617 research outputs found
Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas
In this paper, multifrequency synthetic aperture radar (SAR) images from ALOS/PALSAR, ENVISAT/ASAR and CosmoâSkyMed sensors were studied for forest classification in a test area in Central Italy (San Rossore), where detailed inâsitu measurements were available. A preliminary discrimination of the main land cover classes and forest types was carried out by exploiting the synergy among Lâ, Câ and Xâbands and different polarizations. SAR data were preliminarily inspected to assess the capabilities of discriminating forest from nonâforest and separating broadleaf from coniferous forests. The temporal average backscattering coefficient (°) was computed for each sensorâpolarization pair and labeled on a pixel basis according to the reference map. Several classification methods based on the machine learning framework were applied and validated considering different features, in order to highlight the contribution of bands and polarizations, as well as to assess the classifiersâ performance. The experimental results indicate that the different surface types are best identified by using all bands, followed by joint Lâ and Xâ bands. In the former case, the best overall average accuracy (83.1%) is achieved by random forest classification. Finally, the classification maps on class edges are discussed to highlight the misclassification errors
Biomass retrieval based on genetic algorithm feature selection and support vector regression in Alpine grassland using ground-based hyperspectral and Sentinel-1 SAR data
A general framework for the integration of multi-sensor data for dry and fresh biomass retrieval is proposed and tested in Alpine meadows and pastures. To this purpose, hyperspectral spectroradiometer (as simulation of hyperspectral imagery) and biomass samples were collected in field campaigns and Copernicus Sentinel-1 Interferometric Wide (IW) swath SAR backscattering coefficients were used. First, a genetic algorithm feature selection was performed on hyperspectral data, and afterwards the resulting most sensitive bands where combined with SAR data within a support vector regression (SVR) model. The most sensitive hyperspectral bands were mainly located in different regions of the SWIR range for both fresh and dry biomass, and in the red and near-infrared regions mainly for dry biomass, but with less influence for fresh biomass. The R (2) correlation values between the sampled and the estimated biomass range from 0.24 to 0.71. The relatively low performances are mainly related to the saturation effect in the optical bands, as well as to the paucity of points for high values of biomass. The methodology allows a better understanding of the interaction between grassland systems and the electromagnetic spectrum by offering a model with a reduced number of narrow bands in the context of a multi-sensor integration
Deriving wheat crop productivity indicators using Sentinel-1 time series
High-frequency Earth observation (EO) data have been shown to be effective in identifying crops and monitoring their development. The purpose of this paper is to derive quantitative indicators of crop productivity using synthetic aperture radar (SAR). This study shows that the field-specific SAR time series can be used to characterise growth and maturation periods and to estimate the performance of cereals. Winter wheat fields on the Rothamsted Research farm in Harpenden (UK) were selected for the analysis during three cropping seasons (2017 to 2019). Average SAR backscatter from Sentinel-1 satellites was extracted for each field and temporal analysis was applied to the backscatter cross-polarisation ratio (VH/VV). The calculation of the different curve parameters during the growing period involves (i) fitting of two logistic curves to the dynamics of the SAR time series, which describe timing and intensity of growth and maturation, respectively; (ii) plotting the associated first and second derivative in order to assist the determination of key stages in the crop development; and (iii) exploring the correlation matrix for the derived indicators and their predictive power for yield. The results show that the day of the year of the maximum VH/VV value was negatively correlated with yield (r = â0.56), and the duration of âfullâ vegetation was positively correlated with yield (r = 0.61). Significant seasonal variation in the timing of peak vegetation (p = 0.042), the midpoint of growth (p = 0.037), the duration of the growing season (p = 0.039) and yield (p = 0.016) were observed and were consistent with observations of crop phenology. Further research is required to obtain a more detailed picture of the uncertainty of the presented novel methodology, as well as its validity across a wider range of agroecosystem
Integrazione di tecniche di agricoltura biologica e conservativa in sistemi colturali con crescente intensitĂ ecologica: il progetto F.I.R.B. SMOCA
Il progetto SMOCA (Smart Management of Organic Conservative Agriculture) (2014- 2017) mira ad incrementare la sostenibilitaÌ dei sistemi colturali integrati/biologici mediante lâintroduzione di tecniche di agricoltura conservativa, finalizzate alla riduzione dei consumi energetici e al miglioramento della fertilitaÌ del terreno. In SMOCA saranno sviluppate macchine e strategie agronomiche innovative che permettano di applicare le tecniche di lavorazione ridotta anche in assenza di mezzi chimici di sintesi
Remote Sensing of Forest Biomass Using GNSS Reflectometry
