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Influence of Soil Properties on Maize and Wheat Nitrogen Status Assessment from Sentinel-2 Data

Alberto Crema, Mirco Boschetti, Francesco Nutini, Donato Cillis, Raffaele Casa
<span title="2020-07-08">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
The authors would also like to thank Pietro Marino, Paolo Villa, Francesco Mastromauro and Giampiero Ubertini for help with samples analysis and field campaigns.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs12142175">doi:10.3390/rs12142175</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/abbcywphkng7jhldesafrbvwae">fatcat:abbcywphkng7jhldesafrbvwae</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709115255/https://res.mdpi.com/d_attachment/remotesensing/remotesensing-12-02175/article_deploy/remotesensing-12-02175.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1a/80/1a807c712ce8aa647ff9a823e43d205b0d132cc8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs12142175"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Evaporative Fraction as an Indicator of Moisture Condition and Water Stress Status in Semi-Arid Rangeland Ecosystems

Francesco Nutini, Mirco Boschetti, Gabriele Candiani, Stefano Bocchi, Pietro Brivio
<span title="2014-07-07">2014</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Rangeland monitoring services require the capability to investigate vegetation condition and to assess biomass production, especially in areas where local livelihood depends on rangeland status. Remote sensing solutions are strongly recommended, where the systematic acquisition of field data is not feasible and does not guarantee properly describing the spatio-temporal dynamics of wide areas. Recent research on semi-arid rangelands has focused its attention on the evaporative fraction (EF), a
more &raquo; ... y factor to estimate evapotranspiration (ET) in the energy balance (EB) algorithm. EF is strongly linked to the vegetation water status, and works conducted on eddy covariance towers used this parameter to increase the performances of satellite-based biomass estimation. In this work, a method to estimate EF from MODIS products, originally developed for evapotranspiration estimation, is tested and evaluated. Results show that the EF estimation from low spatial resolution over wide semi-arid area is feasible. Estimated EF resulted in being well correlated to field ET measurements, and the spatial patterns of EF maps are in agreement with the well-known climatic and landscape Sahelian features. The preliminary test on rangeland biomass production shows that satellite-retrieved EF as a water availability factor significantly increased the capacity of a remote sensing operational product to detect the variability of the field biomass measurements. OPEN ACCESS Remote Sens. 2014, 6 6301 Keywords: evaporative fraction; semi-arid rangeland; biomass estimation characteristics, such as albedo, vegetation cover, leaf area index and land surface temperature, can be retrieved from satellite observations providing data for ET estimation from space. Since the launch of Earth Observation satellites with thermal infrared channel, such as Landsat Thematic Mapper, NOAA-AVHRR and Terra/Aqua MODIS, several applications have been developed over near fully agricultural canopy covers and semiarid rangeland basins to estimate instantaneous ET and to scale up such estimations to daily ET. One of the widely used methods [22] to estimate daily ET is based on the evaporative fraction (EF), which is defined as the ratio between latent heat flux and the total heat leaving the Earth's surface. A strong correlation between the value of EF at midday and the daytime average value has been observed [23, 24] , and it is often assumed as a constant daytime variable [18, 21, [25] [26] [27] [28] [29] [30] [31] [32] . The EF has a strong link with soil moisture availability [33] , which is the limiting factor of latent heat flux [29] , and it is essentially controlled by water availability in the root zone [34]. The EF behavior at the landscape scale is correlated to the amount of vegetation cover [35], the timing of rainfall events [36], the successions of wet and dry periods [37], the vapor pressure deficit and vegetation photosynthesis activity [38]. EF has an annual behavior related to rainfall events, with peaks during the rainy season and decreasing when soil is drying [39] . In fact, a work conducted over paddy rice area shows that EF always has values close to one, because soil moisture was almost saturated [38] . Recent works conducted in correspondence with eddy covariance stations in North America [39], the northern Australia savannah [40] and the Sahelian region [41] proposed the EF as an indicator of water stress to correct vegetation production estimation. The results of these studies indicated that the use of field-measured EF values within a light use efficiency (LUE) model allows one to improve the estimate of biomass production. EF can be derived from satellite data using the NDVI-temperature triangle method [42] or the simplified surface energy balance index (S-SEBI) model [43] , following the relationship between albedo and land surface temperature [18] . This last approach found applications with a wide range of remotely sensed data and in different ecosystems. The accuracy of EF estimated by S-SEBI was demonstrated in comparison with other approaches, both for high resolution ASTER images [44] and low resolution NOAA-imagery [18] . Daily ET values, estimated via the EF approach, were validated at the field scale with flux measurements on cropland [27] , as well as at the regional scale over the Iberian Peninsula with Digital Airborne Imaging Spectrometer (DAIS) high resolution data [26] . Outside of Europe, the use of this approach has been reported in the Mediterranean landscapes of Chile [45] and in the cotton crops of Brazil [46] , demonstrating the suitability of the method in semi-arid areas. The aim of this work is to retrieve EF from satellite data in the Sahelian rangeland ecosystem and to evaluate the parameter as a moisture indicator, useful also as a correcting factor in the radiation use efficiency biomass estimation model. The application of the S-SEBI method requires the presence of wet and very dry surfaces [26, 43, 47] ; these conditions are well satisfied over the West Africa area, thanks to presence of the Sahara Desert and stable, humid ecosystems, such as the Niger Inner Delta and Lake Chad. In particular, the goals of this research are: (i) to set-up an automatic procedure to derive EF maps
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs6076300">doi:10.3390/rs6076300</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x6yaljvmhvc7rg72aj63h7kqtu">fatcat:x6yaljvmhvc7rg72aj63h7kqtu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321105533/http://space4agri.irea.cnr.it/it/prodotti-della-ricerca/articolo-su-s4a-su-remote-sensing-2014" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/50/d5/50d59c05fb6e6a9438735a57c6309c49c6d43f22.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs6076300"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Estimating Crop Nutritional Status Using Smart Apps to Support Nitrogen Fertilization. A Case Study on Paddy Rice

