    Questo articolo si propone di illustrare l’importanza dell’utilizzo di metodi per la misura delle proprietà locali del materiale per determinarne la legge di comportamento. Vengono di seguito presentati alcuni esempi che evidenziano quanto più accurate e realistiche siano le simulazioni numeriche di test di trazione ad alta velocità su provini di poliolefine, quando vengano utilizzate proprietà dei materiali rilevate con misure locali, utilizzando metodi ottici. La disponibilità di misure locali e più accurate evidenzia come sia necessario che nei codici di calcolo commerciali vengano implementate delle leggi di materiale più sofisticate di quelle disponibili attualmente, che sono state per lo più originariamente sviluppate per materiali metallici, e dunque non riescono sempre a predire correttamente il comportamento dei componenti in materiali polimerici

    Sentinel-2 estimation of CNC and LAI in rice cropping system through hybrid approach modelling

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    Earth observation techniques represent a reliable and faster alternative to in-situ measurements by providing spatio-temporal information on crop status. In this framework, a study was conducted to assess the performance of hybrid approaches, either standard (HYB) or exploiting an active learning optimisation strategy (HYB-AL), to estimate leaf area index (LAI) and canopy nitrogen content (CNC) from Sentinel–2 (S2) data, in rice crops. To achieve this, the PROSAILPRO Radiative Transfer Model (RTM) was tested. Results demonstrate that a wide range of rice spectra, simulated according to realistic crop parameters, are reliable when appropriate field background conditions are considered. Simulations were used to train a Gaussian Process Regression (GPR) algorithm. Both cross-validation and validation results showed that HYB-AL approach resulted the best performing retrieval schema. LAI estimation achieved good performance (R2=0.86; RMSE=0.54) and resulted very promising for model application in operational monitoring systems. CNC estimations showed moderate performance (R2=0.63; RMSE=0.89) due to a saturation behaviour limiting the retrieval accuracy for moderate/high CNC values, approximately above 4 [g m−2]. S2 maps of LAI and CNC provided spatio-temporal information in agreement with crop growth, nutritional status and agro-practices applied to the study area, resulting in an important contribution to precision farming applications

    Contributo del telerilevamento da satellite alla comprensione dei fenomeni idrologici del fiume Congo

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    project Geoland2. Congo basin is one of the target area where NARMA has to contribute to the development of AMESD/CEMAC services in support to management of water resources focusing on environmental aspects of watersheds. In this contest and to better understand dynamics that occur in the watershed, an analysis has been conducted on the relation between precipitation, river discharge and vegetation dynamics by exploiting available time series of Earth Observation data. Rainfall dynamics has been described using FEWS-NET RFE estimations, river discharge has been monitored using ENVISAT radar altimeter data provided by LEGOS laboratory and vegetation dynamics have been examined through vegetation indices available from long term series of SPOT¿VGT data. The comparison between river discharge measured at Bangui (Central African Republic), gauging station and radar altimeter virtual station data demonstrated that these data can be used to estimate river discharge. Results on Uelè basin showed that a strong positive correlation is obtained between rain data and river discharge only at the end of the vegetation season when plants have reduced water demand for evapotranspiration and less intercept rain. Trend analysis on the considered time windows are provided and the contribution of these finding for river water alert monitoring system is discussed.JRC.DDG.H.3-Global environement monitorin
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