In this study, the capability of Global Navigation Satellite System Reflectometry in evaluating forest biomass from space has been investigated by using data coming from the TechDemoSat-1 (TDS-1) mission of Surrey Satellite Technology Ltd. and from the Cyclone Satellite System (CyGNSS) mission of NASA. The analysis has been first conducted using TDS-1 data on a local scale, by selecting five test areas located in different parts of the Earth's surface. The areas were chosen as examples of various forest coverages, including equatorial and boreal forests. Then, the analysis has been extended by using CyGNSS to a global scale, including any type of forest coverage. The peak of the Delay Doppler Map calibrated to retrieve an "equivalent" reflectivity has been exploited for this investigation and its sensitivity to forest parameters has been evaluated by a direct comparison with vegetation optical depth (VOD) derived from the Soil Moisture Active Passive L-band radiometer, with a pantropical aboveground biomass (AGB) map and then with a tree height (H) global map derived from the Geoscience Laser Altimeter System installed on-board the ICEsat satellite. The sensitivity analysis confirmed the decreasing trend of the observed equivalent reflectivity for increasing biomass, with correlation coefficients 0.31 †R †0.54 depending on the target parameter (VOD, AGB, or H) and on the considered dataset (local or global). These correlations were not sufficient to retrieve the target parameters by simple inversion of the direct relationships. The retrieval has been therefore based on Artificial Neural Networks making it possible to add other inputs (e.g., the incidence angle, the signal to noise ratio, and the lat/lon information in case of global maps) to the algorithm. Although not directly correlated to the biomass, these inputs helped in improving the retrieval accuracy. The algorithm was tested on both the selected areas and globally, showing a promising ability to retrieve the target parameter, either AGB or H, with correlation coefficients R â 0.8
Eranet-Med Optimed- Water Project: Results on soil Moisture Maps of Semi-Arid Environment by using Optical/Microwave Satellite Data
This project deals with the implementation of an
innovative water management system in Mediterranean
countries (i.e. Tunisia and Egypt), which suffer from chronic
water scarcity, together with two European countries
(Germany and Italy). The consortium is developing and
applying synergic methods and algorithms for investigating
the water cycle, using remote sensing techniques.
The focus is on the use of satellite data (optical and
microwave) for monitoring vegetation cover and water status
along with soil moisture temporal evolutions in order to
improve the knowledge of the water cycle in arid areas. Both
local and regional monitoring are carried out in order to
investigate different spatial scales.
The scope of the project is to propose practical and costeffective solutions for driving and updating a method for the
sustainable use of water in agriculture.
First results on soil moisture mapping retrieved in Tunisia
using an Artificial Neural Network (ANN) based algorithm is
presented in this pap
Les droits disciplinaires des fonctions publiques : « unification », « harmonisation » ou « distanciation ». A propos de la loi du 26 avril 2016 relative à la déontologie et aux droits et obligations des fonctionnaires
The production of tt⟠, W+bb⟠and W+cc⟠is studied in the forward region of protonâproton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98±0.02 fbâ1 . The W bosons are reconstructed in the decays WââÎœ , where â denotes muon or electron, while the b and c quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions.The production of , and is studied in the forward region of proton-proton collisions collected at a centre-of-mass energy of 8 TeV by the LHCb experiment, corresponding to an integrated luminosity of 1.98 0.02 \mbox{fb}^{-1}. The bosons are reconstructed in the decays , where denotes muon or electron, while the and quarks are reconstructed as jets. All measured cross-sections are in agreement with next-to-leading-order Standard Model predictions
Observation of the B0 â Ï0Ï0 decay from an amplitude analysis of B0 â (Ï+Ïâ)(Ï+Ïâ) decays
Protonâproton collision data recorded in 2011 and 2012 by the LHCb experiment, corresponding to an integrated luminosity of 3.0 fbâ1 , are analysed to search for the charmless B0âÏ0Ï0 decay. More than 600 B0â(Ï+Ïâ)(Ï+Ïâ) signal decays are selected and used to perform an amplitude analysis, under the assumption of no CP violation in the decay, from which the B0âÏ0Ï0 decay is observed for the first time with 7.1 standard deviations significance. The fraction of B0âÏ0Ï0 decays yielding a longitudinally polarised final state is measured to be fL=0.745â0.058+0.048(stat)±0.034(syst) . The B0âÏ0Ï0 branching fraction, using the B0âÏKâ(892)0 decay as reference, is also reported as B(B0âÏ0Ï0)=(0.94±0.17(stat)±0.09(syst)±0.06(BF))Ă10â6
A study of CP violation in B-+/- -> DK +/- and B-+/- -> D pi(+/-) decays with D -> (KSK +/-)-K-0 pi(-/+) final states
A first study of CP violation in the decay modes and , where labels a or meson and labels a or meson, is performed. The analysis uses the LHCb data set collected in collisions, corresponding to an integrated luminosity of 3 fb. The analysis is sensitive to the CP-violating CKM phase through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of using other decay modes
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