Livia Paleari, Ermes Movedi, Fosco Vesely, William Thoelke, Sofia Tartarini, Marco Foi, Mirco Boschetti, Francesco Nutini, Roberto Confalonieri
<span title="2019-02-25">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
The within-field variability map was generated from the 6 July 2018 NDRE (Normalized Difference Red-Edge) Sentinel 2 image using k-means clustering according to Nutini et al. [24] .  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190503131639/https://res.mdpi.com/sensors/sensors-19-00981/article_deploy/sensors-19-00981.pdf?filename=&amp;attachment=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3c/b6/3cb6b582dc1fcba6f2e31685b046145966162635.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s19040981"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan

Mirco Boschetti, Andrew Nelson, Francesco Nutini, Giacinto Manfron, Lorenzo Busetto, Massimo Barbieri, Alice Laborte, Jeny Raviz, Francesco Holecz, Mary Mabalay, Alfie Bacong, Eduardo Quilang
<span title="2015-05-26">2015</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
Asian countries strongly depend on rice production for food security. The major rice-growing season (June to October) is highly exposed to the risk of tropical storm related damage. Unbiased and transparent approaches to assess the risk of rice crop damage are essential to support mitigation and disaster response strategies in the region. This study describes and demonstrates a method for rapid, pre-event crop status assessment. The ex-post test case is Typhoon Haiyan and its impact on the rice
more &raquo; ... crop in Leyte Province in the Philippines. A synthetic aperture radar (SAR) derived rice area map was used to delineate the area at risk while crop status at the moment of typhoon landfall was estimated from specific time series analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) data. A spatially explicit indicator of risk of standing crop loss was calculated as the time OPEN ACCESS Remote Sens. 2015, 7 6536 between estimated heading date and typhoon occurrence. Results of the analysis of pre-and post-event SAR images showed that 6500 ha were flooded in northeastern Leyte. This area was also the region most at risk to storm related crop damage due to late establishment of rice. Estimates highlight that about 700 ha of rice (71% of which was in northeastern Leyte) had not reached maturity at the time of the typhoon event and a further 8400 ha (84% of which was in northeastern Leyte) were likely to be not yet harvested. We demonstrated that the proposed approach can provide pre-event, in-season information on the status of rice and other field crops and the risk of damage posed by tropical storms.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs70606535">doi:10.3390/rs70606535</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4nnnxzrqofhchjptpxoqufq6yy">fatcat:4nnnxzrqofhchjptpxoqufq6yy</a> </span>
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A Weekly Indicator of Surface Moisture Status from Satellite Data for Operational Monitoring of Crop Conditions

Francesco Nutini, Daniela Stroppiana, Lorenzo Busetto, Dario Bellingeri, Chiara Corbari, Marco Mancini, Enrico Zini, Pietro Brivio, Mirco Boschetti
<span title="2017-06-09">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
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
more &raquo; ... ity of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator (EF w ) were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EF w 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 EF w 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. 2 of 24 distributed information at province/regional scale can hardly be extrapolated due to heterogeneity of land surface and complexity of the hydrological processes [3]. Since Remote Sensing (RS) data can provide a large variety of information on crop status and surface hydrological conditions, which are of key importance to highlight potential criticalities to support water planning and provide quantitative data for management [4,5], RS techniques are recognized as the only viable means to map ET at regional scale in a consistent and economically feasible way [6]. Instantaneous values of ET at satellite overpass can be used as diagnostics for surface status [7], or as controls for hydrological models through assimilation schemes [8]. Several approaches have been developed to estimate ET and/or indicators of water stress, spanning from simple empirical methods to more complex energy balance models, as fully described in literature reviews [9][10] [11] [12] . The Triangle Method: A Short Review on Past Applications and Recent Improvements Among the available RS-based approaches for ET analysis, the triangle method, based on the work of Price in the early 1990s [13] and later elaborated by Jiang and Islam [14] [15] [16] , has been widely exploited to estimate the Evaporative Fraction (EF), which is the ratio between the latent heat flux and the total available energy at canopy surface [5, 17] . EF is both a key parameter to estimate ET as well as a direct indicator of surface moisture conditions [18] and water stress itself [19, 20] . This approach, regarded as a simplification of more complex models such as the Surface Energy Balance Algorithm for Land (SEBAL) [21] , is suitable for large area monitoring of surface moisture conditions [14, 22] . Among its advantages are the simple parameterization/calibration and its reliance on operational satellite data [6, 20, 23] , which allow to spatially explicitly estimate EF in near real-time over large areas. In its original formulation, the triangle method builds on the triangular shape of the scatter plot of remotely sensed surface/canopy temperature (T s ) versus a Vegetation Index (VI) such as the Normalized Difference Vegetation Index (NDVI) [10, 24] . This scatterplot is used to compute the so-called wet and dry edges: the wet edge corresponds to areas where EF is at maximum (i.e., maximum evapotranspiration) whereas the dry edge corresponds to areas where the EF is close to zero (i.e., limited water availability) [23] . Given two co-registered raster images containing temperature and VI value, EF can then be estimated for each pixel based on its relative position with respect to the two edges (see Section 3.1 for details). Alternative formulations of the method were also proposed in later studies. In particular, using the difference between air surface and air temperature (∆T = T s − T a ) instead than simply T s to build the aforementioned scatterplot was proposed by Moran et al. [25] and Jiang and Islam [16] , and successively adopted by numerous studies (e.g., [26] [27] [28] [29] ). Additionally, other RS-derived indicators of vegetation characteristics (e.g., fractional cover, albedo, etc.) were proposed as an alternative to NDVI for computing the dry and wet edges [6, 30] . The triangle method has been exploited starting from data acquired by several satellite platforms/sensors, among which NOAA-Advanced Very High Resolution Radiometer (AVHRR) [31], Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG SEVIRI) [32], NASA Moderate Resolution Imaging Spectroradiometer (MODIS) [2], Envisat-Advanced Along-Track Scanning Radiometer (AATSR) and Medium Resolution Imaging Spectrometer (MERIS) [23], Landsat Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+) [23] as well as airborne sensors [28]. One of its main advantages is its suitability for hydrological studies where field data availability is limited or missing. Thanks to this, it was implemented in operational monitoring systems such as the EVapotranspiration Assessment from SPAce (EVASPA) tool [33], exploited to derive the Temperature Vegetation Dryness Index (TVDI) [25] used for vegetation water stress detection [34-37] and soil moisture estimation [38,39] in semi-arid, temperate and tropical areas [18] and used to improve the performances of hydrological models [40]. Nevertheless, it is important to remind that several issues should be addressed for a full exploitation of satellite based EF/ET estimations. Sensors 2017, 17, 1338 3 of 24 A first assumption of the method is that incoming energy, aerodynamic properties and atmospheric conditions have to be reasonably uniform over the area at the time of satellite overpass [2,23,32] and the AOI should be as flat as possible in order to identify a proper triangular shape in the pixel distribution [24] . Tave et al. [41] recently tried to solve this requirement by improving the triangle method to compute EF for different elevation zones rather than keeping the estimation of flat area only. Second, a key issue for applying the triangle method is the proper computation of the wet and dry edges, which influences the accuracy of EF estimation [6]. The method can therefore be applied only under specific conditions, in relation to study area characteristics and EO data exploited, and a proper data handling is needed to retrieve reliable estimates. In particular: (i) a large range of combined soil moisture status and vegetation characteristics must be present in the study area to represent a wide range of evapotranspiration conditions [37, 42] , and (ii) this variability must be properly captured by the RS data used. These conditions influence the required extension of the area of interest (AOI) analyzed, which should be sufficiently large [43] to allow the construction of reliable scatterplots as a function of the spatial resolution of the EO data used. According to previous studies, the triangular shape depends more on the number of pixels, rather than on the spatial resolution [24, 44] . Hence, for small AOIs (e.g.,~4000 km 2 ) HR satellite data may allow obtaining more accurate EF estimations. On the other hand, while working with satellite data at coarse resolution the AOI should be bigger since a larger area is needed for an appropriate definition of the triangle shape [23] . If these conditions are not completely fulfilled, the shape of the temperature vs. VI scatterplot may be "flawed" (i.e., not triangular at all), leading the estimated dry and wet edges to be far from the theoretical ones, and therefore to large inaccuracies in EF estimation [32] . To deal with the aforementioned problem, many authors proposed modifications and advancements to the "standard" method allowing a better and more stable computation of the edges. Tang et al. [6] proposed a specific pre-processing technique for identifying outliers in the temperature vs. VI scatterplot space and removing them before the computation of the edges. De Tomas et al. [23] demonstrated how this approach can improve EF estimates when HR data (e.g., Landsat like) are used. Maltese et al. [28] compared scatterplots derived from different dates suggesting that, to cope with the uncertainness in the dry and wet edges identification, a multi-temporal analysis should be exploited to include outer extremes in soil water content. Minacapilli et al. [2] further developed this idea building the temperature vs. VI scatterplot in the temporal domains for each pixel of the AOI using all available dates; application of this approach resulted in an accurate estimation of ET at regional scale. Other recent contributions determined the theoretical edges on the base of the surface energy balance principle rather than by identifying the boundaries empirically in the data space; EF is then estimated for each pixel using the observed temperature vs. VI scatterplot [22, 32] . Comparison with in situ data of soil moisture and EF revealed that this approach could increase the accuracy of the triangle method. However, its implementation requires a more complex parameterization and requires input field data not be always available over the AOI. Another important issue discussed in literature is whether the output of the triangle method can be considered representative of the daily condition or the instantaneous momentum. Most approaches based on satellite data assumed EF to be relatively constant in daytime ("self-preservation of EF" [23]), so that satellite-based instantaneous EF estimates can be representative of daily conditions [30] (see Section 3.1 for details). Nevertheless, for some scientific applications it is necessary to more rigorously upscale the instantaneous estimation to daily conditions taking into account the diurnal cycle using exogenous information such as meteo data [45] . To perform this daily upscaling, Trezza [46] proposed to multiply the instantaneous EF by the daily reference ET computed with FAO approach [47] while Ryu et al. [48] exploited the variations of the daily extraterrestrial solar radiation. Finally, Tang et al. [49] recently presented a promising approach for upscaling, based on half-hourly meteo data (i.e., air temperature, Sensors 2017, 17, 1338 4 of 24
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17061338">doi:10.3390/s17061338</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28598399">pmid:28598399</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5492004/">pmcid:PMC5492004</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k73upfpdsndmzdwme7msjhrcsq">fatcat:k73upfpdsndmzdwme7msjhrcsq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190225154916/http://pdfs.semanticscholar.org/649b/c434c55d641b330dfb3edd6fb424f631e3ba.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/64/9b/649bc434c55d641b330dfb3edd6fb424f631e3ba.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17061338"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492004" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index

Manuel Campos-Taberner, Francisco García-Haro, Gustau Camps-Valls, Gonçal Grau-Muedra, Francesco Nutini, Lorenzo Busetto, Dimitrios Katsantonis, Dimitris Stavrakoudis, Chara Minakou, Luca Gatti, Massimo Barbieri, Francesco Holecz (+2 others)
<span title="2017-03-07">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
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
more &raquo; ... ransfer 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. System (GTOS) and the Global Climate Observing System (GCOS) [1] . Defined as half of the total green leaf area per unit ground surface area [2], LAI plays a key role in land surface models [3] and can be used to address various agricultural issues, such as rice crop monitoring, yield forecasting and crop management [4] . Crop monitoring is necessary to identify the onset of stress conditions, which require actions for reducing their impact on crop yield. Anomaly drops in canopy LAI are indicators of plant stress conditions, which could lead to a decrease of plant production and to an increased senescence rate [5] . Rice yield forecasting is a crucial task for management and planning, and it can be addressed with both statistical and mathematical modeling approaches. Statistical approaches directly link crop biophysical variables, such as LAI, to crop yield. LAI is indeed recognized as the major morphological parameter for determining crop growth, and it is strongly correlated with crop productivity [6] . Crop models are able to simulate rice growing and are used to provide indications on crop status and to predict yields over large areas [7, 8] . However, crop models require information on soil, meteorological variable, crop parameters and management practices, which are not always available or practical to be obtained in a spatially distributed way and during the season [9] . Hence, the best way to simulate the real spatial-temporal differences in crop development of fields sowed the same day with the same variety is to assimilate exogenous observation, such as LAI maps, in the modeling solution [10]. Accurate estimation of LAI has been shown to improve the accuracy of grain yield estimates [11] , and an operational application of this workflow for rice was successfully demonstrated in Asia in the framework of the RIICE (Remote sensing-based Information and Insurance for Crops in Emerging economies) project (http://www.riice.org/) where rice yield is estimated from the Oryza2000 model by assimilating LAI maps derived from synthetic aperture radar (SAR) images [12] . As far as precise crop management is concerned, LAI data have been found to be useful in new approaches for the determination of nitrogen concentration dilution curves, which are traditionally based on plant dry matter (PDM) estimation [13, 14] . Remotely-sensed data at decametric resolution (e.g., Sentinel-2A) are the sole source of information available to provide high-resolution (HR) LAI estimation on wide areas to exploit the nitrogen concentration dilution curve approach for optimal crop fertilization. In the last few years, the scientific community has made big efforts with the goal of providing reliable and accurate LAI estimates at local scales taking advantage of unmanned aerial vehicles and high-resolution sensors, such as Landsat [15] and SPOT5 [16] [17] [18] . The recently launched Sentinel-2A satellite [19] provides well-suited spectral and temporal data for LAI retrieval at high-resolution in near real time, useful for assessing crop status and providing support in agro-practices at the parcel level. Many methods have been proposed and implemented in retrieval chains from Earth observation (EO) data to derive LAI estimates [20] . Empirical parametric algorithms have been developed based on calibrated relationships between vegetation indices and canopy biophysical variables [21] . On the other hand, non-parametric algorithms estimate biophysical variables using a training database containing pairs of the biophysical parameter and the associated spectral data [22] . In statistical approaches, concomitant in situ measurements of the biophysical parameter of interest and the associated spectral data from remote sensing platforms are used as a training database, whereas the hybrid approaches rely on a database generated by radiative transfer models (RTMs). RTMs describe the interactions between the incoming radiation, canopy elements and the background soil surface. The PROSAIL RTM has become one of the most popular and widely-used RTMs due to its consistency and robustness [23] . Hybrid approaches retrieve LAI by inverting RTM through machine learning techniques with a large number of methods [24, 25] . Among them, neural networks (NN) [26] and kernel-based methods [27, 28] are the most popular and used regression methods in remote sensing. State-of-the-art kernel-based methods, such as Gaussian process regression (GPR) [29] , provided encouraging results in the framework of biophysical parameter estimation outperforming other kernel methods and NN [18, 30] .
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs9030248">doi:10.3390/rs9030248</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2v6g3wfey5dhveeuuc7wv67dxy">fatcat:2v6g3wfey5dhveeuuc7wv67dxy</a> </span>
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Comparative Analysis of Normalised Difference Spectral Indices Derived from MODIS for Detecting Surface Water in Flooded Rice Cropping Systems

Mirco Boschetti, Francesco Nutini, Giacinto Manfron, Pietro Alessandro Brivio, Andrew Nelson, Guy J.-P. Schumann
<span title="2014-02-20">2014</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
Identifying managed flooding in paddy fields is commonly used in remote sensing to detect rice. Such flooding, followed by rapid vegetation growth, is a reliable indicator to discriminate rice. Spectral indices (SIs) are often used to perform this task. However, little work has been done on determining which spectral combination in the form of Normalised Difference Spectral Indices (NDSIs) is most appropriate for surface water detection or which thresholds are most robust to separate water from
more &raquo; ... other surfaces in operational contexts. To address this, we conducted analyses on satellite and field spectral data from an agronomic experiment as well as on real farming situations with different soil and plant conditions. Firstly, we review and select NDSIs proposed in the literature, including a new combination of visible and shortwave infrared bands. Secondly, we analyse spectroradiometric field data and satellite data to evaluate mixed pixel effects. Thirdly, we analyse MODIS data and Landsat data at four sites in Europe and Asia to assess NDSI performance in real-world conditions. Finally, we test the performance of the NDSIs on MODIS temporal profiles in the four sites. We also compared the NDSIs against a combined index previously used for agronomic flood detection. Analyses suggest that NDSIs using MODIS bands 4 and 7, 1 and 7, 4 and 6 or 1 and 6 perform best. A common threshold for each NDSI across all sites was more appropriate than locally adaptive thresholds. In general, NDSIs that use band 7 have a negligible increase in Commission Error over those that use band 6 but are more sensitive to water presence in mixed land cover conditions typical of moderate spatial resolution analyses. The best performing NDSI is comparable to the combined index but with less variability in performance across sites, suggesting a more succinct and robust flood detection method.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0088741">doi:10.1371/journal.pone.0088741</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/24586381">pmid:24586381</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3930609/">pmcid:PMC3930609</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dzsyq4splzgwjfing7ydimfdqu">fatcat:dzsyq4splzgwjfing7ydimfdqu</a> </span>
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Page 124 of The Musical Quarterly Vol. 22, Issue 1 [page]

<span title="">1936</span> <i title="Oxford Publishing Limited(England)"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_musical-quarterly" style="color: black;">The Musical Quarterly </a> </i> &nbsp;
Milano: Erta, 1935. 173 P» Larionov, P., AND FRANCESCO PESTELLINI Maria Malibran e i suoi tempi. 253 p, 8°. Firenze: R. Bemporad e Figlio, 1935.  ...  Nutini, 1935. Bruno, GINEVRA Cenni riassuntivi di storia della musica. 135 p. Avellino: Tip. Pergola, 1934. FaRAONE, AUSANO Il Comm. Ladislao Zavertal, ‘“‘direttore d’orchestra ¢ compositore.”  ... 
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Results from the Cuore Experiment †

Alessio Caminata, Douglas Adams, Chris Alduino, Krystal Alfonso, Frank Avignone, Oscar Azzolini, Giacomo Bari, Fabio Bellini, Giovanni Benato, Andrea Bersani, Matteo Biassoni, Antonio Branca (+102 others)
<span title="2019-01-02">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vccdvorg3fbgppqlyxxkdsvlfm" style="color: black;">Universe</a> </i> &nbsp;
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 TeO 2 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
more &raquo; ... present the neutrinoless double beta decay results of CUORE from examining a total TeO 2 exposure of 86.3 kg 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 130 Te > 1.3 · 10 25 yr (90% C.L.). Moreover, an analysis of the background of the experiment is presented as well as the measurement of the 130 Te 2 ν β β decay with a resulting half-life of T 1 / 2 2 ν = [ 7.9 ± 0.1 ( stat . ) ± 0.2 ( syst . ) ] × 10 20 yr which is the most precise measurement of the half-life and compatible with previous results.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/universe5010010">doi:10.3390/universe5010010</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hnkmtwssirgz7epevt5z2glywe">fatcat:hnkmtwssirgz7epevt5z2glywe</a> </span>
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Page 147 of The Athenaeum Vol. , Issue 2544 [page]

<span title="1876-07-29">1876</span> <i title="New Statesman Ltd"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_athenaeum-uk" style="color: black;">The Athenaeum </a> </i> &nbsp;
Bernardo Bandini and Francesco de’ Pazzi were the assassins of Giu- liano de’ Medici, in the Cathedral of Florence.  ...  History ‘ely in- plendid Indian lued it General p. 339, ably for will be be pro ot only , which "y grain pon the yped up e most, odes in works are his > of the m pany. born in r, left it n years he East nutiny  ... 
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Acknowledgement to Reviewers of Remote Sensing in 2015

<span title="2016-01-21">2016</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
, Francesco O'Connell, Jessica L.  ...  Fassnacht, Fabian Fasullo, John Fava, Francesco Pietro Fearns, Peter Feigl, Kurt L.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs8010081">doi:10.3390/rs8010081</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tewflx4robeulikaupjih77jue">fatcat:tewflx4robeulikaupjih77jue</a> </span>
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A high-resolution, integrated system for rice yield forecasting at district level

Valentina Pagani, Tommaso Guarneri, Lorenzo Busetto, Luigi Ranghetti, Mirco Boschetti, Ermes Movedi, Manuel Campos-Taberner, Francisco Javier Garcia-Haro, Dimitrios Katsantonis, Dimitris Stavrakoudis, Elisabetta Ricciardelli, Filomena Romano (+5 others)
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/r3xcuv6v75dl7dxbvok7sn3nnq" style="color: black;">Agricultural Systems</a> </i> &nbsp;
., Nutini, F., Manfron, G., Brivio, P.A., Nelson, A., 2014.  ...  DOI: 10.1016/j.eja.2016.02.009 514 Campos-Taberner, M., García-Haro, F.J., Camps-Valls, G., Grau-Muedra, G., Nutini, F., Busetto, L., 515 Katsantonis, D., Stavrakoudis, D., Minakou, C., Gatti, L., Barbieri  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.agsy.2018.05.007">doi:10.1016/j.agsy.2018.05.007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4sn5llmlvjejvdg24apd3hbecu">fatcat:4sn5llmlvjejvdg24apd3hbecu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305062326/http://repositori.uji.es/xmlui/bitstream/handle/10234/182258/57937.pdf;jsessionid=222054843B6954B92E5893547B565BC6?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b1/07/b1070382f957228ea3076b7eec57643d573ceb90.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.agsy.2018.05.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Firenze e Pistoia: Governo del territorio e fazioni cittadine

Luca Vannini
<span title="2015-08-30">2015</span> <i title="Departmento de Publicaciones del CSIC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nd4tzx5wyrgjzd622pa37bdmgu" style="color: black;">Hispania</a> </i> &nbsp;
Ricordi di Francesco Ricciardi 52 .  ...  Come ricostruito da Connell con dovizia di particolari, fu proprio l'intervento del Rucellai in favore del suo cliente di parte cancelliera, Bernardo Nutini, a consentire al vescovo Pandolfini (anch'egli  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3989/hispania.2015.011">doi:10.3989/hispania.2015.011</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yrm3uubntjhgfobrmdra22yuym">fatcat:yrm3uubntjhgfobrmdra22yuym</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721212659/http://hispania.revistas.csic.es/index.php/hispania/article/download/458/454" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/38/d2/38d25033d4b01922737d09f589ca6c89a37c107a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3989/hispania.2015.011"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Libertà e prosperità: l'economia politica dell'Italia rivoluzionaria (1796-1799)

Cecilia Carnino
<span title="2018-06-18">2018</span> <i title="OpenEdition"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m5l5xu4y4rbkzjdi3wxleqjgau" style="color: black;">La Révolution française</a> </i> &nbsp;
Francesco MILIZIA, Economia pubblica spiegata in diciotto capitoli dal cittadino Francesco Milizia. Opera postuma molto interessante a tutti, Roma, Petretti, 1798.  ...  Citato anche in Stefano NUTINI, «Problemi annonari e protesta popolare in Lombardia alla fine del settecento», Società e storia, n° 38, 1987, p. 847-876. 22.  ... 
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REFLEXIONES EN TORNO A LA PRIMERA EDICIÓN MILANESA (1801) DE LA CIENCIA NUEVA DE GIAMBATTISTA VICO

Maurizio Martirano
<span title="">2021</span> <i title="Editorial Universidad de Sevilla"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3vzpqucpvreorks3kcnlyoudfm" style="color: black;">Cuadernos sobre Vico</a> </i> &nbsp;
DE FRANCESCO, Vincenzo Cuoco.  ...  DE FRANCESCO, Mito e storiografia della «Grande Rivoluzione». La rivoluzione francese nella cultura politica italiana del '900, Nápolesi, Guida, 2006, pp. 31-38. 87.  ...  NUTINI, op. cit., y S. FARAONI, Giulio Ferrario, intellettuale milanese ed editore della Società Tipografica de' Classici Italiani, cit., que sin embargo no explican los motivos de la oposición.  ... 
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